Excel Questions to be Answered in a Period of Time

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Quizes Examples/Build Your First Model .docx

1. Which of these sentences provides the best definition of a model?

A method used by companies to predict future performance

A set of processes that accepts inputs from a user and returns valuable output results

A simplified version of reality used by analysts to help make better decisions

A method used by companies to analyze past performance

2. Which of these is not a characteristic of a badly structured problem?

There are no clear objectives for the analysis

Not all the assumptions to be made are obvious

Not enough time is available to complete the analysis

Not all the necessary data is available

3. Which of these is the final stage of Powell & Batt's 4-stage modeling process?

Build the model

Diagram the problem

Frame the problem

Generate insights

4. Which component of an influence diagram is represented by a rectangle?

Decision variable

Parameter

Intermediate variable

Outcome

5. Which of these sheets in an Excel model is most likely to contain the problem statement for the model?

Cover sheet

Dataset

Control panel

Influence diagram

6. In the 'sample_single_flight' sheet of this exam's Excel file, what is the total number of bumped customers for the given input values?

7. In the 'sample_single_flight' sheet of this exam's Excel file, what is the total amount of additional profit for the given input values?

8. In the 'sample_single_flight' sheet of this exam's Excel file, increase the booking limit from 193 to 215 seats and increase the Price per ticket from $165 to $250. What is the total additional profit after making these changes?

9. Consider the scenario in the 'sample_single_flight' sheet of this exam's Excel file. If you wanted to guarantee that you would never lose money on any flight due to overbooking, what booking limit would you set?

10. In the 'sample_single_flight' sheet of this exam's Excel file, create a sensitivity analysis for the booking limit and no-shows using the table provided. What booking limit maximizes the total additional profit if the number of no-shows is 12?

11. In the 'sample_single_flight' sheet of this exam's Excel file, adjust the Price per ticket in the model from $250 to $165. After doing this, which of these is not a risk highlighted by the sensitivity analysis of the booking limit and no-shows?

If the average number of no-shows is 3, then losses occur at most booking limits

Booking limits of 200 or below usually lead to losses for any number of no-shows

The optimal booking limit is uncertain because it varies based on the number of no-shows

Losses are likely if the booking limit is high and the number of no-shows is low

12. When should a model input be added to the control panel, and not included in the data set?

When the input has the same value for every row in the data set

When the input has been named using the Name Manager

When the input is one that the user should not be able to adjust

When the input is calculated using a formula

13. In the 'dataset' sheet of this exam's Excel file, which of these cells is not used to calculate the figure in cell L11?

D11D12H11O12

14. In the 'control_panel' sheet of this exam's Excel file, what is the booking limit that maximizes total additional profit for the given set of input values?

15. In the 'control_panel' sheet of this exam's Excel file, what is the booking limit (to the nearest whole number) that results in a total additional profit of 0? (Hint: The answer should be greater than the optimal booking limit)

16. In the 'control_panel' sheet of this exam's Excel file, return the booking limit to 200 seats. After doing this, use the data from the 'dataset' sheet to calculate the total additional profit contributed by flights from London to Paris.

Quizes Examples/Build Your First Model exam.xlsx

influence_diagram

sample_single_flight

Blue indicates hard-coded numbers or inputs
Black indicates formulas or text
Green indicates links from other worksheets
Decision variables Intermediate variables Outputs
Booking limit 193 seats Total bookings
Additional Revenue
Fixed assumptions # extra bookings
Capacity per flight 180 seats Additional Cost
# bumped customers
Projections Additional Profit
Demand 210 (Change in value)
Price per ticket $ 165.00
# no shows per flight 7
unit bumping cost $ 280.00
Booking limit
180 185 190 195 200 205 210
No-shows 3
6
9
12
15
18

control_panel

Blue indicates hard-coded numbers or inputs
Black indicates formulas or text
Green indicates links from other worksheets
Inputs Outputs
Decision variable Total Additional Revenue $ 906,462.65
Booking limit 190 seats
Total Additional Cost $ 134,790.55
Fixed assumptions % due to high-cost bumped 30%
Capacity per flight 180 seats % due to low-cost bumped 70%
Low-cost bumped price $ 130.00
High-cost bumped price $ 280.00 Total Additional Profit $ 771,672.10
Variable assumptions
Conversion rate 16.85%
Aidan: Aidan: Average value of the conversion rates calculated in model. Sensitivity test should be performed

dataset

Blue indicates hard-coded numbers or inputs
Black indicates formulas or text
Green indicates links from other worksheets
Day Dep time From To Number of price quotes given Bookings completed Flight revenue (£) # no-shows Conversion rate
Aidan: Aidan: = Bookings completed / Price quotes, but only for flights that not full. 		Demand
Aidan: Aidan: If flight full, = # price quotes x conversion rate. Otherwise, equal to bookings completed		 Price per ticket
Aidan: Aidan: Conservative assumption: Additional price per ticket = average ticket price per flight		 # free seats available
Aidan: Aidan: Returns a positive numberif a later flight exists and free seats are available on that flight		 # low-cost bumped
Aidan: Aidan: Returns the lower value of # bumped customers and # free seats available		 # high cost bumped
Aidan: Aidan: # Bumped customers - # low-cost bumped customers
Aidan: Aidan: = Bookings completed / Price quotes, but only for flights that not full.
Aidan: Aidan: If flight full, = # price quotes x conversion rate. Otherwise, equal to bookings completed
Aidan: Aidan: Conservative assumption: Additional price per ticket = average ticket price per flight		 # Total bookings # Extra bookings # Bumped customers Total additional revenue Total additional cost LC Total additional cost HC Total additional profit
1 7:00 London Paris 1632 180 20,460 9 275 113.6666666667 17 1 0 190 10 1 1137 130 0 1007
1 10:15 London Paris 932 172 18,539 9 18% 172 107.7848837209 0 0 0 172 0 0 0 0 0 0
1 19:30 Paris London 1183 180 26,964 3 199 149.8 34 7 0 190 10 7 1498 910 0 588
1 22:00 Paris London 983 150 15,644 4 15% 150 104.2933333333 0 0 0 150 0 0 0 0 0 0
1 6:50 London Madrid 1526 180 21,566 4 257 119.8111111111 71 6 0 190 10 6 1198 780 0 418
1 9:30 London Madrid 804 123 12,559 14 15% 123 102.1056910569 0 0 0 123 0 0 0 0 0 0
1 19:00 Madrid London 1266 180 24,295 12 213 134.9722222222 20 0 0 190 10 0 1350 0 0 1350
1 21:30 Madrid London 1034 177 15,209 17 17% 177 85.9265536723 0 0 0 177 0 0 0 0 0 0
1 7:10 London Berlin 1097 180 17,140 4 185 95.2222222222 2 1 0 185 5 1 465 115 0 350
1 9:15 London Berlin 1144 180 23,014 12 193 127.8555555556 0 0 0 190 10 0 1279 0 0 1279
1 18:30 Berlin London 1108 180 16,118 7 187 89.5444444444 24 0 0 187 7 0 604 0 0 604
1 20:30 Berlin London 1012 180 15,198 15 171 84.4333333333 0 0 0 171 0 0 0 0 0 0
1 6:30 London Brussels 999 179 20,240 18 18% 179 113.0726256983 71 0 0 179 0 0 0 0 0 0
1 8:45 London Brussels 813 125 11,919 16 15% 125 95.352 0 0 0 125 0 0 0 0 0 0
1 18:50 Brussels London 1583 180 20,562 20 267 114.2333333333 58 0 0 190 10 0 1142 0 0 1142
1 21:05 Brussels London 812 180 16,118 15 137 89.5444444444 0 0 0 137 0 0 0 0 0 0
2 7:00 London Paris 1704 180 19,970 10 287 110.9444444444 56 0 0 190 10 0 1109 0 0 1109
2 10:15 London Paris 808 136 9,895 12 17% 136 72.7573529412 0 0 0 136 0 0 0 0 0 0
2 19:30 Paris London 1647 180 27,098 20 278 150.5444444444 59 0 0 190 10 0 1505 0 0 1505
2 22:00 Paris London 950 145 14,239 24 15% 145 98.2 0 0 0 145 0 0 0 0 0 0
2 6:50 London Madrid 1540 180 18,552 22 260 103.0666666667 34 0 0 190 10 0 1031 0 0 1031
2 9:30 London Madrid 1050 161 15,380 15 15% 161 95.5279503106 0 0 0 161 0 0 0 0 0 0
2 19:00 Madrid London 1180 180 26,078 18 199 144.8777777778 46 0 0 190 10 0 1449 0 0 1449
2 21:30 Madrid London 858 138 14,815 4 16% 138 107.3550724638 0 0 0 138 0 0 0 0 0 0
2 7:10 London Berlin 1061 175 22,624 16 16% 175 129.28 47 0 0 175 0 0 0 0 0 0
2 9:15 London Berlin 919 180 16,977 22 155 94.3166666667 0 0 0 155 0 0 0 0 0 0
2 18:30 Berlin London 1760 180 20,847 21 297 115.8166666667 30 0 0 190 10 0 1158 0 0 1158
2 20:30 Berlin London 962 180 18,886 12 162 104.9222222222 0 0 0 162 0 0 0 0 0 0
2 6:30 London Brussels 1596 180 22,150 13 269 123.0555555556 43 0 0 190 10 0 1231 0 0 1231
2 8:45 London Brussels 694 165 13,635 28 24% 165 82.6363636364 0 0 0 165 0 0 0 0 0 0
2 18:50 Brussels London 1984 180 25,188 15 334 139.9333333333 48 0 0 190 10 0 1399 0 0 1399
2 21:05 Brussels London 1162 140 12,965 8 12% 140 92.6071428571 0 0 0 140 0 0 0 0 0 0
3 7:00 London Paris 1306 180 25,508 25 220 141.7111111111 42 0 0 190 10 0 1417 0 0 1417
3 10:15 London Paris 958 180 22,981 23 161 127.6722222222 0 0 0 161 0 0 0 0 0 0
3 19:30 Paris London 864 180 22,198 15 146 123.3222222222 5 0 0 146 0 0 0 0 0 0
3 22:00 Paris London 1188 180 17,802 15 200 98.9 0 0 0 190 10 0 989 0 0 989
3 6:50 London Madrid 1561 180 19,087 5 263 106.0388888889 24 5 0 190 10 5 1060 650 0 410
3 9:30 London Madrid 1051 180 21,934 21 177 121.8555555556 0 0 0 177 0 0 0 0 0 0
3 19:00 Madrid London 1582 180 24,423 10 267 135.6833333333 23 0 0 190 10 0 1357 0 0 1357
3 21:30 Madrid London 1116 176 16,011 19 16% 176 90.9715909091 0 0 0 176 0 0 0 0 0 0
3 7:10 London Berlin 1198 176 20,430 20 15% 176 116.0795454545 14 0 0 176 0 0 0 0 0 0
3 9:15 London Berlin 1434 180 18,396 24 242 102.2 0 0 0 190 10 0 1022 0 0 1022
3 18:30 Berlin London 1116 180 27,735 17 188 154.0833333333 27 0 0 188 8 0 1247 0 0 1247
3 20:30 Berlin London 1150 163 15,568 10 14% 163 95.509202454 0 0 0 163 0 0 0 0 0 0
3 6:30 London Brussels 1168 180 18,271 22 197 101.5055555556 47 0 0 190 10 0 1015 0 0 1015
3 8:45 London Brussels 821 137 11,912 4 17% 137 86.9489051095 0 0 0 137 0 0 0 0 0 0
3 18:50 Brussels London 2180 180 21,251 19 367 118.0611111111 59 0 0 190 10 0 1181 0 0 1181
3 21:05 Brussels London 1025 141 11,040 20 14% 141 78.2978723404 0 0 0 141 0 0 0 0 0 0
4 7:00 London Paris 2460 180 23,516 22 415 130.6444444444 22 0 0 190 10 0 1306 0 0 1306
4 10:15 London Paris 1047 162 19,445 4 15% 162 120.0308641975 0 0 0 162 0 0 0 0 0 0
4 19:30 Paris London 1498 180 26,883 14 252 149.35 43 0 0 190 10 0 1494 0 0 1494
4 22:00 Paris London 911 180 18,434 17 154 102.4111111111 0 0 0 154 0 0 0 0 0 0
4 6:50 London Madrid 1542 180 19,344 20 260 107.4666666667 32 0 0 190 10 0 1075 0 0 1075
4 9:30 London Madrid 828 164 17,166 16 20% 164 104.6707317073 0 0 0 164 0 0 0 0 0 0
4 19:00 Madrid London 1966 180 22,817 21 331 126.7611111111 62 0 0 190 10 0 1268 0 0 1268
4 21:30 Madrid London 1007 136 11,733 18 14% 136 86.2720588235 0 0 0 136 0 0 0 0 0 0
4 7:10 London Berlin 1997 180 23,093 10 337 128.2944444444 32 0 0 190 10 0 1283 0 0 1283
4 9:15 London Berlin 993 180 13,218 19 167 73.4333333333 0 0 0 167 0 0 0 0 0 0
4 18:30 Berlin London 1224 180 16,798 10 206 93.3222222222 49 0 0 190 10 0 933 0 0 933
4 20:30 Berlin London 966 142 10,404 11 15% 142 73.2676056338 0 0 0 142 0 0 0 0 0 0
4 6:30 London Brussels 1643 180 26,234 9 277 145.7444444444 43 1 0 190 10 1 1457 130 0 1327
4 8:45 London Brussels 926 150 12,787 13 16% 150 85.2466666667 0 0 0 150 0 0 0 0 0 0
4 18:50 Brussels London 2107 180 19,207 11 355 106.7055555556 27 0 0 190 10 0 1067 0 0 1067
4 21:05 Brussels London 796 176 13,016 23 22% 176 73.9545454545 0 0 0 176 0 0 0 0 0 0
5 7:00 London Paris 1872 180 26,601 19 316 147.7833333333 60 0 0 190 10 0 1478 0 0 1478
5 10:15 London Paris 998 142 14,571 22 14% 142 102.6126760563 0 0 0 142 0 0 0 0 0 0
5 19:30 Paris London 1332 180 23,166 12 224 128.7 45 0 0 190 10 0 1287 0 0 1287
5 22:00 Paris London 1103 156 13,690 21 14% 156 87.7564102564 0 0 0 156 0 0 0 0 0 0
5 6:50 London Madrid 1280 180 25,560 7 216 142 29 3 0 190 10 3 1420 390 0 1030
5 9:30 London Madrid 1140 165 16,781 14 14% 165 101.703030303 0 0 0 165 0 0 0 0 0 0
5 19:00 Madrid London 1581 180 20,439 7 266 113.55 49 3 0 190 10 3 1136 390 0 746
5 21:30 Madrid London 727 141 12,953 10 19% 141 91.865248227 0 0 0 141 0 0 0 0 0 0
5 7:10 London Berlin 996 180 22,830 4 168 126.8333333333 0 0 0 168 0 0 0 0 0 0
5 9:15 London Berlin 1396 180 23,152 2 235 128.6222222222 0 0 8 190 10 8 1286 0 2240 -954
5 18:30 Berlin London 1295 180 20,158 7 218 111.9888888889 47 3 0 190 10 3 1120 390 0 730
5 20:30 Berlin London 1104 147 12,341 14 13% 147 83.9523809524 0 0 0 147 0 0 0 0 0 0
5 6:30 London Brussels 883 180 21,170 22 149 117.6111111111 73 0 0 149 0 0 0 0 0 0
5 8:45 London Brussels 758 128 13,283 21 17% 128 103.7734375 0 0 0 128 0 0 0 0 0 0
5 18:50 Brussels London 1566 180 26,208 10 264 145.6 67 0 0 190 10 0 1456 0 0 1456
5 21:05 Brussels London 744 180 13,729 12 125 76.2722222222 0 0 0 125 0 0 0 0 0 0
6 7:00 London Paris 1651 180 21,908 6 278 121.7111111111 16 4 0 190 10 4 1217 520 0 697
6 10:15 London Paris 916 176 16,299 12 19% 176 92.6079545455 0 0 0 176 0 0 0 0 0 0
6 19:30 Paris London 1485 180 24,813 18 250 137.85 58 0 0 190 10 0 1379 0 0 1379
6 22:00 Paris London 825 180 18,196 17 139 101.0888888889 0 0 0 139 0 0 0 0 0 0
6 6:50 London Madrid 1205 180 25,611 16 203 142.2833333333 49 0 0 190 10 0 1423 0 0 1423
6 9:30 London Madrid 918 137 13,161 6 15% 137 96.0656934307 0 0 0 137 0 0 0 0 0 0
6 19:00 Madrid London 1569 180 21,776 21 264 120.9777777778 21 0 0 190 10 0 1210 0 0 1210
6 21:30 Madrid London 985 180 13,231 7 166 73.5055555556 0 0 0 166 0 0 0 0 0 0
6 7:10 London Berlin 1087 176 18,935 6 16% 176 107.5852272727 48 0 0 176 0 0 0 0 0 0
6 9:15 London Berlin 993 140 14,418 8 14% 140 102.9857142857 0 0 0 140 0 0 0 0 0 0
6 18:30 Berlin London 1200 180 18,144 15 202 100.8 13 0 0 190 10 0 1008 0 0 1008
6 20:30 Berlin London 1027 180 15,942 6 173 88.5666666667 0 0 0 173 0 0 0 0 0 0
6 6:30 London Brussels 1659 180 20,873 22 280 115.9611111111 95 0 0 190 10 0 1160 0 0 1160
6 8:45 London Brussels 529 108 11,048 23 20% 108 102.2962962963 0 0 0 108 0 0 0 0 0 0
6 18:50 Brussels London 1777 180 18,832 8 299 104.6222222222 34 2 0 190 10 2 1046 260 0 786
6 21:05 Brussels London 896 180 17,112 5 151 95.0666666667 0 0 0 151 0 0 0 0 0 0
7 7:00 London Paris 1904 180 24,312 18 321 135.0666666667 31 0 0 190 10 0 1351 0 0 1351
7 10:15 London Paris 1005 156 11,711 7 16% 156 75.0705128205 0 0 0 156 0 0 0 0 0 0
7 19:30 Paris London 1118 180 23,776 27 188 132.0888888889 41 0 0 188 8 0 1113 0 0 1113
7 22:00 Paris London 1154 157 14,998 18 14% 157 95.5286624204 0 0 0 157 0 0 0 0 0 0
7 6:50 London Madrid 1893 180 21,806 29 319 121.1444444444 56 0 0 190 10 0 1211 0 0 1211
7 9:30 London Madrid 1181 143 11,038 19 12% 143 77.1888111888 0 0 0 143 0 0 0 0 0 0
7 19:00 Madrid London 2272 180 21,952 23 383 121.9555555556 85 0 0 190 10 0 1220 0 0 1220
7 21:30 Madrid London 688 180 13,580 21 116 75.4444444444 0 0 0 116 0 0 0 0 0 0
7 7:10 London Berlin 1548 180 26,287 27 261 146.0388888889 16 0 0 190 10 0 1460 0 0 1460
7 9:15 London Berlin 1371 180 22,459 26 231 124.7722222222 0 0 0 190 10 0 1248 0 0 1248
7 18:30 Berlin London 1300 180 16,729 9 219 92.9388888889 40 1 0 190 10 1 929 130 0 799
7 20:30 Berlin London 1012 148 15,008 8 15% 148 101.4054054054 0 0 0 148 0 0 0 0 0 0
7 6:30 London Brussels 1171 180 18,340 19 197 101.8888888889 77 0 0 190 10 0 1019 0 0 1019
7 8:45 London Brussels 578 115 9,852 12 20% 115 85.6695652174 0 0 0 115 0 0 0 0 0 0
7 18:50 Brussels London 1386 180 20,695 17 234 114.9722222222 13 0 0 190 10 0 1150 0 0 1150
7 21:05 Brussels London 926 170 17,910 3 18% 170 105.3529411765 0 0 0 170 0 0 0 0 0 0
8 7:00 London Paris 1484 180 21,718 4 250 120.6555555556 68 6 0 190 10 6 1207 780 0 427
8 10:15 London Paris 876 128 13,662 16 15% 128 106.734375 0 0 0 128 0 0 0 0 0 0
8 19:30 Paris London 1672 180 18,608 21 282 103.3777777778 82 0 0 190 10 0 1034 0 0 1034
8 22:00 Paris London 742 180 16,280 27 125 90.4444444444 0 0 0 125 0 0 0 0 0 0
8 6:50 London Madrid 1875 180 19,731 19 316 109.6166666667 46 0 0 190 10 0 1096 0 0 1096
8 9:30 London Madrid 1344 146 11,049 12 11% 146 75.6780821918 0 0 0 146 0 0 0 0 0 0
8 19:00 Madrid London 1405 180 19,268 4 237 107.0444444444 48 6 0 190 10 6 1070 780 0 290
8 21:30 Madrid London 874 140 14,898 8 16% 140 106.4142857143 0 0 0 140 0 0 0 0 0 0
8 7:10 London Berlin 1196 180 22,352 20 202 124.1777777778 20 0 0 190 10 0 1242 0 0 1242
8 9:15 London Berlin 936 166 16,998 6 18% 166 102.3975903614 0 0 0 166 0 0 0 0 0 0
8 18:30 Berlin London 1306 180 18,108 15 220 100.6 48 0 0 190 10 0 1006 0 0 1006
8 20:30 Berlin London 978 151 13,729 19 15% 151 90.9205298013 0 0 0 151 0 0 0 0 0 0
8 6:30 London Brussels 1755 180 26,964 17 296 149.8 83 0 0 190 10 0 1498 0 0 1498
8 8:45 London Brussels 585 122 9,600 25 21% 122 78.6885245902 0 0 0 122 0 0 0 0 0 0
8 18:50 Brussels London 1412 180 27,241 5 238 151.3388888889 21 5 0 190 10 5 1513 650 0 863
8 21:05 Brussels London 932 173 13,270 14 19% 173 76.7052023121 0 0 0 173 0 0 0 0 0 0
9 7:00 London Paris 1899 180 19,731 14 320 109.6166666667 19 0 0 190 10 0 1096 0 0 1096
9 10:15 London Paris 1086 171 20,857 10 16% 171 121.9707602339 0 0 0 171 0 0 0 0 0 0
9 19:30 Paris London 874 180 23,703 15 147 131.6833333333 38 0 0 147 0 0 0 0 0 0
9 22:00 Paris London 921 149 12,239 7 16% 149 82.1409395973 0 0 0 149 0 0 0 0 0 0
9 6:50 London Madrid 1193 180 21,893 20 201 121.6277777778 4 0 0 190 10 0 1216 0 0 1216
9 9:30 London Madrid 1474 180 18,052 14 248 100.2888888889 0 0 0 190 10 0 1003 0 0 1003
9 19:00 Madrid London 1348 180 20,777 12 227 115.4277777778 61 0 0 190 10 0 1154 0 0 1154
9 21:30 Madrid London 980 126 11,794 7 13% 126 93.6031746032 0 0 0 126 0 0 0 0 0 0
9 7:10 London Berlin 1757 180 19,403 8 296 107.7944444444 57 2 0 190 10 2 1078 260 0 818
9 9:15 London Berlin 885 180 20,190 26 149 112.1666666667 0 0 0 149 0 0 0 0 0 0
9 18:30 Berlin London 1608 180 25,659 9 271 142.55 48 1 0 190 10 1 1426 130 0 1296
9 20:30 Berlin London 838 180 19,206 9 141 106.7 0 0 0 141 0 0 0 0 0 0
9 6:30 London Brussels 1109 165 14,622 7 15% 165 88.6181818182 91 0 0 165 0 0 0 0 0 0
9 8:45 London Brussels 637 109 10,064 20 17% 109 92.3302752294 0 0 0 109 0 0 0 0 0 0
9 18:50 Brussels London 2086 180 25,348 4 352 140.8222222222 30 6 0 190 10 6 1408 780 0 628
9 21:05 Brussels London 1173 160 12,072 10 14% 160 75.45 0 0 0 160 0 0 0 0 0 0
10 7:00 London Paris 1810 180 26,182 8 305 145.4555555556 16 2 0 190 10 2 1455 260 0 1195
10 10:15 London Paris 1058 180 19,187 14 178 106.5944444444 0 0 0 178 0 0 0 0 0 0
10 19:30 Paris London 1438 180 23,617 19 242 131.2055555556 31 0 0 190 10 0 1312 0 0 1312
10 22:00 Paris London 783 163 15,165 14 21% 163 93.036809816 0 0 0 163 0 0 0 0 0 0
10 6:50 London Madrid 2395 180 20,571 10 404 114.2833333333 43 0 0 190 10 0 1143 0 0 1143
10 9:30 London Madrid 642 149 14,661 12 23% 149 98.3959731544 0 0 0 149 0 0 0 0 0 0
10 19:00 Madrid London 1747 180 19,267 19 294 107.0388888889 46 0 0 190 10 0 1070 0 0 1070
10 21:30 Madrid London 1068 146 12,644 12 14% 146 86.602739726 0 0 0 146 0 0 0 0 0 0
10 7:10 London Berlin 1140 180 21,177 9 192 117.65 52 1 0 190 10 1 1177 130 0 1047
10 9:15 London Berlin 1229 134 12,630 6 11% 134 94.2537313433 0 0 0 134 0 0 0 0 0 0
10 18:30 Berlin London 1222 180 15,792 22 206 87.7333333333 47 0 0 190 10 0 877 0 0 877
10 20:30 Berlin London 791 159 13,486 26 20% 159 84.8176100629 0 0 0 159 0 0 0 0 0 0
10 6:30 London Brussels 1266 180 21,427 25 213 119.0388888889 66 0 0 190 10 0 1190 0 0 1190
10 8:45 London Brussels 785 131 13,670 17 17% 131 104.3511450382 0 0 0 131 0 0 0 0 0 0
10 18:50 Brussels London 1594 180 27,214 17 269 151.1888888889 8 0 0 190 10 0 1512 0 0 1512
10 21:05 Brussels London 884 176 12,697 4 20% 176 72.1420454545 0 0 0 176 0 0 0 0 0 0
11 7:00 London Paris 1475 180 26,283 29 249 146.0166666667 46 0 0 190 10 0 1460 0 0 1460
11 10:15 London Paris 982 156 13,783 22 16% 156 88.3525641026 0 0 0 156 0 0 0 0 0 0
11 19:30 Paris London 1575 180 24,816 18 265 137.8666666667 17 0 0 190 10 0 1379 0 0 1379
11 22:00 Paris London 1109 180 16,395 24 187 91.0833333333 0 0 0 187 7 0 629 0 0 629
11 6:50 London Madrid 1852 180 23,933 18 312 132.9611111111 2 0 0 190 10 0 1330 0 0 1330
11 9:30 London Madrid 1324 180 22,065 12 223 122.5833333333 0 0 0 190 10 0 1226 0 0 1226
11 19:00 Madrid London 1493 180 20,439 3 252 113.55 23 7 0 190 10 7 1136 910 0 226
11 21:30 Madrid London 1056 180 14,274 21 178 79.3 0 0 0 178 0 0 0 0 0 0
11 7:10 London Berlin 1419 180 20,216 19 239 112.3111111111 54 0 0 190 10 0 1123 0 0 1123
11 9:15 London Berlin 909 142 14,908 16 16% 142 104.985915493 0 0 0 142 0 0 0 0 0 0
11 18:30 Berlin London 1432 180 21,114 29 241 117.3 23 0 0 190 10 0 1173 0 0 1173
11 20:30 Berlin London 1081 180 23,060 25 182 128.1111111111 0 0 0 182 2 0 281 0 0 281
11 6:30 London Brussels 1045 180 23,831 14 176 132.3944444444 74 0 0 176 0 0 0 0 0 0
11 8:45 London Brussels 827 125 9,113 19 15% 125 72.904 0 0 0 125 0 0 0 0 0 0
11 18:50 Brussels London 1538 180 18,533 14 259 102.9611111111 4 0 0 190 10 0 1030 0 0 1030
11 21:05 Brussels London 1130 180 16,840 14 190 93.5555555556 0 0 0 190 10 0 936 0 0 936
12 7:00 London Paris 1448 180 21,936 12 244 121.8666666667 12 0 0 190 10 0 1219 0 0 1219
12 10:15 London Paris 1057 180 15,987 10 178 88.8166666667 0 0 0 178 0 0 0 0 0 0
12 19:30 Paris London 1520 180 22,150 16 256 123.0555555556 0 0 0 190 10 0 1231 0 0 1231
12 22:00 Paris London 1343 180 18,925 9 226 105.1388888889 0 0 1 190 10 1 1051 0 280 771
12 6:50 London Madrid 1507 180 22,319 17 254 123.9944444444 10 0 0 190 10 0 1240 0 0 1240
12 9:30 London Madrid 1530 180 21,954 20 258 121.9666666667 0 0 0 190 10 0 1220 0 0 1220
12 19:00 Madrid London 2002 180 25,052 15 337 139.1777777778 61 0 0 190 10 0 1392 0 0 1392
12 21:30 Madrid London 807 125 12,827 6 15% 125 102.616 0 0 0 125 0 0 0 0 0 0
12 7:10 London Berlin 1774 180 25,946 26 299 144.1444444444 50 0 0 190 10 0 1441 0 0 1441
12 9:15 London Berlin 858 180 16,385 15 145 91.0277777778 0 0 0 145 0 0 0 0 0 0
12 18:30 Berlin London 1783 180 18,216 27 301 101.2 69 0 0 190 10 0 1012 0 0 1012
12 20:30 Berlin London 802 180 15,187 24 135 84.3722222222 0 0 0 135 0 0 0 0 0 0
12 6:30 London Brussels 1329 180 19,760 5 224 109.7777777778 59 5 0 190 10 5 1098 650 0 448
12 8:45 London Brussels 992 135 11,908 14 14% 135 88.2074074074 0 0 0 135 0 0 0 0 0 0
12 18:50 Brussels London 1261 180 19,751 22 213 109.7277777778 30 0 0 190 10 0 1097 0 0 1097
12 21:05 Brussels London 982 167 12,763 17 17% 167 76.4251497006 0 0 0 167 0 0 0 0 0 0
13 7:00 London Paris 1713 180 24,126 23 289 134.0333333333 38 0 0 190 10 0 1340 0 0 1340
13 10:15 London Paris 778 160 16,064 18 21% 160 100.4 0 0 0 160 0 0 0 0 0 0
13 19:30 Paris London 1730 180 20,154 8 292 111.9666666667 3 2 0 190 10 2 1120 260 0 860
13 22:00 Paris London 1081 180 18,634 5 182 103.5222222222 0 0 0 182 2 0 227 0 0 227
13 6:50 London Madrid 1825 180 22,239 5 308 123.55 22 5 0 190 10 5 1236 650 0 586
13 9:30 London Madrid 1027 164 14,759 6 16% 164 89.993902439 0 0 0 164 0 0 0 0 0 0
13 19:00 Madrid London 1560 180 18,859 12 263 104.7722222222 10 0 0 190 10 0 1048 0 0 1048
13 21:30 Madrid London 955 174 13,062 4 18% 174 75.0689655172 0 0 0 174 0 0 0 0 0 0
13 7:10 London Berlin 1016 180 19,780 16 171 109.8888888889 0 0 0 171 0 0 0 0 0 0
13 9:15 London Berlin 1132 180 22,738 4 191 126.3222222222 0 0 6 190 10 6 1263 0 1680 -417
13 18:30 Berlin London 1495 180 25,525 22 252 141.8055555556 20 0 0 190 10 0 1418 0 0 1418
13 20:30 Berlin London 864 175 12,537 15 20% 175 71.64 0 0 0 175 0 0 0 0 0 0
13 6:30 London Brussels 1372 180 19,963 17 231 110.9055555556 90 0 0 190 10 0 1109 0 0 1109
13 8:45 London Brussels 577 96 9,802 6 17% 96 102.1041666667 0 0 0 96 0 0 0 0 0 0
13 18:50 Brussels London 1838 180 23,773 11 310 132.0722222222 26 0 0 190 10 0 1321 0 0 1321
13 21:05 Brussels London 999 180 18,450 14 168 102.5 0 0 0 168 0 0 0 0 0 0
14 7:00 London Paris 2045 180 22,886 3 345 127.1444444444 23 7 0 190 10 7 1271 910 0 361
14 10:15 London Paris 844 174 15,896 17 21% 174 91.3563218391 0 0 0 174 0 0 0 0 0 0
14 19:30 Paris London 2093 180 21,679 7 353 120.4388888889 65 3 0 190 10 3 1204 390 0 814
14 22:00 Paris London 788 180 19,479 18 133 108.2166666667 0 0 0 133 0 0 0 0 0 0
14 6:50 London Madrid 1215 180 20,029 13 205 111.2722222222 46 0 0 190 10 0 1113 0 0 1113
14 9:30 London Madrid 928 180 23,317 22 156 129.5388888889 0 0 0 156 0 0 0 0 0 0
14 19:00 Madrid London 1375 180 22,794 12 232 126.6333333333 0 0 0 190 10 0 1266 0 0 1266
14 21:30 Madrid London 1191 180 17,746 7 201 98.5888888889 0 0 3 190 10 3 986 0 840 146
14 7:10 London Berlin 1264 180 26,336 21 213 146.3111111111 25 0 0 190 10 0 1463 0 0 1463
14 9:15 London Berlin 992 180 16,366 12 167 90.9222222222 0 0 0 167 0 0 0 0 0 0
14 18:30 Berlin London 1488 180 23,689 22 251 131.6055555556 70 0 0 190 10 0 1316 0 0 1316
14 20:30 Berlin London 857 133 10,134 23 16% 133 76.1954887218 0 0 0 133 0 0 0 0 0 0
14 6:30 London Brussels 1786 180 27,363 29 301 152.0166666667 39 0 0 190 10 0 1520 0 0 1520
14 8:45 London Brussels 762 148 11,099 7 19% 148 74.9932432432 0 0 0 148 0 0 0 0 0 0
14 18:50 Brussels London 1861 180 27,595 11 314 153.3055555556 0 0 0 190 10 0 1533 0 0 1533
14 21:05 Brussels London 1207 180 14,993 5 203 83.2944444444 0 0 5 190 10 5 833 0 1400 -567
15 7:00 London Paris 2036 180 21,653 4 343 120.2944444444 56 6 0 190 10 6 1203 780 0 423
15 10:15 London Paris 967 137 14,188 13 14% 137 103.5620437956 0 0 0 137 0 0 0 0 0 0
15 19:30 Paris London 1828 180 20,665 20 308 114.8055555556 29 0 0 190 10 0 1148 0 0 1148
15 22:00 Paris London 1043 171 17,202 20 16% 171 100.5964912281 0 0 0 171 0 0 0 0 0 0
15 6:50 London Madrid 1446 180 23,492 29 244 130.5111111111 24 0 0 190 10 0 1305 0 0 1305
15 9:30 London Madrid 820 170 15,346 14 21% 170 90.2705882353 0 0 0 170 0 0 0 0 0 0
15 19:00 Madrid London 2320 180 26,444 19 391 146.9111111111 42 0 0 190 10 0 1469 0 0 1469
15 21:30 Madrid London 734 156 15,158 18 21% 156 97.1666666667 0 0 0 156 0 0 0 0 0 0
15 7:10 London Berlin 1738 180 20,115 7 293 111.75 5 3 0 190 10 3 1118 390 0 728
15 9:15 London Berlin 1374 180 17,891 15 232 99.3944444444 0 0 0 190 10 0 994 0 0 994
15 18:30 Berlin London 1136 180 20,034 20 191 111.3 38 0 0 190 10 0 1113 0 0 1113
15 20:30 Berlin London 721 149 12,018 7 21% 149 80.6577181208 0 0 0 149 0 0 0 0 0 0
15 6:30 London Brussels 1004 180 18,248 6 169 101.3777777778 36 0 0 169 0 0 0 0 0 0
15 8:45 London Brussels 1075 154 13,266 10 14% 154 86.1428571429 0 0 0 154 0 0 0 0 0 0
15 18:50 Brussels London 1530 180 20,184 23 258 112.1333333333 43 0 0 190 10 0 1121 0 0 1121
15 21:05 Brussels London 1167 157 13,117 20 13% 157 83.5477707006 0 0 0 157 0 0 0 0 0 0
16 7:00 London Paris 1703 180 24,555 20 287 136.4166666667 44 0 0 190 10 0 1364 0 0 1364
16 10:15 London Paris 973 148 13,665 12 15% 148 92.3310810811 0 0 0 148 0 0 0 0 0 0
16 19:30 Paris London 1130 180 17,192 24 190 95.5111111111 18 0 0 190 10 0 955 0 0 955
16 22:00 Paris London 1255 180 19,259 28 212 106.9944444444 0 0 0 190 10 0 1070 0 0 1070
16 6:50 London Madrid 1407 180 19,518 7 237 108.4333333333 18 3 0 190 10 3 1084 390 0 694
16 9:30 London Madrid 817 169 14,117 7 21% 169 83.5325443787 0 0 0 169 0 0 0 0 0 0
16 19:00 Madrid London 2228 180 21,952 5 376 121.9555555556 23 5 0 190 10 5 1220 650 0 570
16 21:30 Madrid London 745 160 14,108 3 21% 160 88.175 0 0 0 160 0 0 0 0 0 0
16 7:10 London Berlin 1099 171 19,425 13 16% 171 113.5964912281 38 0 0 171 0 0 0 0 0 0
16 9:15 London Berlin 939 160 11,976 18 17% 160 74.85 0 0 0 160 0 0 0 0 0 0
16 18:30 Berlin London 854 180 17,910 7 144 99.5 32 0 0 144 0 0 0 0 0 0
16 20:30 Berlin London 1147 167 17,961 19 15% 167 107.5508982036 0 0 0 167 0 0 0 0 0 0
16 6:30 London Brussels 1342 180 17,927 10 226 99.5944444444 74 0 0 190 10 0 996 0 0 996
16 8:45 London Brussels 1049 131 12,861 25 12% 131 98.1755725191 0 0 0 131 0 0 0 0 0 0
16 18:50 Brussels London 1223 180 20,743 6 206 115.2388888889 29 4 0 190 10 4 1152 520 0 632
16 21:05 Brussels London 942 180 18,339 8 159 101.8833333333 0 0 0 159 0 0 0 0 0 0
17 7:00 London Paris 1574 180 27,225 19 265 151.25 23 0 0 190 10 0 1513 0 0 1513
17 10:15 London Paris 1092 161 17,869 4 15% 161 110.9875776398 0 0 0 161 0 0 0 0 0 0
17 19:30 Paris London 1147 180 18,070 16 193 100.3888888889 55 0 0 190 10 0 1004 0 0 1004
17 22:00 Paris London 1130 145 15,530 20 13% 145 107.1034482759 0 0 0 145 0 0 0 0 0 0
17 6:50 London Madrid 1455 180 19,695 23 245 109.4166666667 15 0 0 190 10 0 1094 0 0 1094
17 9:30 London Madrid 1052 177 23,355 12 17% 177 131.9491525424 0 0 0 177 0 0 0 0 0 0
17 19:00 Madrid London 1433 180 27,833 16 242 154.6277777778 32 0 0 190 10 0 1546 0 0 1546
17 21:30 Madrid London 954 159 13,608 11 17% 159 85.5849056604 0 0 0 159 0 0 0 0 0 0
17 7:10 London Berlin 989 166 18,819 4 17% 166 113.3674698795 8 0 0 166 0 0 0 0 0 0
17 9:15 London Berlin 1165 180 19,818 18 196 110.1 0 0 0 190 10 0 1101 0 0 1101
17 18:30 Berlin London 1200 180 16,599 6 202 92.2166666667 43 4 0 190 10 4 922 520 0 402
17 20:30 Berlin London 840 153 13,687 16 18% 153 89.4575163399 0 0 0 153 0 0 0 0 0 0
17 6:30 London Brussels 1528 180 27,833 16 258 154.6277777778 80 0 0 190 10 0 1546 0 0 1546
17 8:45 London Brussels 625 114 9,214 14 18% 114 80.8245614035 0 0 0 114 0 0 0 0 0 0
17 18:50 Brussels London 1333 180 27,515 14 225 152.8611111111 8 0 0 190 10 0 1529 0 0 1529
17 21:05 Brussels London 1252 180 15,692 18 211 87.1777777778 0 0 0 190 10 0 872 0 0 872
18 7:00 London Paris 2557 180 27,071 9 431 150.3944444444 20 1 0 190 10 1 1504 130 0 1374
18 10:15 London Paris 1072 180 18,816 21 181 104.5333333333 0 0 0 181 1 0 71 0 0 71
18 19:30 Paris London 1331 180 27,667 8 224 153.7055555556 34 2 0 190 10 2 1537 260 0 1277
18 22:00 Paris London 958 180 19,297 15 161 107.2055555556 0 0 0 161 0 0 0 0 0 0
18 6:50 London Madrid 2311 180 25,714 13 389 142.8555555556 79 0 0 190 10 0 1429 0 0 1429
18 9:30 London Madrid 703 180 17,784 17 118 98.8 0 0 0 118 0 0 0 0 0 0
18 19:00 Madrid London 2046 180 19,106 3 345 106.1444444444 31 7 0 190 10 7 1061 910 0 151
18 21:30 Madrid London 819 156 13,351 7 19% 156 85.5833333333 0 0 0 156 0 0 0 0 0 0
18 7:10 London Berlin 931 180 21,647 10 157 120.2611111111 4 0 0 157 0 0 0 0 0 0
18 9:15 London Berlin 1091 180 22,662 8 184 125.9 0 0 0 184 4 0 488 0 0 488
18 18:30 Berlin London 1634 180 23,492 11 275 130.5111111111 53 0 0 190 10 0 1305 0 0 1305
18 20:30 Berlin London 1225 148 10,854 21 12% 148 73.3378378378 0 0 0 148 0 0 0 0 0 0
18 6:30 London Brussels 1468 180 19,923 8 247 110.6833333333 67 2 0 190 10 2 1107 260 0 847
18 8:45 London Brussels 719 134 14,356 21 19% 134 107.1343283582 0 0 0 134 0 0 0 0 0 0
18 18:50 Brussels London 1541 180 25,297 14 260 140.5388888889 8 0 0 190 10 0 1405 0 0 1405
18 21:05 Brussels London 1194 180 12,830 18 201 71.2777777778 0 0 0 190 10 0 713 0 0 713
19 7:00 London Paris 1550 180 21,165 7 261 117.5833333333 3 3 0 190 10 3 1176 390 0 786
19 10:15 London Paris 1168 180 17,838 13 197 99.1 0 0 0 190 10 0 991 0 0 991
19 19:30 Paris London 1468 180 26,365 12 247 146.4722222222 46 0 0 190 10 0 1465 0 0 1465
19 22:00 Paris London 843 147 14,493 13 17% 147 98.5918367347 0 0 0 147 0 0 0 0 0 0
19 6:50 London Madrid 1462 180 23,749 11 246 131.9388888889 15 0 0 190 10 0 1319 0 0 1319
19 9:30 London Madrid 822 175 18,957 10 21% 175 108.3257142857 0 0 0 175 0 0 0 0 0 0
19 19:00 Madrid London 1278 180 22,644 7 215 125.8 14 3 0 190 10 3 1258 390 0 868
19 21:30 Madrid London 808 177 12,826 11 22% 177 72.4632768362 0 0 0 177 0 0 0 0 0 0
19 7:10 London Berlin 1315 169 18,776 12 13% 169 111.100591716 10 0 0 169 0 0 0 0 0 0
19 9:15 London Berlin 1476 180 22,588 20 249 125.4888888889 0 0 0 190 10 0 1255 0 0 1255
19 18:30 Berlin London 1610 171 22,227 6 11% 171 129.9824561404 48 0 0 171 0 0 0 0 0 0
19 20:30 Berlin London 870 180 19,259 15 147 106.9944444444 0 0 0 147 0 0 0 0 0 0
19 6:30 London Brussels 1633 180 16,252 6 275 90.2888888889 52 4 0 190 10 4 903 520 0 383
19 8:45 London Brussels 719 145 14,384 17 20% 145 99.2 0 0 0 145 0 0 0 0 0 0
19 18:50 Brussels London 1398 180 22,863 10 236 127.0166666667 46 0 0 190 10 0 1270 0 0 1270
19 21:05 Brussels London 945 157 16,757 23 17% 157 106.7324840764 0 0 0 157 0 0 0 0 0 0
20 7:00 London Paris 1586 180 25,188 3 267 139.9333333333 79 7 0 190 10 7 1399 910 0 489
20 10:15 London Paris 914 130 12,501 29 14% 130 96.1615384615 0 0 0 130 0 0 0 0 0 0
20 19:30 Paris London 1758 180 21,080 22 296 117.1111111111 24 0 0 190 10 0 1171 0 0 1171
20 22:00 Paris London 870 167 17,435 11 19% 167 104.4011976048 0 0 0 167 0 0 0 0 0 0
20 6:50 London Madrid 1171 180 18,739 16 197 104.1055555556 7 0 0 190 10 0 1041 0 0 1041
20 9:30 London Madrid 1092 180 22,527 11 184 125.15 0 0 0 184 4 0 506 0 0 506
20 19:00 Madrid London 1235 180 27,018 16 208 150.1 5 0 0 190 10 0 1501 0 0 1501
20 21:30 Madrid London 1142 180 17,817 15 192 98.9833333333 0 0 0 190 10 0 990 0 0 990
20 7:10 London Berlin 1054 180 20,312 21 178 112.8444444444 1 0 0 178 0 0 0 0 0 0
20 9:15 London Berlin 1158 180 13,908 11 195 77.2666666667 0 0 0 190 10 0 773 0 0 773
20 18:30 Berlin London 1187 168 18,498 17 14% 168 110.1071428571 24 0 0 168 0 0 0 0 0 0
20 20:30 Berlin London 1033 180 20,353 18 174 113.0722222222 0 0 0 174 0 0 0 0 0 0
20 6:30 London Brussels 1286 180 19,187 3 217 106.5944444444 78 7 0 190 10 7 1066 910 0 156
20 8:45 London Brussels 931 111 8,955 9 12% 111 80.6756756757 0 0 0 111 0 0 0 0 0 0
20 18:50 Brussels London 1670 180 24,619 4 281 136.7722222222 30 6 0 190 10 6 1368 780 0 588
20 21:05 Brussels London 1039 180 16,959 25 175 94.2166666667 0 0 0 175 0 0 0 0 0 0
21 7:00 London Paris 2027 180 19,150 13 342 106.3888888889 4 0 0 190 10 0 1064 0 0 1064
21 10:15 London Paris 1369 180 21,671 14 231 120.3944444444 0 0 0 190 10 0 1204 0 0 1204
21 19:30 Paris London 1433 180 20,164 26 242 112.0222222222 50 0 0 190 10 0 1120 0 0 1120
21 22:00 Paris London 767 152 16,062 22 20% 152 105.6710526316 0 0 0 152 0 0 0 0 0 0
21 6:50 London Madrid 1967 180 22,230 4 332 123.5 26 6 0 190 10 6 1235 780 0 455
21 9:30 London Madrid 1221 165 20,836 11 14% 165 126.2787878788 0 0 0 165 0 0 0 0 0 0
21 19:00 Madrid London 1942 180 21,610 14 327 120.0555555556 23 0 0 190 10 0 1201 0 0 1201
21 21:30 Madrid London 1019 180 17,782 15 172 98.7888888889 0 0 0 172 0 0 0 0 0 0
21 7:10 London Berlin 1139 180 24,030 22 192 133.5 4 0 0 190 10 0 1335 0 0 1335
21 9:15 London Berlin 1335 180 18,622 14 225 103.4555555556 0 0 0 190 10 0 1035 0 0 1035
21 18:30 Berlin London 1319 180 19,938 23 222 110.7666666667 46 0 0 190 10 0 1108 0 0 1108
21 20:30 Berlin London 823 145 12,428 11 18% 145 85.7103448276 0 0 0 145 0 0 0 0 0 0
21 6:30 London Brussels 1514 180 21,144 6 255 117.4666666667 50 4 0 190 10 4 1175 520 0 655
21 8:45 London Brussels 510 134 12,726 4 26% 134 94.9701492537 0 0 0 134 0 0 0 0 0 0
21 18:50 Brussels London 1278 180 24,531 6 215 136.2833333333 0 0 4 190 10 4 1363 0 1120 243
21 21:05 Brussels London 1352 180 14,150 8 228 78.6111111111 0 0 2 190 10 2 786 0 560 226
22 7:00 London Paris 2387 180 19,558 8 402 108.6555555556 65 2 0 190 10 2 1087 260 0 827
22 10:15 London Paris 821 180 17,605 23 138 97.8055555556 0 0 0 138 0 0 0 0 0 0
22 19:30 Paris London 1452 180 26,442 13 245 146.9 39 0 0 190 10 0 1469 0 0 1469
22 22:00 Paris London 878 153 13,285 12 17% 153 86.8300653595 0 0 0 153 0 0 0 0 0 0
22 6:50 London Madrid 1634 180 21,776 10 275 120.9777777778 50 0 0 190 10 0 1210 0 0 1210
22 9:30 London Madrid 954 148 10,720 18 16% 148 72.4324324324 0 0 0 148 0 0 0 0 0 0
22 19:00 Madrid London 1803 180 20,976 18 304 116.5333333333 32 0 0 190 10 0 1165 0 0 1165
22 21:30 Madrid London 918 166 16,415 18 18% 166 98.8855421687 0 0 0 166 0 0 0 0 0 0
22 7:10 London Berlin 835 170 16,662 7 20% 170 98.0117647059 31 0 0 170 0 0 0 0 0 0
22 9:15 London Berlin 908 164 15,708 15 18% 164 95.7804878049 0 0 0 164 0 0 0 0 0 0
22 18:30 Berlin London 1815 180 21,849 20 306 121.3833333333 26 0 0 190 10 0 1214 0 0 1214
22 20:30 Berlin London 802 164 15,973 10 20% 164 97.3963414634 0 0 0 164 0 0 0 0 0 0
22 6:30 London Brussels 1584 180 22,030 27 267 122.3888888889 88 0 0 190 10 0 1224 0 0 1224
22 8:45 London Brussels 689 113 9,604 21 16% 113 84.9911504425 0 0 0 113 0 0 0 0 0 0
22 18:50 Brussels London 1506 180 26,809 26 254 148.9388888889 63 0 0 190 10 0 1489 0 0 1489
22 21:05 Brussels London 641 136 11,216 19 21% 136 82.4705882353 0 0 0 136 0 0 0 0 0 0
23 7:00 London Paris 1370 180 23,306 19 231 129.4777777778 0 0 0 190 10 0 1295 0 0 1295
23 10:15 London Paris 1300 180 16,699 9 219 92.7722222222 0 0 1 190 10 1 928 0 280 648
23 19:30 Paris London 1846 180 24,312 13 311 135.0666666667 71 0 0 190 10 0 1351 0 0 1351
23 22:00 Paris London 739 180 16,764 16 125 93.1333333333 0 0 0 125 0 0 0 0 0 0
23 6:50 London Madrid 1781 180 27,179 16 300 150.9944444444 5 0 0 190 10 0 1510 0 0 1510
23 9:30 London Madrid 1167 180 20,852 15 197 115.8444444444 0 0 0 190 10 0 1158 0 0 1158
23 19:00 Madrid London 1666 180 20,798 13 281 115.5444444444 54 0 0 190 10 0 1155 0 0 1155
23 21:30 Madrid London 1025 137 13,631 11 13% 137 99.496350365 0 0 0 137 0 0 0 0 0 0
23 7:10 London Berlin 837 180 23,247 21 141 129.15 41 0 0 141 0 0 0 0 0 0
23 9:15 London Berlin 797 156 13,351 17 20% 156 85.5833333333 0 0 0 156 0 0 0 0 0 0
23 18:30 Berlin London 1041 180 22,186 25 175 123.2555555556 7 0 0 175 0 0 0 0 0 0
23 20:30 Berlin London 1052 180 16,187 4 177 89.9277777778 0 0 0 177 0 0 0 0 0 0
23 6:30 London Brussels 1532 180 23,892 12 258 132.7333333333 88 0 0 190 10 0 1327 0 0 1327
23 8:45 London Brussels 879 116 9,566 24 13% 116 82.4655172414 0 0 0 116 0 0 0 0 0 0
23 18:50 Brussels London 2138 180 23,330 17 360 129.6111111111 41 0 0 190 10 0 1296 0 0 1296
23 21:05 Brussels London 813 154 14,495 15 19% 154 94.1233766234 0 0 0 154 0 0 0 0 0 0
24 7:00 London Paris 1615 180 18,897 11 272 104.9833333333 47 0 0 190 10 0 1050 0 0 1050
24 10:15 London Paris 880 151 16,068 18 17% 151 106.4105960265 0 0 0 151 0 0 0 0 0 0
24 19:30 Paris London 1403 180 18,878 13 236 104.8777777778 42 0 0 190 10 0 1049 0 0 1049
24 22:00 Paris London 1188 148 15,038 10 12% 148 101.6081081081 0 0 0 148 0 0 0 0 0 0
24 6:50 London Madrid 1430 180 22,554 21 241 125.3 9 0 0 190 10 0 1253 0 0 1253
24 9:30 London Madrid 1127 180 17,105 19 190 95.0277777778 0 0 0 190 10 0 945 0 0 945
24 19:00 Madrid London 2261 180 26,283 24 381 146.0166666667 19 0 0 190 10 0 1460 0 0 1460
24 21:30 Madrid London 1013 180 12,960 10 171 72 0 0 0 171 0 0 0 0 0 0
24 7:10 London Berlin 1238 180 16,366 4 209 90.9222222222 55 6 0 190 10 6 909 780 0 129
24 9:15 London Berlin 868 180 18,829 21 146 104.6055555556 0 0 0 146 0 0 0 0 0 0
24 18:30 Berlin London 1237 180 17,552 20 208 97.5111111111 16 0 0 190 10 0 975 0 0 975
24 20:30 Berlin London 1051 172 19,507 8 16% 172 113.4127906977 0 0 0 172 0 0 0 0 0 0
24 6:30 London Brussels 1686 180 20,777 3 284 115.4277777778 29 7 0 190 10 7 1154 910 0 244
24 8:45 London Brussels 768 161 12,493 10 21% 161 77.5962732919 0 0 0 161 0 0 0 0 0 0
24 18:50 Brussels London 2032 180 27,460 8 342 152.5555555556 40 2 0 190 10 2 1526 260 0 1266
24 21:05 Brussels London 1335 155 16,445 15 12% 155 106.0967741935 0 0 0 155 0 0 0 0 0 0
25 7:00 London Paris 1700 180 20,154 20 287 111.9666666667 67 0 0 190 10 0 1120 0 0 1120
25 10:15 London Paris 701 180 22,617 5 118 125.65 0 0 0 118 0 0 0 0 0 0
25 19:30 Paris London 1180 180 23,060 8 199 128.1111111111 25 2 0 190 10 2 1281 260 0 1021
25 22:00 Paris London 1006 180 17,873 15 170 99.2944444444 0 0 0 170 0 0 0 0 0 0
25 6:50 London Madrid 1725 180 27,799 15 291 154.4388888889 10 0 0 190 10 0 1544 0 0 1544
25 9:30 London Madrid 1109 180 23,130 17 187 128.5 0 0 0 187 7 0 888 0 0 888
25 19:00 Madrid London 1699 180 19,963 27 286 110.9055555556 56 0 0 190 10 0 1109 0 0 1109
25 21:30 Madrid London 860 127 13,534 3 15% 127 106.5669291339 0 0 0 127 0 0 0 0 0 0
25 7:10 London Berlin 975 180 22,595 21 164 125.5277777778 33 0 0 164 0 0 0 0 0 0
25 9:15 London Berlin 898 180 19,700 4 151 109.4444444444 0 0 0 151 0 0 0 0 0 0
25 18:30 Berlin London 1262 180 16,931 15 213 94.0611111111 35 0 0 190 10 0 941 0 0 941
25 20:30 Berlin London 982 163 16,086 18 17% 163 98.6871165644 0 0 0 163 0 0 0 0 0 0
25 6:30 London Brussels 1194 180 18,216 22 201 101.2 84 0 0 190 10 0 1012 0 0 1012
25 8:45 London Brussels 943 102 9,281 6 11% 102 90.9901960784 0 0 0 102 0 0 0 0 0 0
25 18:50 Brussels London 1525 180 18,832 5 257 104.6222222222 16 5 0 190 10 5 1046 650 0 396
25 21:05 Brussels London 1407 180 19,278 26 237 107.1 0 0 0 190 10 0 1071 0 0 1071
26 7:00 London Paris 1568 180 24,271 4 264 134.8388888889 12 6 0 190 10 6 1348 780 0 568
26 10:15 London Paris 1122 180 21,030 21 189 116.8333333333 0 0 0 189 9 0 1063 0 0 1063
26 19:30 Paris London 1858 180 27,996 13 313 155.5333333333 56 0 0 190 10 0 1555 0 0 1555
26 22:00 Paris London 1109 144 14,602 20 13% 144 101.4027777778 0 0 0 144 0 0 0 0 0 0
26 6:50 London Madrid 1178 180 25,869 12 199 143.7166666667 53 0 0 190 10 0 1437 0 0 1437
26 9:30 London Madrid 836 180 14,313 14 141 79.5166666667 0 0 0 141 0 0 0 0 0 0
26 19:00 Madrid London 1453 180 26,706 11 245 148.3666666667 66 0 0 190 10 0 1484 0 0 1484
26 21:30 Madrid London 789 132 10,778 18 17% 132 81.6515151515 0 0 0 132 0 0 0 0 0 0
26 7:10 London Berlin 1054 180 21,292 14 178 118.2888888889 0 0 0 178 0 0 0 0 0 0
26 9:15 London Berlin 1357 180 19,798 5 229 109.9888888889 0 0 5 190 10 5 1100 0 1400 -300
26 18:30 Berlin London 902 176 20,501 7 20% 176 116.4829545455 14 0 0 176 0 0 0 0 0 0
26 20:30 Berlin London 1036 180 16,450 9 175 91.3888888889 0 0 0 175 0 0 0 0 0 0
26 6:30 London Brussels 1505 180 18,108 19 254 100.6 66 0 0 190 10 0 1006 0 0 1006
26 8:45 London Brussels 585 119 10,796 5 20% 119 90.7226890756 0 0 0 119 0 0 0 0 0 0
26 18:50 Brussels London 1122 180 24,385 23 189 135.4722222222 6 0 0 189 9 0 1233 0 0 1233
26 21:05 Brussels London 1124 180 15,777 15 189 87.65 0 0 0 189 9 0 827 0 0 827
27 7:00 London Paris 1741 180 25,276 14 293 140.4222222222 45 0 0 190 10 0 1404 0 0 1404
27 10:15 London Paris 857 180 18,107 9 144 100.5944444444 0 0 0 144 0 0 0 0 0 0
27 19:30 Paris London 2030 180 23,189 20 342 128.8277777778 41 0 0 190 10 0 1288 0 0 1288
27 22:00 Paris London 868 180 14,399 7 146 79.9944444444 0 0 0 146 0 0 0 0 0 0
27 6:50 London Madrid 1235 180 25,019 12 208 138.9944444444 14 0 0 190 10 0 1390 0 0 1390
27 9:30 London Madrid 1285 180 20,832 24 217 115.7333333333 0 0 0 190 10 0 1157 0 0 1157
27 19:00 Madrid London 2124 180 21,294 21 358 118.3 10 0 0 190 10 0 1183 0 0 1183
27 21:30 Madrid London 854 174 18,830 4 20% 174 108.2183908046 0 0 0 174 0 0 0 0 0 0
27 7:10 London Berlin 1093 168 16,733 10 15% 168 99.6011904762 17 0 0 168 0 0 0 0 0 0
27 9:15 London Berlin 1245 180 15,661 27 210 87.0055555556 0 0 0 190 10 0 870 0 0 870
27 18:30 Berlin London 1234 180 26,703 8 208 148.35 45 2 0 190 10 2 1484 260 0 1224
27 20:30 Berlin London 1446 157 14,623 22 11% 157 93.1401273885 0 0 0 157 0 0 0 0 0 0
27 6:30 London Brussels 1167 180 22,981 10 197 127.6722222222 78 0 0 190 10 0 1277 0 0 1277
27 8:45 London Brussels 503 118 12,046 16 23% 118 102.0847457627 0 0 0 118 0 0 0 0 0 0
27 18:50 Brussels London 1615 180 22,516 15 272 125.0888888889 21 0 0 190 10 0 1251 0 0 1251
27 21:05 Brussels London 996 180 14,136 9 168 78.5333333333 0 0 0 168 0 0 0 0 0 0
28 7:00 London Paris 1371 180 25,946 20 231 144.1444444444 42 0 0 190 10 0 1441 0 0 1441
28 10:15 London Paris 854 157 15,023 19 18% 157 95.6878980892 0 0 0 157 0 0 0 0 0 0
28 19:30 Paris London 1550 180 26,991 5 261 149.95 23 5 0 190 10 5 1500 650 0 850
28 22:00 Paris London 887 169 17,359 12 19% 169 102.7159763314 0 0 0 169 0 0 0 0 0 0
28 6:50 London Madrid 1236 180 21,358 14 208 118.6555555556 12 0 0 190 10 0 1187 0 0 1187
28 9:30 London Madrid 736 178 17,781 10 24% 178 99.893258427 0 0 0 178 0 0 0 0 0 0
28 19:00 Madrid London 1797 180 24,239 9 303 134.6611111111 31 1 0 190 10 1 1347 130 0 1217
28 21:30 Madrid London 928 164 15,085 15 18% 164 91.9817073171 0 0 0 164 0 0 0 0 0 0
28 7:10 London Berlin 1374 180 19,539 19 232 108.55 30 0 0 190 10 0 1086 0 0 1086
28 9:15 London Berlin 1103 174 16,706 24 16% 174 96.0114942529 0 0 0 174 0 0 0 0 0 0
28 18:30 Berlin London 1419 180 24,630 21 239 136.8333333333 48 0 0 190 10 0 1368 0 0 1368
28 20:30 Berlin London 826 180 22,265 7 139 123.6944444444 0 0 0 139 0 0 0 0 0 0
28 6:30 London Brussels 1465 180 23,120 21 247 128.4444444444 56 0 0 190 10 0 1284 0 0 1284
28 8:45 London Brussels 796 141 10,341 17 18% 141 73.3404255319 0 0 0 141 0 0 0 0 0 0
28 18:50 Brussels London 1517 180 23,823 24 256 132.35 43 0 0 190 10 0 1324 0 0 1324
28 21:05 Brussels London 1066 156 11,630 19 15% 156 74.5512820513 0 0 0 156 0 0 0 0 0 0
29 7:00 London Paris 1707 180 22,329 18 288 124.05 51 0 0 190 10 0 1241 0 0 1241
29 10:15 London Paris 877 138 14,335 9 16% 138 103.8768115942 0 0 0 138 0 0 0 0 0 0
29 19:30 Paris London 1259 180 18,052 11 212 100.2888888889 43 0 0 190 10 0 1003 0 0 1003
29 22:00 Paris London 1021 160 11,462 23 16% 160 71.6375 0 0 0 160 0 0 0 0 0 0
29 6:50 London Madrid 1449 180 18,840 14 244 104.6666666667 7 0 0 190 10 0 1047 0 0 1047
29 9:30 London Madrid 904 175 18,239 2 19% 175 104.2228571429 0 0 0 175 0 0 0 0 0 0
29 19:00 Madrid London 1182 180 23,681 6 199 131.5611111111 32 4 0 190 10 4 1316 520 0 796
29 21:30 Madrid London 970 180 18,811 15 163 104.5055555556 0 0 0 163 0 0 0 0 0 0
29 7:10 London Berlin 1095 180 18,754 18 185 104.1888888889 11 0 0 185 5 0 474 0 0 474
29 9:15 London Berlin 1061 180 17,295 10 179 96.0833333333 0 0 0 179 0 0 0 0 0 0
29 18:30 Berlin London 1051 180 25,171 20 177 139.8388888889 57 0 0 177 0 0 0 0 0 0
29 20:30 Berlin London 855 133 12,255 10 16% 133 92.1428571429 0 0 0 133 0 0 0 0 0 0
29 6:30 London Brussels 1298 180 21,976 10 219 122.0888888889 41 0 0 190 10 0 1221 0 0 1221
29 8:45 London Brussels 820 150 15,953 11 18% 150 106.3533333333 0 0 0 150 0 0 0 0 0 0
29 18:50 Brussels London 1799 180 24,555 26 303 136.4166666667 29 0 0 190 10 0 1364 0 0 1364
29 21:05 Brussels London 810 170 17,151 19 21% 170 100.8882352941 0 0 0 170 0 0 0 0 0 0
30 7:00 London Paris 1819 180 22,494 27 307 124.9666666667 22 0 0 190 10 0 1250 0 0 1250
30 10:15 London Paris 1084 180 20,095 25 183 111.6388888889 0 0 0 183 3 0 301 0 0 301
30 19:30 Paris London 1224 180 17,302 23 206 96.1222222222 5 0 0 190 10 0 961 0 0 961
30 22:00 Paris London 1354 178 14,943 3 13% 178 83.9494382022 0 0 0 178 0 0 0 0 0 0
30 6:50 London Madrid 1367 180 25,353 28 230 140.85 12 0 0 190 10 0 1409 0 0 1409
30 9:30 London Madrid 1369 180 17,598 22 231 97.7666666667 0 0 0 190 10 0 978 0 0 978
30 19:00 Madrid London 2104 180 18,795 8 355 104.4166666667 55 2 0 190 10 2 1044 260 0 784
30 21:30 Madrid London 1193 141 12,475 16 12% 141 88.475177305 0 0 0 141 0 0 0 0 0 0
30 7:10 London Berlin 1500 180 27,679 15 253 153.7722222222 0 0 0 190 10 0 1538 0 0 1538
30 9:15 London Berlin 1273 180 17,999 7 215 99.9944444444 0 0 3 190 10 3 1000 0 840 160
30 18:30 Berlin London 1282 180 20,251 7 216 112.5055555556 6 3 0 190 10 3 1125 390 0 735
30 20:30 Berlin London 977 179 19,532 5 18% 179 109.1173184358 0 0 0 179 0 0 0 0 0 0
30 6:30 London Brussels 1397 180 23,587 26 235 131.0388888889 69 0 0 190 10 0 1310 0 0 1310
30 8:45 London Brussels 498 132 12,753 21 27% 132 96.6136363636 0 0 0 132 0 0 0 0 0 0
30 18:50 Brussels London 2361 180 23,073 10 398 128.1833333333 44 0 0 190 10 0 1282 0 0 1282
30 21:05 Brussels London 1051 145 12,557 9 14% 145 86.6 0 0 0 145 0 0 0 0 0 0
31 7:00 London Paris 1748 180 25,404 12 295 141.1333333333 43 0 0 190 10 0 1411 0 0 1411
31 10:15 London Paris 1000 152 15,858 15 15% 152 104.3289473684 0 0 0 152 0 0 0 0 0 0
31 19:30 Paris London 1347 180 17,226 14 227 95.7 8 0 0 190 10 0 957 0 0 957
31 22:00 Paris London 1064 180 18,416 7 179 102.3111111111 0 0 0 179 0 0 0 0 0 0
31 6:50 London Madrid 1209 180 19,636 22 204 109.0888888889 20 0 0 190 10 0 1091 0 0 1091
31 9:30 London Madrid 1107 180 23,546 27 187 130.8111111111 0 0 0 187 7 0 860 0 0 860
31 19:00 Madrid London 1870 180 26,178 25 315 145.4333333333 39 0 0 190 10 0 1454 0 0 1454
31 21:30 Madrid London 733 145 11,081 4 20% 145 76.4206896552 0 0 0 145 0 0 0 0 0 0
31 7:10 London Berlin 1412 180 26,680 4 238 148.2222222222 11 6 0 190 10 6 1482 780 0 702
31 9:15 London Berlin 1289 180 21,072 21 217 117.0666666667 0 0 0 190 10 0 1171 0 0 1171
31 18:30 Berlin London 1386 180 17,463 23 234 97.0166666667 25 0 0 190 10 0 970 0 0 970
31 20:30 Berlin London 1054 180 16,006 23 178 88.9222222222 0 0 0 178 0 0 0 0 0 0
31 6:30 London Brussels 1274 180 23,138 5 215 128.5444444444 64 5 0 190 10 5 1285 650 0 635
31 8:45 London Brussels 675 122 11,643 6 18% 122 95.4344262295 0 0 0 122 0 0 0 0 0 0
31 18:50 Brussels London 1761 180 25,113 9 297 139.5166666667 27 1 0 190 10 1 1395 130 0 1265
31 21:05 Brussels London 898 162 14,123 9 18% 162 87.1790123457 0 0 0 162 0 0 0 0 0 0
32 7:00 London Paris 2096 180 21,697 30 353 120.5388888889 17 0 0 190 10 0 1205 0 0 1205
32 10:15 London Paris 918 167 20,732 4 18% 167 124.1437125748 0 0 0 167 0 0 0 0 0 0
32 19:30 Paris London 1598 180 21,018 23 269 116.7666666667 31 0 0 190 10 0 1168 0 0 1168
32 22:00 Paris London 1107 155 16,279 6 14% 155 105.0258064516 0 0 0 155 0 0 0 0 0 0
32 6:50 London Madrid 1872 180 23,115 25 316 128.4166666667 34 0 0 190 10 0 1284 0 0 1284
32 9:30 London Madrid 934 171 13,879 25 18% 171 81.1637426901 0 0 0 171 0 0 0 0 0 0
32 19:00 Madrid London 1681 180 19,383 9 283 107.6833333333 13 1 0 190 10 1 1077 130 0 947
32 21:30 Madrid London 957 178 15,287 11 19% 178 85.8820224719 0 0 0 178 0 0 0 0 0 0
32 7:10 London Berlin 986 180 20,095 18 166 111.6388888889 48 0 0 166 0 0 0 0 0 0
32 9:15 London Berlin 718 147 15,386 15 20% 147 104.6666666667 0 0 0 147 0 0 0 0 0 0
32 18:30 Berlin London 1457 180 23,154 22 246 128.6333333333 31 0 0 190 10 0 1286 0 0 1286
32 20:30 Berlin London 931 180 20,748 8 157 115.2666666667 0 0 0 157 0 0 0 0 0 0
32 6:30 London Brussels 1143 180 23,641 14 193 131.3388888889 73 0 0 190 10 0 1313 0 0 1313
32 8:45 London Brussels 860 123 12,957 16 14% 123 105.3414634146 0 0 0 123 0 0 0 0 0 0
32 18:50 Brussels London 1360 180 21,420 14 229 119 49 0 0 190 10 0 1190 0 0 1190
32 21:05 Brussels London 957 149 11,860 18 16% 149 79.5973154362 0 0 0 149 0 0 0 0 0 0
33 7:00 London Paris 1318 180 23,027 28 222 127.9277777778 61 0 0 190 10 0 1279 0 0 1279
33 10:15 London Paris 941 139 14,872 20 15% 139 106.9928057554 0 0 0 139 0 0 0 0 0 0
33 19:30 Paris London 1648 180 23,470 12 278 130.3888888889 58 0 0 190 10 0 1304 0 0 1304
33 22:00 Paris London 1005 144 14,109 22 14% 144 97.9791666667 0 0 0 144 0 0 0 0 0 0
33 6:50 London Madrid 1638 180 23,494 9 276 130.5222222222 69 1 0 190 10 1 1305 130 0 1175
33 9:30 London Madrid 780 133 10,751 22 17% 133 80.8345864662 0 0 0 133 0 0 0 0 0 0
33 19:00 Madrid London 1334 180 21,271 12 225 118.1722222222 6 0 0 190 10 0 1182 0 0 1182
33 21:30 Madrid London 1055 177 13,590 3 17% 177 76.7796610169 0 0 0 177 0 0 0 0 0 0
33 7:10 London Berlin 1050 180 24,433 14 177 135.7388888889 15 0 0 177 0 0 0 0 0 0
33 9:15 London Berlin 1006 173 20,525 8 17% 173 118.6416184971 0 0 0 173 0 0 0 0 0 0
33 18:30 Berlin London 1312 180 18,829 5 221 104.6055555556 12 5 0 190 10 5 1046 650 0 396
33 20:30 Berlin London 1073 180 17,982 13 181 99.9 0 0 0 181 1 0 84 0 0 84
33 6:30 London Brussels 1169 180 17,692 24 197 98.2888888889 83 0 0 190 10 0 983 0 0 983
33 8:45 London Brussels 859 119 9,349 22 14% 119 78.5630252101 0 0 0 119 0 0 0 0 0 0
33 18:50 Brussels London 1641 180 25,323 20 277 140.6833333333 24 0 0 190 10 0 1407 0 0 1407
33 21:05 Brussels London 998 160 12,701 4 16% 160 79.38125 0 0 0 160 0 0 0 0 0 0
34 7:00 London Paris 1786 180 27,336 3 301 151.8666666667 37 7 0 190 10 7 1519 910 0 609
34 10:15 London Paris 1267 154 14,633 11 12% 154 95.0194805195 0 0 0 154 0 0 0 0 0 0
34 19:30 Paris London 1307 180 21,588 5 220 119.9333333333 17 5 0 190 10 5 1199 650 0 549
34 22:00 Paris London 1020 180 13,729 9 172 76.2722222222 0 0 0 172 0 0 0 0 0 0
34 6:50 London Madrid 2216 180 24,472 15 373 135.9555555556 27 0 0 190 10 0 1360 0 0 1360
34 9:30 London Madrid 1025 170 16,420 17 17% 170 96.5882352941 0 0 0 170 0 0 0 0 0 0
34 19:00 Madrid London 1574 180 27,515 9 265 152.8611111111 46 1 0 190 10 1 1529 130 0 1399
34 21:30 Madrid London 675 159 15,041 25 24% 159 94.5974842767 0 0 0 159 0 0 0 0 0 0
34 7:10 London Berlin 1398 180 22,816 5 236 126.7555555556 42 5 0 190 10 5 1268 650 0 618
34 9:15 London Berlin 1099 158 17,639 20 14% 158 111.6392405063 0 0 0 158 0 0 0 0 0 0
34 18:30 Berlin London 1282 180 21,377 17 216 118.7611111111 20 0 0 190 10 0 1188 0 0 1188
34 20:30 Berlin London 879 176 12,805 16 20% 176 72.7556818182 0 0 0 176 0 0 0 0 0 0
34 6:30 London Brussels 1021 180 18,359 11 172 101.9944444444 68 0 0 172 0 0 0 0 0 0
34 8:45 London Brussels 654 118 11,167 6 18% 118 94.6355932203 0 0 0 118 0 0 0 0 0 0
34 18:50 Brussels London 1875 180 28,041 9 316 155.7833333333 19 1 0 190 10 1 1558 130 0 1428
34 21:05 Brussels London 974 179 18,594 18 18% 179 103.8770949721 0 0 0 179 0 0 0 0 0 0
35 7:00 London Paris 1700 180 20,618 17 287 114.5444444444 46 0 0 190 10 0 1145 0 0 1145
35 10:15 London Paris 891 155 14,257 21 17% 155 91.9806451613 0 0 0 155 0 0 0 0 0 0
35 19:30 Paris London 1790 180 23,024 13 302 127.9111111111 30 0 0 190 10 0 1279 0 0 1279
35 22:00 Paris London 906 180 15,121 3 153 84.0055555556 0 0 0 153 0 0 0 0 0 0
35 6:50 London Madrid 1469 180 24,190 11 248 134.3888888889 27 0 0 190 10 0 1344 0 0 1344
35 9:30 London Madrid 978 180 21,198 12 165 117.7666666667 0 0 0 165 0 0 0 0 0 0
35 19:00 Madrid London 1711 180 19,539 13 288 108.55 33 0 0 190 10 0 1086 0 0 1086
35 21:30 Madrid London 945 180 18,053 12 159 100.2944444444 0 0 0 159 0 0 0 0 0 0
35 7:10 London Berlin 1158 180 21,711 23 195 120.6166666667 0 0 0 190 10 0 1206 0 0 1206
35 9:15 London Berlin 1288 180 18,325 7 217 101.8055555556 0 0 3 190 10 3 1018 0 840 178
35 18:30 Berlin London 1547 180 21,593 4 261 119.9611111111 68 6 0 190 10 6 1200 780 0 420
35 20:30 Berlin London 932 129 12,489 17 14% 129 96.8139534884 0 0 0 129 0 0 0 0 0 0
35 6:30 London Brussels 885 180 20,516 22 149 113.9777777778 93 0 0 149 0 0 0 0 0 0
35 8:45 London Brussels 604 107 7,857 20 18% 107 73.4299065421 0 0 0 107 0 0 0 0 0 0
35 18:50 Brussels London 1710 180 19,774 17 288 109.8555555556 27 0 0 190 10 0 1099 0 0 1099
35 21:05 Brussels London 937 166 12,887 13 18% 166 77.6325301205 0 0 0 166 0 0 0 0 0 0
36 7:00 London Paris 1736 180 25,063 23 293 139.2388888889 33 0 0 190 10 0 1392 0 0 1392
36 10:15 London Paris 905 166 16,105 19 18% 166 97.0180722892 0 0 0 166 0 0 0 0 0 0
36 19:30 Paris London 1170 180 23,236 9 197 129.0888888889 6 1 0 190 10 1 1291 130 0 1161
36 22:00 Paris London 840 177 17,329 3 21% 177 97.9039548023 0 0 0 177 0 0 0 0 0 0
36 6:50 London Madrid 1592 180 21,294 21 268 118.3 25 0 0 190 10 0 1183 0 0 1183
36 9:30 London Madrid 1009 172 17,455 17 17% 172 101.4825581395 0 0 0 172 0 0 0 0 0 0
36 19:00 Madrid London 1999 180 27,171 8 337 150.95 34 2 0 190 10 2 1510 260 0 1250
36 21:30 Madrid London 657 169 14,718 23 26% 169 87.0887573964 0 0 0 169 0 0 0 0 0 0
36 7:10 London Berlin 890 173 16,111 11 19% 173 93.1271676301 10 0 0 173 0 0 0 0 0 0
36 9:15 London Berlin 1030 180 17,398 4 174 96.6555555556 0 0 0 174 0 0 0 0 0 0
36 18:30 Berlin London 1195 180 18,575 6 201 103.1944444444 39 4 0 190 10 4 1032 520 0 512
36 20:30 Berlin London 830 148 14,084 7 18% 148 95.1621621622 0 0 0 148 0 0 0 0 0 0
36 6:30 London Brussels 1112 180 19,998 22 187 111.1 57 0 0 187 7 0 824 0 0 824
36 8:45 London Brussels 799 133 10,795 10 17% 133 81.1654135338 0 0 0 133 0 0 0 0 0 0
36 18:50 Brussels London 1682 180 26,900 20 283 149.4444444444 0 0 0 190 10 0 1494 0 0 1494
36 21:05 Brussels London 1274 180 16,346 4 215 90.8111111111 0 0 6 190 10 6 908 0 1680 -772
37 7:00 London Paris 1740 180 25,474 11 293 141.5222222222 44 0 0 190 10 0 1415 0 0 1415
37 10:15 London Paris 928 180 21,715 20 156 120.6388888889 0 0 0 156 0 0 0 0 0 0
37 19:30 Paris London 1536 180 23,892 16 259 132.7333333333 27 0 0 190 10 0 1327 0 0 1327
37 22:00 Paris London 978 169 12,549 16 17% 169 74.2544378698 0 0 0 169 0 0 0 0 0 0
37 6:50 London Madrid 1066 180 22,516 18 180 125.0888888889 22 0 0 180 0 0 0 0 0 0
37 9:30 London Madrid 872 164 20,346 6 19% 164 124.0609756098 0 0 0 164 0 0 0 0 0 0
37 19:00 Madrid London 1104 180 19,735 5 186 109.6388888889 64 1 0 186 6 1 665 139 0 526
37 21:30 Madrid London 609 138 14,300 22 23% 138 103.6231884058 0 0 0 138 0 0 0 0 0 0
37 7:10 London Berlin 1320 158 15,022 9 12% 158 95.0759493671 73 0 0 158 0 0 0 0 0 0
37 9:15 London Berlin 722 180 20,925 15 122 116.25 0 0 0 122 0 0 0 0 0 0
37 18:30 Berlin London 1170 180 22,471 5 197 124.8388888889 28 5 0 190 10 5 1248 650 0 598
37 20:30 Berlin London 944 180 15,038 7 159 83.5444444444 0 0 0 159 0 0 0 0 0 0
37 6:30 London Brussels 1170 180 27,855 14 197 154.75 59 0 0 190 10 0 1548 0 0 1548
37 8:45 London Brussels 468 136 13,408 15 29% 136 98.5882352941 0 0 0 136 0 0 0 0 0 0
37 18:50 Brussels London 1714 180 19,364 16 289 107.5777777778 0 0 0 190 10 0 1076 0 0 1076
37 21:05 Brussels London 1352 180 16,280 3 228 90.4444444444 0 0 7 190 10 7 904 0 1960 -1056
38 7:00 London Paris 1936 180 24,247 5 326 134.7055555556 6 5 0 190 10 5 1347 650 0 697
38 10:15 London Paris 1138 180 22,374 16 192 124.3 0 0 0 190 10 0 1243 0 0 1243
38 19:30 Paris London 1451 180 23,609 10 245 131.1611111111 14 0 0 190 10 0 1312 0 0 1312
38 22:00 Paris London 1337 180 19,297 24 225 107.2055555556 0 0 0 190 10 0 1072 0 0 1072
38 6:50 London Madrid 920 180 18,954 9 155 105.3 30 0 0 155 0 0 0 0 0 0
38 9:30 London Madrid 1335 172 22,336 22 13% 172 129.8604651163 0 0 0 172 0 0 0 0 0 0
38 19:00 Madrid London 1526 180 20,215 8 257 112.3055555556 18 2 0 190 10 2 1123 260 0 863
38 21:30 Madrid London 1061 180 13,161 17 179 73.1166666667 0 0 0 179 0 0 0 0 0 0
38 7:10 London Berlin 1452 180 16,582 12 245 92.1222222222 14 0 0 190 10 0 921 0 0 921
38 9:15 London Berlin 804 174 16,065 8 22% 174 92.3275862069 0 0 0 174 0 0 0 0 0 0
38 18:30 Berlin London 1232 180 23,130 17 208 128.5 76 0 0 190 10 0 1285 0 0 1285
38 20:30 Berlin London 728 180 14,136 19 123 78.5333333333 0 0 0 123 0 0 0 0 0 0
38 6:30 London Brussels 1244 180 19,346 21 210 107.4777777778 57 0 0 190 10 0 1075 0 0 1075
38 8:45 London Brussels 773 141 12,322 18 18% 141 87.390070922 0 0 0 141 0 0 0 0 0 0
38 18:50 Brussels London 1593 180 24,531 18 268 136.2833333333 46 0 0 190 10 0 1363 0 0 1363
38 21:05 Brussels London 830 180 17,713 6 140 98.4055555556 0 0 0 140 0 0 0 0 0 0
39 7:00 London Paris 1842 180 22,621 17 310 125.6722222222 25 0 0 190 10 0 1257 0 0 1257
39 10:15 London Paris 1023 162 15,757 7 16% 162 97.2654320988 0 0 0 162 0 0 0 0 0 0
39 19:30 Paris London 1392 180 19,676 17 235 109.3111111111 34 0 0 190 10 0 1093 0 0 1093
39 22:00 Paris London 1033 164 12,617 18 16% 164 76.9329268293 0 0 0 164 0 0 0 0 0 0
39 6:50 London Madrid 1570 180 22,363 7 265 124.2388888889 49 3 0 190 10 3 1242 390 0 852
39 9:30 London Madrid 674 134 14,602 3 20% 134 108.9701492537 0 0 0 134 0 0 0 0 0 0
39 19:00 Madrid London 1913 180 20,419 16 322 113.4388888889 16 0 0 190 10 0 1134 0 0 1134
39 21:30 Madrid London 1051 168 12,144 4 16% 168 72.2857142857 0 0 0 168 0 0 0 0 0 0
39 7:10 London Berlin 1392 180 20,790 19 235 115.5 0 0 0 190 10 0 1155 0 0 1155
39 9:15 London Berlin 1255 180 16,482 7 212 91.5666666667 0 0 3 190 10 3 916 0 840 76
39 18:30 Berlin London 1435 180 16,090 24 242 89.3888888889 38 0 0 190 10 0 894 0 0 894
39 20:30 Berlin London 1143 146 13,416 4 13% 146 91.8904109589 0 0 0 146 0 0 0 0 0 0
39 6:30 London Brussels 1775 180 21,507 19 299 119.4833333333 100 0 0 190 10 0 1195 0 0 1195
39 8:45 London Brussels 688 110 8,955 30 16% 110 81.4090909091 0 0 0 110 0 0 0 0 0 0
39 18:50 Brussels London 1534 180 23,861 17 259 132.5611111111 52 0 0 190 10 0 1326 0 0 1326
39 21:05 Brussels London 794 180 16,574 6 134 92.0777777778 0 0 0 134 0 0 0 0 0 0
40 7:00 London Paris 2045 180 28,136 3 345 156.3111111111 37 7 0 190 10 7 1563 910 0 653
40 10:15 London Paris 1061 159 14,754 16 15% 159 92.7924528302 0 0 0 159 0 0 0 0 0 0
40 19:30 Paris London 1581 180 19,602 13 266 108.9 56 0 0 190 10 0 1089 0 0 1089
40 22:00 Paris London 1038 138 13,007 14 13% 138 94.2536231884 0 0 0 138 0 0 0 0 0 0
40 6:50 London Madrid 1087 180 19,810 9 183 110.0555555556 0 0 0 183 3 0 352 0 0 352
40 9:30 London Madrid 1285 180 16,247 4 217 90.2611111111 0 0 6 190 10 6 903 0 1680 -777
40 19:00 Madrid London 2332 180 19,731 27 393 109.6166666667 17 0 0 190 10 0 1096 0 0 1096
40 21:30 Madrid London 1053 174 15,627 11 17% 174 89.8103448276 0 0 0 174 0 0 0 0 0 0
40 7:10 London Berlin 1305 180 18,660 13 220 103.6666666667 28 0 0 190 10 0 1037 0 0 1037
40 9:15 London Berlin 684 171 12,645 19 25% 171 73.9473684211 0 0 0 171 0 0 0 0 0 0
40 18:30 Berlin London 1015 180 16,695 14 171 92.75 0 0 0 171 0 0 0 0 0 0
40 20:30 Berlin London 1097 180 18,380 5 185 102.1111111111 0 0 0 185 5 0 499 0 0 499
40 6:30 London Brussels 1618 180 20,736 21 273 115.2 58 0 0 190 10 0 1152 0 0 1152
40 8:45 London Brussels 929 130 11,734 8 14% 130 90.2615384615 0 0 0 130 0 0 0 0 0 0
40 18:50 Brussels London 1654 180 18,878 27 279 104.8777777778 35 0 0 190 10 0 1049 0 0 1049
40 21:05 Brussels London 940 180 14,285 13 158 79.3611111111 0 0 0 158 0 0 0 0 0 0
41 7:00 London Paris 1491 180 24,223 18 251 134.5722222222 40 0 0 190 10 0 1346 0 0 1346
41 10:15 London Paris 955 145 11,568 5 15% 145 79.7793103448 0 0 0 145 0 0 0 0 0 0
41 19:30 Paris London 1674 180 24,107 7 282 133.9277777778 24 3 0 190 10 3 1339 390 0 949
41 22:00 Paris London 1245 170 12,979 14 14% 170 76.3470588235 0 0 0 170 0 0 0 0 0 0
41 6:50 London Madrid 1770 180 22,599 15 298 125.55 43 0 0 190 10 0 1256 0 0 1256
41 9:30 London Madrid 903 180 16,087 15 152 89.3722222222 0 0 0 152 0 0 0 0 0 0
41 19:00 Madrid London 1614 180 24,263 21 272 134.7944444444 52 0 0 190 10 0 1348 0 0 1348
41 21:30 Madrid London 1355 150 12,247 22 11% 150 81.6466666667 0 0 0 150 0 0 0 0 0 0
41 7:10 London Berlin 1511 180 17,372 21 255 96.5111111111 22 0 0 190 10 0 965 0 0 965
41 9:15 London Berlin 1398 169 17,864 11 12% 169 105.7041420118 0 0 0 169 0 0 0 0 0 0
41 18:30 Berlin London 1269 180 22,531 7 214 125.1722222222 24 3 0 190 10 3 1252 390 0 862
41 20:30 Berlin London 1043 180 21,867 20 176 121.4833333333 0 0 0 176 0 0 0 0 0 0
41 6:30 London Brussels 1535 180 24,767 8 259 137.5944444444 97 2 0 190 10 2 1376 260 0 1116
41 8:45 London Brussels 661 99 9,134 16 15% 99 92.2626262626 0 0 0 99 0 0 0 0 0 0
41 18:50 Brussels London 1912 180 21,871 12 322 121.5055555556 60 0 0 190 10 0 1215 0 0 1215
41 21:05 Brussels London 732 143 12,754 23 20% 143 89.1888111888 0 0 0 143 0 0 0 0 0 0
42 7:00 London Paris 1989 180 27,179 7 335 150.9944444444 20 3 0 190 10 3 1510 390 0 1120
42 10:15 London Paris 1302 173 15,527 13 13% 173 89.7514450867 0 0 0 173 0 0 0 0 0 0
42 19:30 Paris London 1067 180 17,745 6 180 98.5833333333 24 0 0 180 0 0 0 0 0 0
42 22:00 Paris London 1056 180 18,376 22 178 102.0888888889 0 0 0 178 0 0 0 0 0 0
42 6:50 London Madrid 1879 180 26,000 17 317 144.4444444444 71 0 0 190 10 0 1444 0 0 1444
42 9:30 London Madrid 957 136 9,890 27 14% 136 72.7205882353 0 0 0 136 0 0 0 0 0 0
42 19:00 Madrid London 1500 180 22,516 21 253 125.0888888889 14 0 0 190 10 0 1251 0 0 1251
42 21:30 Madrid London 1031 180 13,967 8 174 77.5944444444 0 0 0 174 0 0 0 0 0 0
42 7:10 London Berlin 1369 180 23,808 4 231 132.2666666667 10 6 0 190 10 6 1323 780 0 543
42 9:15 London Berlin 1355 180 14,142 20 228 78.5666666667 0 0 0 190 10 0 786 0 0 786
42 18:30 Berlin London 1306 180 25,946 7 220 144.1444444444 1 1 2 190 10 3 1441 127 566 748
42 20:30 Berlin London 1080 180 23,491 3 182 130.5055555556 0 0 0 182 2 0 264 0 0 264
42 6:30 London Brussels 1446 180 19,760 9 244 109.7777777778 21 1 0 190 10 1 1098 130 0 968
42 8:45 London Brussels 1272 166 14,805 7 13% 166 89.186746988 0 0 0 166 0 0 0 0 0 0
42 18:50 Brussels London 1169 180 25,404 16 197 141.1333333333 32 0 0 190 10 0 1411 0 0 1411
42 21:05 Brussels London 1066 166 14,207 18 16% 166 85.5843373494 0 0 0 166 0 0 0 0 0 0
43 7:00 London Paris 2128 180 24,385 21 359 135.4722222222 50 0 0 190 10 0 1355 0 0 1355
43 10:15 London Paris 876 136 13,546 6 16% 136 99.6029411765 0 0 0 136 0 0 0 0 0 0
43 19:30 Paris London 1498 180 22,886 16 252 127.1444444444 29 0 0 190 10 0 1271 0 0 1271
43 22:00 Paris London 834 156 16,295 5 19% 156 104.4551282051 0 0 0 156 0 0 0 0 0 0
43 6:50 London Madrid 1532 180 21,034 7 258 116.8555555556 8 3 0 190 10 3 1169 390 0 779
43 9:30 London Madrid 1368 180 22,150 18 231 123.0555555556 0 0 0 190 10 0 1231 0 0 1231
43 19:00 Madrid London 1890 180 23,820 23 319 132.3333333333 24 0 0 190 10 0 1323 0 0 1323
43 21:30 Madrid London 943 159 14,695 3 17% 159 92.4213836478 0 0 0 159 0 0 0 0 0 0
43 7:10 London Berlin 1201 180 22,243 18 202 123.5722222222 1 0 0 190 10 0 1236 0 0 1236
43 9:15 London Berlin 1326 180 19,739 11 223 109.6611111111 0 0 0 190 10 0 1097 0 0 1097
43 18:30 Berlin London 1364 180 19,283 16 230 107.1277777778 5 0 0 190 10 0 1071 0 0 1071
43 20:30 Berlin London 1172 180 19,898 15 198 110.5444444444 0 0 0 190 10 0 1105 0 0 1105
43 6:30 London Brussels 1368 180 20,686 15 231 114.9222222222 89 0 0 190 10 0 1149 0 0 1149
43 8:45 London Brussels 638 107 10,678 16 17% 107 99.7943925234 0 0 0 107 0 0 0 0 0 0
43 18:50 Brussels London 1511 180 20,997 13 255 116.65 23 0 0 190 10 0 1167 0 0 1167
43 21:05 Brussels London 899 172 18,669 15 19% 172 108.5406976744 0 0 0 172 0 0 0 0 0 0
44 7:00 London Paris 1830 180 21,657 23 308 120.3166666667 27 0 0 190 10 0 1203 0 0 1203
44 10:15 London Paris 958 160 11,879 7 17% 160 74.24375 0 0 0 160 0 0 0 0 0 0
44 19:30 Paris London 1618 180 22,239 16 273 123.55 5 0 0 190 10 0 1236 0 0 1236
44 22:00 Paris London 1080 180 16,831 7 182 93.5055555556 0 0 0 182 2 0 189 0 0 189
44 6:50 London Madrid 1794 180 27,612 19 302 153.4 30 0 0 190 10 0 1534 0 0 1534
44 9:30 London Madrid 990 180 21,755 17 167 120.8611111111 0 0 0 167 0 0 0 0 0 0
44 19:00 Madrid London 1454 180 21,871 22 245 121.5055555556 57 0 0 190 10 0 1215 0 0 1215
44 21:30 Madrid London 919 144 13,362 21 16% 144 92.7916666667 0 0 0 144 0 0 0 0 0 0
44 7:10 London Berlin 1415 180 17,569 3 238 97.6055555556 25 7 0 190 10 7 976 910 0 66
44 9:15 London Berlin 1032 180 13,784 19 174 76.5777777778 0 0 0 174 0 0 0 0 0 0
44 18:30 Berlin London 1047 178 22,531 23 17% 178 126.5786516854 49 0 0 178 0 0 0 0 0 0
44 20:30 Berlin London 936 180 15,894 27 158 88.3 0 0 0 158 0 0 0 0 0 0
44 6:30 London Brussels 1359 180 21,845 16 229 121.3611111111 40 0 0 190 10 0 1214 0 0 1214
44 8:45 London Brussels 792 159 12,749 19 20% 159 80.1823899371 0 0 0 159 0 0 0 0 0 0
44 18:50 Brussels London 1744 180 24,506 9 294 136.1444444444 44 1 0 190 10 1 1361 130 0 1231
44 21:05 Brussels London 951 160 11,451 24 17% 160 71.56875 0 0 0 160 0 0 0 0 0 0
45 7:00 London Paris 1682 180 21,675 10 283 120.4166666667 75 0 0 190 10 0 1204 0 0 1204
45 10:15 London Paris 785 123 9,606 18 16% 123 78.0975609756 0 0 0 123 0 0 0 0 0 0
45 19:30 Paris London 957 180 18,072 23 161 100.4 25 0 0 161 0 0 0 0 0 0
45 22:00 Paris London 1034 176 15,791 21 17% 176 89.7215909091 0 0 0 176 0 0 0 0 0 0
45 6:50 London Madrid 1465 180 26,442 9 247 146.9 27 1 0 190 10 1 1469 130 0 1339
45 9:30 London Madrid 949 165 13,783 12 17% 165 83.5333333333 0 0 0 165 0 0 0 0 0 0
45 19:00 Madrid London 1419 180 27,623 22 239 153.4611111111 19 0 0 190 10 0 1535 0 0 1535
45 21:30 Madrid London 1067 177 17,718 16 17% 177 100.1016949153 0 0 0 177 0 0 0 0 0 0
45 7:10 London Berlin 1235 180 23,598 4 208 131.1 0 0 6 190 10 6 1311 0 1680 -369
45 9:15 London Berlin 1156 180 20,956 10 195 116.4222222222 0 0 0 190 10 0 1164 0 0 1164
45 18:30 Berlin London 1629 180 24,343 19 275 135.2388888889 59 0 0 190 10 0 1352 0 0 1352
45 20:30 Berlin London 922 149 14,038 28 16% 149 94.2147651007 0 0 0 149 0 0 0 0 0 0
45 6:30 London Brussels 1418 180 15,983 19 239 88.7944444444 47 0 0 190 10 0 888 0 0 888
45 8:45 London Brussels 818 154 11,840 21 19% 154 76.8831168831 0 0 0 154 0 0 0 0 0 0
45 18:50 Brussels London 1675 180 27,762 25 282 154.2333333333 15 0 0 190 10 0 1542 0 0 1542
45 21:05 Brussels London 1195 180 13,784 25 201 76.5777777778 0 0 0 190 10 0 766 0 0 766
46 7:00 London Paris 1785 180 19,676 10 301 109.3111111111 4 0 0 190 10 0 1093 0 0 1093
46 10:15 London Paris 1076 180 22,998 5 181 127.7666666667 0 0 0 181 1 0 172 0 0 172
46 19:30 Paris London 2180 180 25,710 3 367 142.8333333333 27 7 0 190 10 7 1428 910 0 518
46 22:00 Paris London 1134 165 11,951 12 15% 165 72.4303030303 0 0 0 165 0 0 0 0 0 0
46 6:50 London Madrid 1778 180 23,963 18 300 133.1277777778 9 0 0 190 10 0 1331 0 0 1331
46 9:30 London Madrid 1429 180 15,745 19 241 87.4722222222 0 0 0 190 10 0 875 0 0 875
46 19:00 Madrid London 1525 180 20,204 26 257 112.2444444444 58 0 0 190 10 0 1122 0 0 1122
46 21:30 Madrid London 790 180 14,057 11 133 78.0944444444 0 0 0 133 0 0 0 0 0 0
46 7:10 London Berlin 1540 180 24,838 6 260 137.9888888889 67 4 0 190 10 4 1380 520 0 860
46 9:15 London Berlin 979 130 10,077 17 13% 130 77.5153846154 0 0 0 130 0 0 0 0 0 0
46 18:30 Berlin London 1292 180 16,268 14 218 90.3777777778 21 0 0 190 10 0 904 0 0 904
46 20:30 Berlin London 1032 180 15,359 15 174 85.3277777778 0 0 0 174 0 0 0 0 0 0
46 6:30 London Brussels 992 180 17,329 11 167 96.2722222222 17 0 0 167 0 0 0 0 0 0
46 8:45 London Brussels 947 172 12,322 9 18% 172 71.6395348837 0 0 0 172 0 0 0 0 0 0
46 18:50 Brussels London 1467 180 27,623 22 247 153.4611111111 8 0 0 190 10 0 1535 0 0 1535
46 21:05 Brussels London 882 176 14,500 4 20% 176 82.3863636364 0 0 0 176 0 0 0 0 0 0
47 7:00 London Paris 1658 180 19,989 6 279 111.05 14 4 0 190 10 4 1111 520 0 591
47 10:15 London Paris 1513 180 16,166 24 255 89.8111111111 0 0 0 190 10 0 898 0 0 898
47 19:30 Paris London 1699 180 25,534 17 286 141.8555555556 64 0 0 190 10 0 1419 0 0 1419
47 22:00 Paris London 808 137 11,243 21 17% 137 82.0656934307 0 0 0 137 0 0 0 0 0 0
47 6:50 London Madrid 2042 180 22,621 15 344 125.6722222222 29 0 0 190 10 0 1257 0 0 1257
47 9:30 London Madrid 1001 180 17,892 18 169 99.4 0 0 0 169 0 0 0 0 0 0
47 19:00 Madrid London 1660 180 20,236 21 280 112.4222222222 33 0 0 190 10 0 1124 0 0 1124
47 21:30 Madrid London 1170 161 11,678 14 14% 161 72.5341614907 0 0 0 161 0 0 0 0 0 0
47 7:10 London Berlin 1358 180 21,736 13 229 120.7555555556 52 0 0 190 10 0 1208 0 0 1208
47 9:15 London Berlin 736 134 11,462 6 18% 134 85.5373134328 0 0 0 134 0 0 0 0 0 0
47 18:30 Berlin London 1359 180 26,078 27 229 144.8777777778 37 0 0 190 10 0 1449 0 0 1449
47 20:30 Berlin London 881 150 16,202 7 17% 150 108.0133333333 0 0 0 150 0 0 0 0 0 0
47 6:30 London Brussels 1358 180 18,829 10 229 104.6055555556 38 0 0 190 10 0 1046 0 0 1046
47 8:45 London Brussels 794 152 14,848 10 19% 152 97.6842105263 0 0 0 152 0 0 0 0 0 0
47 18:50 Brussels London 2127 180 20,154 19 358 111.9666666667 57 0 0 190 10 0 1120 0 0 1120
47 21:05 Brussels London 812 180 14,742 14 137 81.9 0 0 0 137 0 0 0 0 0 0
48 7:00 London Paris 1556 180 19,092 21 262 106.0666666667 51 0 0 190 10 0 1061 0 0 1061
48 10:15 London Paris 898 180 16,411 22 151 91.1722222222 0 0 0 151 0 0 0 0 0 0
48 19:30 Paris London 1309 180 18,322 15 221 101.7888888889 29 0 0 190 10 0 1018 0 0 1018
48 22:00 Paris London 1010 165 15,403 14 16% 165 93.3515151515 0 0 0 165 0 0 0 0 0 0
48 6:50 London Madrid 1552 180 18,840 20 262 104.6666666667 11 0 0 190 10 0 1047 0 0 1047
48 9:30 London Madrid 1097 180 22,853 16 185 126.9611111111 0 0 0 185 5 0 621 0 0 621
48 19:00 Madrid London 1572 180 28,052 21 265 155.8444444444 49 0 0 190 10 0 1558 0 0 1558
48 21:30 Madrid London 862 180 19,182 14 145 106.5666666667 0 0 0 145 0 0 0 0 0 0
48 7:10 London Berlin 1126 180 16,220 7 190 90.1111111111 0 0 3 190 10 3 881 0 777 104
48 9:15 London Berlin 1262 180 17,980 9 213 99.8888888889 0 0 1 190 10 1 999 0 280 719
48 18:30 Berlin London 1533 180 23,701 19 258 131.6722222222 12 0 0 190 10 0 1317 0 0 1317
48 20:30 Berlin London 1036 180 22,396 7 175 124.4222222222 0 0 0 175 0 0 0 0 0 0
48 6:30 London Brussels 1070 180 23,247 3 180 129.15 86 0 0 180 0 0 44 0 0 44
48 8:45 London Brussels 655 121 10,781 27 18% 121 89.0991735537 0 0 0 121 0 0 0 0 0 0
48 18:50 Brussels London 1587 180 23,494 4 267 130.5222222222 11 6 0 190 10 6 1305 780 0 525
48 21:05 Brussels London 1211 180 17,409 21 204 96.7166666667 0 0 0 190 10 0 967 0 0 967
49 7:00 London Paris 1996 180 20,064 23 336 111.4666666667 0 0 0 190 10 0 1115 0 0 1115
49 10:15 London Paris 1333 180 21,491 9 225 119.3944444444 0 0 1 190 10 1 1194 0 280 914
49 19:30 Paris London 1476 180 19,092 16 249 106.0666666667 68 0 0 190 10 0 1061 0 0 1061
49 22:00 Paris London 778 180 13,191 19 131 73.2833333333 0 0 0 131 0 0 0 0 0 0
49 6:50 London Madrid 1821 180 23,050 10 307 128.0555555556 57 0 0 190 10 0 1281 0 0 1281
49 9:30 London Madrid 813 126 9,204 3 15% 126 73.0476190476 0 0 0 126 0 0 0 0 0 0
49 19:00 Madrid London 1753 180 19,015 17 295 105.6388888889 64 0 0 190 10 0 1056 0 0 1056
49 21:30 Madrid London 1021 132 9,781 16 13% 132 74.0984848485 0 0 0 132 0 0 0 0 0 0
49 7:10 London Berlin 1564 180 15,919 29 264 88.4388888889 0 0 0 190 10 0 884 0 0 884
49 9:15 London Berlin 1250 180 18,875 4 211 104.8611111111 0 0 6 190 10 6 1049 0 1680 -631
49 18:30 Berlin London 1445 180 26,991 19 244 149.95 39 0 0 190 10 0 1500 0 0 1500
49 20:30 Berlin London 1374 149 12,446 8 11% 149 83.5302013423 0 0 0 149 0 0 0 0 0 0
49 6:30 London Brussels 967 180 21,584 11 163 119.9111111111 73 0 0 163 0 0 0 0 0 0
49 8:45 London Brussels 915 129 11,598 22 14% 129 89.9069767442 0 0 0 129 0 0 0 0 0 0
49 18:50 Brussels London 1427 180 18,783 6 241 104.35 42 4 0 190 10 4 1044 520 0 524
49 21:05 Brussels London 948 180 14,667 22 160 81.4833333333 0 0 0 160 0 0 0 0 0 0
50 7:00 London Paris 1794 180 26,389 15 302 146.6055555556 61 0 0 190 10 0 1466 0 0 1466
50 10:15 London Paris 725 180 17,351 3 122 96.3944444444 0 0 0 122 0 0 0 0 0 0
50 19:30 Paris London 1618 180 19,771 4 273 109.8388888889 40 6 0 190 10 6 1098 780 0 318
50 22:00 Paris London 896 180 18,376 11 151 102.0888888889 0 0 0 151 0 0 0 0 0 0
50 6:50 London Madrid 1496 180 21,123 11 252 117.35 0 0 0 190 10 0 1174 0 0 1174
50 9:30 London Madrid 1296 180 21,122 8 218 117.3444444444 0 0 2 190 10 2 1173 0 560 613
50 19:00 Madrid London 1894 180 26,336 20 319 146.3111111111 55 0 0 190 10 0 1463 0 0 1463
50 21:30 Madrid London 1252 143 12,446 18 11% 143 87.034965035 0 0 0 143 0 0 0 0 0 0
50 7:10 London Berlin 1146 180 18,904 24 193 105.0222222222 0 0 0 190 10 0 1050 0 0 1050
50 9:15 London Berlin 1391 180 22,527 7 234 125.15 0 0 3 190 10 3 1252 0 840 412
50 18:30 Berlin London 1012 180 18,267 4 171 101.4833333333 62 0 0 171 0 0 0 0 0 0
50 20:30 Berlin London 749 180 19,355 8 126 107.5277777778 0 0 0 126 0 0 0 0 0 0
50 6:30 London Brussels 1510 180 23,570 4 254 130.9444444444 65 6 0 190 10 6 1309 780 0 529
50 8:45 London Brussels 883 124 10,034 9 14% 124 80.9193548387 0 0 0 124 0 0 0 0 0 0
50 18:50 Brussels London 1513 180 22,062 11 255 122.5666666667 45 0 0 190 10 0 1226 0 0 1226
50 21:05 Brussels London 1111 150 14,047 15 14% 150 93.6466666667 0 0 0 150 0 0 0 0 0 0
51 7:00 London Paris 1535 180 23,143 12 259 128.5722222222 65 0 0 190 10 0 1286 0 0 1286
51 10:15 London Paris 801 180 18,580 20 135 103.2222222222 0 0 0 135 0 0 0 0 0 0
51 19:30 Paris London 1056 180 22,952 19 178 127.5111111111 28 0 0 178 0 0 0 0 0 0
51 22:00 Paris London 962 180 16,524 10 162 91.8 0 0 0 162 0 0 0 0 0 0
51 6:50 London Madrid 1375 180 25,508 20 232 141.7111111111 16 0 0 190 10 0 1417 0 0 1417
51 9:30 London Madrid 1011 180 14,638 6 170 81.3222222222 0 0 0 170 0 0 0 0 0 0
51 19:00 Madrid London 2062 180 27,750 30 348 154.1666666667 9 0 0 190 10 0 1542 0 0 1542
51 21:30 Madrid London 969 177 13,948 6 18% 177 78.802259887 0 0 0 177 0 0 0 0 0 0
51 7:10 London Berlin 1114 180 25,002 8 188 138.9 14 0 0 188 8 0 1077 0 0 1077
51 9:15 London Berlin 1139 180 22,352 24 192 124.1777777778 0 0 0 190 10 0 1242 0 0 1242
51 18:30 Berlin London 1434 180 22,208 5 242 123.3777777778 21 5 0 190 10 5 1234 650 0 584
51 20:30 Berlin London 966 172 14,420 13 18% 172 83.8372093023 0 0 0 172 0 0 0 0 0 0
51 6:30 London Brussels 1464 180 20,955 6 247 116.4166666667 40 4 0 190 10 4 1164 520 0 644
51 8:45 London Brussels 926 148 14,682 8 16% 148 99.2027027027 0 0 0 148 0 0 0 0 0 0
51 18:50 Brussels London 1629 180 22,886 20 275 127.1444444444 29 0 0 190 10 0 1271 0 0 1271
51 21:05 Brussels London 987 159 14,309 8 16% 159 89.9937106918 0 0 0 159 0 0 0 0 0 0
52 7:00 London Paris 1318 180 27,415 4 222 152.3055555556 28 6 0 190 10 6 1523 780 0 743
52 10:15 London Paris 951 180 17,295 8 160 96.0833333333 0 0 0 160 0 0 0 0 0 0
52 19:30 Paris London 1128 180 27,035 20 190 150.1944444444 62 0 0 190 10 0 1502 0 0 1502
52 22:00 Paris London 753 180 15,198 9 127 84.4333333333 0 0 0 127 0 0 0 0 0 0
52 6:50 London Madrid 1645 180 26,156 25 277 145.3111111111 6 0 0 190 10 0 1453 0 0 1453
52 9:30 London Madrid 937 179 13,890 5 19% 179 77.5977653631 0 0 0 179 0 0 0 0 0 0
52 19:00 Madrid London 1583 180 21,718 28 267 120.6555555556 42 0 0 190 10 0 1207 0 0 1207
52 21:30 Madrid London 937 180 15,319 20 158 85.1055555556 0 0 0 158 0 0 0 0 0 0
52 7:10 London Berlin 1082 180 19,543 16 182 108.5722222222 2 0 0 182 2 0 256 0 0 256
52 9:15 London Berlin 1126 180 23,703 12 190 131.6833333333 0 0 0 190 10 0 1287 0 0 1287
52 18:30 Berlin London 1401 180 21,936 6 236 121.8666666667 29 4 0 190 10 4 1219 520 0 699
52 20:30 Berlin London 1015 180 20,967 20 171 116.4833333333 0 0 0 171 0 0 0 0 0 0
52 6:30 London Brussels 1141 180 22,119 4 192 122.8833333333 56 6 0 190 10 6 1229 780 0 449
52 8:45 London Brussels 823 132 13,173 8 16% 132 99.7954545455 0 0 0 132 0 0 0 0 0 0
52 18:50 Brussels London 1585 180 19,538 10 267 108.5444444444 75 0 0 190 10 0 1085 0 0 1085
52 21:05 Brussels London 738 180 15,513 19 124 86.1833333333 0 0 0 124 0 0 0 0 0 0
53 7:00 London Paris 1948 180 26,641 7 328 148.0055555556 15 3 0 190 10 3 1480 390 0 1090
53 10:15 London Paris 1248 180 15,926 25 210 88.4777777778 0 0 0 190 10 0 885 0 0 885
53 19:30 Paris London 1865 180 20,317 23 314 112.8722222222 41 0 0 190 10 0 1129 0 0 1129
53 22:00 Paris London 818 154 13,266 15 19% 154 86.1428571429 0 0 0 154 0 0 0 0 0 0
53 6:50 London Madrid 1258 180 23,097 3 212 128.3166666667 5 5 2 190 10 7 1283 606 655 23
53 9:30 London Madrid 1070 180 16,897 5 180 93.8722222222 0 0 0 180 0 0 32 0 0 32
53 19:00 Madrid London 1503 180 24,336 11 253 135.2 11 0 0 190 10 0 1352 0 0 1352
53 21:30 Madrid London 905 172 14,508 3 19% 172 84.3488372093 0 0 0 172 0 0 0 0 0 0
53 7:10 London Berlin 1360 180 19,247 8 229 106.9277777778 27 2 0 190 10 2 1069 260 0 809
53 9:15 London Berlin 955 180 19,798 8 161 109.9888888889 0 0 0 161 0 0 0 0 0 0
53 18:30 Berlin London 1177 180 18,519 17 198 102.8833333333 37 0 0 190 10 0 1029 0 0 1029
53 20:30 Berlin London 920 180 22,724 12 155 126.2444444444 0 0 0 155 0 0 0 0 0 0
53 6:30 London Brussels 1195 180 23,260 18 201 129.2222222222 67 0 0 190 10 0 1292 0 0 1292
53 8:45 London Brussels 889 139 11,270 26 16% 139 81.0791366906 0 0 0 139 0 0 0 0 0 0
53 18:50 Brussels London 1677 180 22,554 4 283 125.3 20 6 0 190 10 6 1253 780 0 473
53 21:05 Brussels London 926 165 15,890 5 18% 165 96.303030303 0 0 0 165 0 0 0 0 0 0
54 7:00 London Paris 1343 180 22,771 9 226 126.5055555556 33 1 0 190 10 1 1265 130 0 1135
54 10:15 London Paris 929 165 14,405 18 18% 165 87.303030303 0 0 0 165 0 0 0 0 0 0
54 19:30 Paris London 1577 180 24,482 10 266 136.0111111111 17 0 0 190 10 0 1360 0 0 1360
54 22:00 Paris London 983 175 18,734 12 18% 175 107.0514285714 0 0 0 175 0 0 0 0 0 0
54 6:50 London Madrid 1352 180 22,698 5 228 126.1 33 5 0 190 10 5 1261 650 0 611
54 9:30 London Madrid 947 180 21,388 13 160 118.8222222222 0 0 0 160 0 0 0 0 0 0
54 19:00 Madrid London 1418 180 26,543 18 239 147.4611111111 42 0 0 190 10 0 1475 0 0 1475
54 21:30 Madrid London 757 150 15,075 12 20% 150 100.5 0 0 0 150 0 0 0 0 0 0
54 7:10 London Berlin 1216 167 17,812 13 14% 167 106.6586826347 30 0 0 167 0 0 0 0 0 0
54 9:15 London Berlin 878 173 15,925 23 20% 173 92.0520231214 0 0 0 173 0 0 0 0 0 0
54 18:30 Berlin London 1385 180 20,603 27 233 114.4611111111 22 0 0 190 10 0 1145 0 0 1145
54 20:30 Berlin London 1066 164 16,382 6 15% 164 99.8902439024 0 0 0 164 0 0 0 0 0 0
54 6:30 London Brussels 1380 180 25,188 7 233 139.9333333333 78 3 0 190 10 3 1399 390 0 1009
54 8:45 London Brussels 637 130 10,128 28 20% 130 77.9076923077 0 0 0 130 0 0 0 0 0 0
54 18:50 Brussels London 1212 180 26,129 4 204 145.1611111111 27 6 0 190 10 6 1452 780 0 672
54 21:05 Brussels London 1118 162 13,851 9 14% 162 85.5 0 0 0 162 0 0 0 0 0 0
55 7:00 London Paris 2031 180 20,265 25 342 112.5833333333 0 0 0 190 10 0 1126 0 0 1126
55 10:15 London Paris 1135 180 18,469 10 191 102.6055555556 0 0 0 190 10 0 1026 0 0 1026
55 19:30 Paris London 1563 180 24,107 5 263 133.9277777778 28 5 0 190 10 5 1339 650 0 689
55 22:00 Paris London 914 162 16,346 10 18% 162 100.9012345679 0 0 0 162 0 0 0 0 0 0
55 6:50 London Madrid 1305 180 20,521 17 220 114.0055555556 0 0 0 190 10 0 1140 0 0 1140
55 9:30 London Madrid 1116 180 20,557 5 188 114.2055555556 0 0 3 188 8 3 924 0 865 59
55 19:00 Madrid London 1649 180 21,886 17 278 121.5888888889 51 0 0 190 10 0 1216 0 0 1216
55 21:30 Madrid London 887 155 12,655 26 17% 155 81.6451612903 0 0 0 155 0 0 0 0 0 0
55 7:10 London Berlin 1160 168 16,748 4 14% 168 99.6904761905 47 0 0 168 0 0 0 0 0 0
55 9:15 London Berlin 931 180 16,134 24 157 89.6333333333 0 0 0 157 0 0 0 0 0 0
55 18:30 Berlin London 1449 179 20,592 3 12% 179 115.0391061453 17 0 0 179 0 0 0 0 0 0
55 20:30 Berlin London 1055 180 15,051 15 178 83.6166666667 0 0 0 178 0 0 0 0 0 0
55 6:30 London Brussels 1365 180 25,608 10 230 142.2666666667 56 0 0 190 10 0 1423 0 0 1423
55 8:45 London Brussels 889 132 10,284 8 15% 132 77.9090909091 0 0 0 132 0 0 0 0 0 0
55 18:50 Brussels London 1782 180 21,358 24 300 118.6555555556 29 0 0 190 10 0 1187 0 0 1187
55 21:05 Brussels London 1082 156 15,212 5 14% 156 97.5128205128 0 0 0 156 0 0 0 0 0 0
56 7:00 London Paris 2466 180 23,916 10 416 132.8666666667 53 0 0 190 10 0 1329 0 0 1329
56 10:15 London Paris 897 135 11,439 8 15% 135 84.7333333333 0 0 0 135 0 0 0 0 0 0
56 19:30 Paris London 1228 180 19,998 16 207 111.1 0 0 0 190 10 0 1111 0 0 1111
56 22:00 Paris London 1107 180 15,023 4 187 83.4611111111 0 0 3 187 7 3 549 0 721 -172
56 6:50 London Madrid 1537 180 21,486 16 259 119.3666666667 0 0 0 190 10 0 1194 0 0 1194
56 9:30 London Madrid 1245 180 19,360 4 210 107.5555555556 0 0 6 190 10 6 1076 0 1680 -604
56 19:00 Madrid London 1664 180 23,050 13 280 128.0555555556 21 0 0 190 10 0 1281 0 0 1281
56 21:30 Madrid London 1002 176 18,774 17 18% 176 106.6704545455 0 0 0 176 0 0 0 0 0 0
56 7:10 London Berlin 1311 180 22,539 15 221 125.2166666667 43 0 0 190 10 0 1252 0 0 1252
56 9:15 London Berlin 861 180 17,605 8 145 97.8055555556 0 0 0 145 0 0 0 0 0 0
56 18:30 Berlin London 1367 180 19,923 8 230 110.6833333333 16 2 0 190 10 2 1107 260 0 847
56 20:30 Berlin London 843 175 22,093 11 21% 175 126.2457142857 0 0 0 175 0 0 0 0 0 0
56 6:30 London Brussels 1052 180 19,919 7 177 110.6611111111 57 0 0 177 0 0 0 0 0 0
56 8:45 London Brussels 843 129 9,665 6 15% 129 74.9224806202 0 0 0 129 0 0 0 0 0 0
56 18:50 Brussels London 1272 180 25,792 17 214 143.2888888889 45 0 0 190 10 0 1433 0 0 1433
56 21:05 Brussels London 865 148 13,347 13 17% 148 90.1824324324 0 0 0 148 0 0 0 0 0 0
57 7:00 London Paris 2219 180 22,958 16 374 127.5444444444 52 0 0 190 10 0 1275 0 0 1275
57 10:15 London Paris 934 147 14,142 19 16% 147 96.2040816327 0 0 0 147 0 0 0 0 0 0
57 19:30 Paris London 1236 180 19,850 17 208 110.2777777778 15 0 0 190 10 0 1103 0 0 1103
57 22:00 Paris London 1218 175 16,145 10 14% 175 92.2571428571 0 0 0 175 0 0 0 0 0 0
57 6:50 London Madrid 1282 180 19,774 14 216 109.8555555556 18 0 0 190 10 0 1099 0 0 1099
57 9:30 London Madrid 771 170 16,796 8 22% 170 98.8 0 0 0 170 0 0 0 0 0 0
57 19:00 Madrid London 2156 180 21,657 3 363 120.3166666667 27 7 0 190 10 7 1203 910 0 293
57 21:30 Madrid London 695 167 14,515 14 24% 167 86.9161676647 0 0 0 167 0 0 0 0 0 0
57 7:10 London Berlin 941 180 19,484 23 159 108.2444444444 38 0 0 159 0 0 0 0 0 0
57 9:15 London Berlin 948 180 23,130 18 160 128.5 0 0 0 160 0 0 0 0 0 0
57 18:30 Berlin London 1405 180 23,282 14 237 129.3444444444 18 0 0 190 10 0 1293 0 0 1293
57 20:30 Berlin London 1259 175 19,598 13 14% 175 111.9885714286 0 0 0 175 0 0 0 0 0 0
57 6:30 London Brussels 996 180 20,435 10 168 113.5277777778 71 0 0 168 0 0 0 0 0 0
57 8:45 London Brussels 716 127 10,782 18 18% 127 84.8976377953 0 0 0 127 0 0 0 0 0 0
57 18:50 Brussels London 2205 180 23,283 23 372 129.35 28 0 0 190 10 0 1294 0 0 1294
57 21:05 Brussels London 969 180 14,156 11 163 78.6444444444 0 0 0 163 0 0 0 0 0 0
58 7:00 London Paris 1515 180 24,263 14 255 134.7944444444 68 0 0 190 10 0 1348 0 0 1348
58 10:15 London Paris 767 122 13,034 10 16% 122 106.8360655738 0 0 0 122 0 0 0 0 0 0
58 19:30 Paris London 1211 180 23,470 17 204 130.3888888889 13 0 0 190 10 0 1304 0 0 1304
58 22:00 Paris London 991 177 18,124 10 18% 177 102.395480226 0 0 0 177 0 0 0 0 0 0
58 6:50 London Madrid 1525 180 23,398 18 257 129.9888888889 28 0 0 190 10 0 1300 0 0 1300
58 9:30 London Madrid 992 180 21,122 15 167 117.3444444444 0 0 0 167 0 0 0 0 0 0
58 19:00 Madrid London 1519 180 24,791 13 256 137.7277777778 63 0 0 190 10 0 1377 0 0 1377
58 21:30 Madrid London 1179 127 10,772 10 11% 127 84.8188976378 0 0 0 127 0 0 0 0 0 0
58 7:10 London Berlin 1020 180 23,444 4 172 130.2444444444 44 0 0 172 0 0 0 0 0 0
58 9:15 London Berlin 679 146 15,099 10 22% 146 103.4178082192 0 0 0 146 0 0 0 0 0 0
58 18:30 Berlin London 1404 180 23,235 20 237 129.0833333333 11 0 0 190 10 0 1291 0 0 1291
58 20:30 Berlin London 1166 180 17,640 21 197 98 0 0 0 190 10 0 980 0 0 980
58 6:30 London Brussels 1386 180 27,241 13 234 151.3388888889 71 0 0 190 10 0 1513 0 0 1513
58 8:45 London Brussels 485 113 9,705 4 23% 113 85.8849557522 0 0 0 113 0 0 0 0 0 0
58 18:50 Brussels London 1522 180 24,506 11 257 136.1444444444 25 0 0 190 10 0 1361 0 0 1361
58 21:05 Brussels London 698 173 14,694 18 25% 173 84.936416185 0 0 0 173 0 0 0 0 0 0
59 7:00 London Paris 1082 180 25,817 15 182 143.4277777778 34 0 0 182 2 0 339 0 0 339
59 10:15 London Paris 1095 155 13,213 9 14% 155 85.2451612903 0 0 0 155 0 0 0 0 0 0
59 19:30 Paris London 1368 180 26,916 18 231 149.5333333333 16 0 0 190 10 0 1495 0 0 1495
59 22:00 Paris London 881 178 14,534 14 20% 178 81.6516853933 0 0 0 178 0 0 0 0 0 0
59 6:50 London Madrid 1634 180 19,011 22 275 105.6166666667 50 0 0 190 10 0 1056 0 0 1056
59 9:30 London Madrid 813 180 18,018 7 137 100.1 0 0 0 137 0 0 0 0 0 0
59 19:00 Madrid London 2047 180 21,102 28 345 117.2333333333 46 0 0 190 10 0 1172 0 0 1172
59 21:30 Madrid London 866 152 12,786 18 18% 152 84.1184210526 0 0 0 152 0 0 0 0 0 0
59 7:10 London Berlin 1089 180 20,988 15 184 116.6 54 0 0 184 4 0 413 0 0 413
59 9:15 London Berlin 989 147 13,349 21 15% 147 90.8095238095 0 0 0 147 0 0 0 0 0 0
59 18:30 Berlin London 1083 180 20,158 16 183 111.9888888889 20 0 0 183 3 0 283 0 0 283
59 20:30 Berlin London 1151 169 22,343 9 15% 169 132.2071005917 0 0 0 169 0 0 0 0 0 0
59 6:30 London Brussels 1504 180 24,166 8 253 134.2555555556 93 2 0 190 10 2 1343 260 0 1083
59 8:45 London Brussels 736 101 10,352 14 14% 101 102.495049505 0 0 0 101 0 0 0 0 0 0
59 18:50 Brussels London 1245 180 26,156 3 210 145.3111111111 41 7 0 190 10 7 1453 910 0 543
59 21:05 Brussels London 1183 163 13,309 24 14% 163 81.6503067485 0 0 0 163 0 0 0 0 0 0
60 7:00 London Paris 1774 180 25,740 6 299 143 45 4 0 190 10 4 1430 520 0 910
60 10:15 London Paris 825 152 13,074 17 18% 152 86.0131578947 0 0 0 152 0 0 0 0 0 0
60 19:30 Paris London 1657 180 22,040 12 279 122.4444444444 12 0 0 190 10 0 1224 0 0 1224
60 22:00 Paris London 1248 180 14,934 22 210 82.9666666667 0 0 0 190 10 0 830 0 0 830
60 6:50 London Madrid 1790 180 24,083 11 302 133.7944444444 19 0 0 190 10 0 1338 0 0 1338
60 9:30 London Madrid 988 180 14,150 6 167 78.6111111111 0 0 0 167 0 0 0 0 0 0
60 19:00 Madrid London 970 180 22,486 17 163 124.9222222222 41 0 0 163 0 0 0 0 0 0
60 21:30 Madrid London 1040 163 14,055 24 16% 163 86.226993865 0 0 0 163 0 0 0 0 0 0
60 7:10 London Berlin 1555 180 19,939 18 262 110.7722222222 19 0 0 190 10 0 1108 0 0 1108
60 9:15 London Berlin 1062 180 23,130 18 179 128.5 0 0 0 179 0 0 0 0 0 0
60 18:30 Berlin London 1155 180 22,486 7 195 124.9222222222 35 3 0 190 10 3 1249 390 0 859
60 20:30 Berlin London 840 165 16,782 20 20% 165 101.7090909091 0 0 0 165 0 0 0 0 0 0
60 6:30 London Brussels 1285 180 25,946 18 217 144.1444444444 49 0 0 190 10 0 1441 0 0 1441
60 8:45 London Brussels 1043 141 11,294 10 14% 141 80.0992907801 0 0 0 141 0 0 0 0 0 0
60 18:50 Brussels London 1833 180 28,333 14 309 157.4055555556 21 0 0 190 10 0 1574 0 0 1574
60 21:05 Brussels London 905 170 15,254 11 19% 170 89.7294117647 0 0 0 170 0 0 0 0 0 0
61 7:00 London Paris 1626 180 21,506 18 274 119.4777777778 21 0 0 190 10 0 1195 0 0 1195
61 10:15 London Paris 1036 180 18,248 16 175 101.3777777778 0 0 0 175 0 0 0 0 0 0
61 19:30 Paris London 1590 180 23,870 9 268 132.6111111111 32 1 0 190 10 1 1326 130 0 1196
61 22:00 Paris London 860 175 17,605 27 20% 175 100.6 0 0 0 175 0 0 0 0 0 0
61 6:50 London Madrid 1276 180 20,277 17 215 112.65 36 0 0 190 10 0 1127 0 0 1127
61 9:30 London Madrid 668 150 13,894 6 22% 150 92.6266666667 0 0 0 150 0 0 0 0 0 0
61 19:00 Madrid London 2250 180 18,814 24 379 104.5222222222 29 0 0 190 10 0 1045 0 0 1045
61 21:30 Madrid London 1014 180 14,816 20 171 82.3111111111 0 0 0 171 0 0 0 0 0 0
61 7:10 London Berlin 731 180 18,524 21 123 102.9111111111 41 0 0 123 0 0 0 0 0 0
61 9:15 London Berlin 940 145 11,427 6 15% 145 78.8068965517 0 0 0 145 0 0 0 0 0 0
61 18:30 Berlin London 1241 180 18,524 17 209 102.9111111111 59 0 0 190 10 0 1029 0 0 1029
61 20:30 Berlin London 848 180 13,540 22 143 75.2222222222 0 0 0 143 0 0 0 0 0 0
61 6:30 London Brussels 1019 180 19,072 23 172 105.9555555556 69 0 0 172 0 0 0 0 0 0
61 8:45 London Brussels 686 129 13,563 18 19% 129 105.1395348837 0 0 0 129 0 0 0 0 0 0
61 18:50 Brussels London 1418 180 27,818 17 239 154.5444444444 8 0 0 190 10 0 1545 0 0 1545
61 21:05 Brussels London 1086 178 15,400 6 16% 178 86.5168539326 0 0 0 178 0 0 0 0 0 0
62 7:00 London Paris 1629 180 26,156 15 275 145.3111111111 76 0 0 190 10 0 1453 0 0 1453
62 10:15 London Paris 928 122 12,064 18 13% 122 98.8852459016 0 0 0 122 0 0 0 0 0 0
62 19:30 Paris London 1595 180 27,778 7 269 154.3222222222 5 3 0 190 10 3 1543 390 0 1153
62 22:00 Paris London 1107 180 13,406 12 187 74.4777777778 0 0 0 187 7 0 490 0 0 490
62 6:50 London Madrid 1864 180 24,556 5 314 136.4222222222 19 5 0 190 10 5 1364 650 0 714
62 9:30 London Madrid 720 169 17,955 8 23% 169 106.2426035503 0 0 0 169 0 0 0 0 0 0
62 19:00 Madrid London 1977 180 24,705 26 333 137.25 37 0 0 190 10 0 1373 0 0 1373
62 21:30 Madrid London 1009 165 13,285 22 16% 165 80.5151515152 0 0 0 165 0 0 0 0 0 0
62 7:10 London Berlin 1464 180 22,369 6 247 124.2722222222 11 4 0 190 10 4 1243 520 0 723
62 9:15 London Berlin 1244 180 22,482 21 210 124.9 0 0 0 190 10 0 1249 0 0 1249
62 18:30 Berlin London 1667 180 22,464 22 281 124.8 34 0 0 190 10 0 1248 0 0 1248
62 20:30 Berlin London 966 163 18,471 17 17% 163 113.3190184049 0 0 0 163 0 0 0 0 0 0
62 6:30 London Brussels 1327 180 21,453 4 224 119.1833333333 54 6 0 190 10 6 1192 780 0 412
62 8:45 London Brussels 883 142 14,214 16 16% 142 100.0985915493 0 0 0 142 0 0 0 0 0 0
62 18:50 Brussels London 1501 180 19,344 7 253 107.4666666667 18 3 0 190 10 3 1075 390 0 685
62 21:05 Brussels London 1203 168 13,016 6 14% 168 77.4761904762 0 0 0 168 0 0 0 0 0 0
63 7:00 London Paris 1368 180 27,446 11 231 152.4777777778 0 0 0 190 10 0 1525 0 0 1525
63 10:15 London Paris 1367 180 23,528 5 230 130.7111111111 0 0 5 190 10 5 1307 0 1400 -93
63 19:30 Paris London 1481 180 25,792 11 250 143.2888888889 4 0 0 190 10 0 1433 0 0 1433
63 22:00 Paris London 1168 180 17,856 14 197 99.2 0 0 0 190 10 0 992 0 0 992
63 6:50 London Madrid 1180 180 20,427 13 199 113.4833333333 57 0 0 190 10 0 1135 0 0 1135
63 9:30 London Madrid 816 127 9,869 4 16% 127 77.7086614173 0 0 0 127 0 0 0 0 0 0
63 19:00 Madrid London 1455 180 20,757 5 245 115.3166666667 44 5 0 190 10 5 1153 650 0 503
63 21:30 Madrid London 1203 140 11,203 4 12% 140 80.0214285714 0 0 0 140 0 0 0 0 0 0
63 7:10 London Berlin 1239 180 22,562 17 209 125.3444444444 40 0 0 190 10 0 1253 0 0 1253
63 9:15 London Berlin 1001 145 14,226 5 14% 145 98.1103448276 0 0 0 145 0 0 0 0 0 0
63 18:30 Berlin London 1162 180 21,780 19 196 121 70 0 0 190 10 0 1210 0 0 1210
63 20:30 Berlin London 945 129 11,374 19 14% 129 88.1705426357 0 0 0 129 0 0 0 0 0 0
63 6:30 London Brussels 1268 180 21,422 19 214 119.0111111111 71 0 0 190 10 0 1190 0 0 1190
63 8:45 London Brussels 700 115 10,175 6 16% 115 88.4782608696 0 0 0 115 0 0 0 0 0 0
63 18:50 Brussels London 1701 180 19,597 6 287 108.8722222222 40 4 0 190 10 4 1089 520 0 569
63 21:05 Brussels London 810 159 16,910 19 20% 159 106.3522012579 0 0 0 159 0 0 0 0 0 0
64 7:00 London Paris 1597 180 24,423 14 269 135.6833333333 35 0 0 190 10 0 1357 0 0 1357
64 10:15 London Paris 1499 161 14,225 16 11% 161 88.3540372671 0 0 0 161 0 0 0 0 0 0
64 19:30 Paris London 1132 180 19,198 9 191 106.6555555556 0 0 1 190 10 1 1067 0 280 787
64 22:00 Paris London 1275 180 18,660 10 215 103.6666666667 0 0 0 190 10 0 1037 0 0 1037
64 6:50 London Madrid 1358 180 21,209 13 229 117.8277777778 12 0 0 190 10 0 1178 0 0 1178
64 9:30 London Madrid 983 171 14,103 3 17% 171 82.4736842105 0 0 0 171 0 0 0 0 0 0
64 19:00 Madrid London 1275 180 20,029 6 215 111.2722222222 57 4 0 190 10 4 1113 520 0 593
64 21:30 Madrid London 626 139 15,117 16 22% 139 108.7553956835 0 0 0 139 0 0 0 0 0 0
64 7:10 London Berlin 1454 180 17,071 27 245 94.8388888889 17 0 0 190 10 0 948 0 0 948
64 9:15 London Berlin 917 166 16,087 3 18% 166 96.9096385542 0 0 0 166 0 0 0 0 0 0
64 18:30 Berlin London 884 180 21,298 20 149 118.3222222222 26 0 0 149 0 0 0 0 0 0
64 20:30 Berlin London 830 161 13,525 7 19% 161 84.0062111801 0 0 0 161 0 0 0 0 0 0
64 6:30 London Brussels 1489 180 17,198 24 251 95.5444444444 87 0 0 190 10 0 955 0 0 955
64 8:45 London Brussels 523 102 10,017 9 20% 102 98.2058823529 0 0 0 102 0 0 0 0 0 0
64 18:50 Brussels London 1361 180 22,554 6 229 125.3 58 4 0 190 10 4 1253 520 0 733
64 21:05 Brussels London 1068 147 14,669 25 14% 147 99.7891156463 0 0 0 147 0 0 0 0 0 0
65 7:00 London Paris 2203 180 23,847 5 371 132.4833333333 58 5 0 190 10 5 1325 650 0 675
65 10:15 London Paris 1106 139 14,907 17 13% 139 107.2446043165 0 0 0 139 0 0 0 0 0 0
65 19:30 Paris London 1362 180 20,888 24 230 116.0444444444 56 0 0 190 10 0 1160 0 0 1160
65 22:00 Paris London 1189 141 10,743 17 12% 141 76.1914893617 0 0 0 141 0 0 0 0 0 0
65 6:50 London Madrid 1488 180 27,502 8 251 152.7888888889 17 2 0 190 10 2 1528 260 0 1268
65 9:30 London Madrid 1050 180 17,963 14 177 99.7944444444 0 0 0 177 0 0 0 0 0 0
65 19:00 Madrid London 1438 180 20,164 12 242 112.0222222222 50 0 0 190 10 0 1120 0 0 1120
65 21:30 Madrid London 788 137 11,018 7 17% 137 80.4233576642 0 0 0 137 0 0 0 0 0 0
65 7:10 London Berlin 1185 180 17,873 5 200 99.2944444444 16 5 0 190 10 5 993 650 0 343
65 9:15 London Berlin 1200 180 22,640 26 202 125.7777777778 0 0 0 190 10 0 1258 0 0 1258
65 18:30 Berlin London 1194 180 17,446 24 201 96.9222222222 10 0 0 190 10 0 969 0 0 969
65 20:30 Berlin London 901 178 15,014 8 20% 178 84.3483146067 0 0 0 178 0 0 0 0 0 0
65 6:30 London Brussels 1400 180 23,656 15 236 131.4222222222 29 0 0 190 10 0 1314 0 0 1314
65 8:45 London Brussels 808 164 16,068 13 20% 164 97.9756097561 0 0 0 164 0 0 0 0 0 0
65 18:50 Brussels London 1804 180 21,081 19 304 117.1166666667 21 0 0 190 10 0 1171 0 0 1171
65 21:05 Brussels London 1117 175 16,158 16 16% 175 92.3314285714 0 0 0 175 0 0 0 0 0 0
66 7:00 London Paris 1479 180 21,144 6 249 117.4666666667 22 4 0 190 10 4 1175 520 0 655
66 10:15 London Paris 954 170 18,353 12 18% 170 107.9588235294 0 0 0 170 0 0 0 0 0 0
66 19:30 Paris London 1153 180 16,533 4 194 91.85 42 6 0 190 10 6 919 780 0 139
66 22:00 Paris London 978 164 16,974 26 17% 164 103.5 0 0 0 164 0 0 0 0 0 0
66 6:50 London Madrid 2096 180 22,857 8 353 126.9833333333 3 2 0 190 10 2 1270 260 0 1010
66 9:30 London Madrid 1190 180 20,448 13 201 113.6 0 0 0 190 10 0 1136 0 0 1136
66 19:00 Madrid London 1449 180 20,805 9 244 115.5833333333 7 1 0 190 10 1 1156 130 0 1026
66 21:30 Madrid London 1045 180 15,198 3 176 84.4333333333 0 0 0 176 0 0 0 0 0 0
66 7:10 London Berlin 965 180 16,467 11 163 91.4833333333 46 0 0 163 0 0 0 0 0 0
66 9:15 London Berlin 1319 146 11,135 12 11% 146 76.2671232877 0 0 0 146 0 0 0 0 0 0
66 18:30 Berlin London 1277 180 16,695 22 215 92.75 33 0 0 190 10 0 928 0 0 928
66 20:30 Berlin London 1001 159 16,477 12 16% 159 103.6289308176 0 0 0 159 0 0 0 0 0 0
66 6:30 London Brussels 1360 180 20,414 14 229 113.4111111111 78 0 0 190 10 0 1134 0 0 1134
66 8:45 London Brussels 525 111 11,595 9 21% 111 104.4594594595 0 0 0 111 0 0 0 0 0 0
66 18:50 Brussels London 1841 180 27,902 24 310 155.0111111111 36 0 0 190 10 0 1550 0 0 1550
66 21:05 Brussels London 1190 168 16,035 24 14% 168 95.4464285714 0 0 0 168 0 0 0 0 0 0
67 7:00 London Paris 1430 180 21,485 14 241 119.3611111111 59 0 0 190 10 0 1194 0 0 1194
67 10:15 London Paris 768 128 13,172 7 17% 128 102.90625 0 0 0 128 0 0 0 0 0 0
67 19:30 Paris London 911 180 20,598 23 154 114.4333333333 13 0 0 154 0 0 0 0 0 0
67 22:00 Paris London 1285 180 17,927 23 217 99.5944444444 0 0 0 190 10 0 996 0 0 996
67 6:50 London Madrid 1350 180 27,651 14 228 153.6166666667 13 0 0 190 10 0 1536 0 0 1536
67 9:30 London Madrid 1008 173 18,199 6 17% 173 105.1965317919 0 0 0 173 0 0 0 0 0 0
67 19:00 Madrid London 1747 180 25,740 24 294 143 20 0 0 190 10 0 1430 0 0 1430
67 21:30 Madrid London 960 170 16,137 10 18% 170 94.9235294118 0 0 0 170 0 0 0 0 0 0
67 7:10 London Berlin 1295 180 18,054 28 218 100.3 38 0 0 190 10 0 1003 0 0 1003
67 9:15 London Berlin 930 160 17,653 18 17% 160 110.33125 0 0 0 160 0 0 0 0 0 0
67 18:30 Berlin London 1471 180 18,821 9 248 104.5611111111 37 1 0 190 10 1 1046 130 0 916
67 20:30 Berlin London 860 154 12,474 11 18% 154 81 0 0 0 154 0 0 0 0 0 0
67 6:30 London Brussels 1829 180 19,661 19 308 109.2277777778 79 0 0 190 10 0 1092 0 0 1092
67 8:45 London Brussels 668 118 9,286 17 18% 118 78.6949152542 0 0 0 118 0 0 0 0 0 0
67 18:50 Brussels London 1696 180 18,608 8 286 103.3777777778 90 2 0 190 10 2 1034 260 0 774
67 21:05 Brussels London 690 180 18,379 26 116 102.1055555556 0 0 0 116 0 0 0 0 0 0
68 7:00 London Paris 1353 180 27,667 29 228 153.7055555556 48 0 0 190 10 0 1537 0 0 1537
68 10:15 London Paris 811 142 12,487 10 18% 142 87.9366197183 0 0 0 142 0 0 0 0 0 0
68 19:30 Paris London 1674 180 19,084 6 282 106.0222222222 43 4 0 190 10 4 1060 520 0 540
68 22:00 Paris London 984 180 13,191 29 166 73.2833333333 0 0 0 166 0 0 0 0 0 0
68 6:50 London Madrid 1435 180 25,870 3 242 143.7222222222 1 1 6 190 10 7 1437 130 1680 -373
68 9:30 London Madrid 1175 180 23,808 11 198 132.2666666667 0 0 0 190 10 0 1323 0 0 1323
68 19:00 Madrid London 1356 180 20,722 14 229 115.1222222222 42 0 0 190 10 0 1151 0 0 1151
68 21:30 Madrid London 847 151 10,975 13 18% 151 72.6821192053 0 0 0 151 0 0 0 0 0 0
68 7:10 London Berlin 1622 180 26,156 20 273 145.3111111111 28 0 0 190 10 0 1453 0 0 1453
68 9:15 London Berlin 1047 180 21,165 24 176 117.5833333333 0 0 0 176 0 0 0 0 0 0
68 18:30 Berlin London 1466 180 22,154 26 247 123.0777777778 49 0 0 190 10 0 1231 0 0 1231
68 20:30 Berlin London 883 158 17,937 27 18% 158 113.5253164557 0 0 0 158 0 0 0 0 0 0
68 6:30 London Brussels 1118 180 18,234 10 188 101.3 67 0 0 188 8 0 854 0 0 854
68 8:45 London Brussels 480 133 10,055 20 28% 133 75.6015037594 0 0 0 133 0 0 0 0 0 0
68 18:50 Brussels London 1252 180 21,588 8 211 119.9333333333 36 2 0 190 10 2 1199 260 0 939
68 21:05 Brussels London 1227 165 15,173 21 13% 165 91.9575757576 0 0 0 165 0 0 0 0 0 0
69 7:00 London Paris 1757 180 20,997 3 296 116.65 47 7 0 190 10 7 1167 910 0 257
69 10:15 London Paris 820 180 15,951 5 138 88.6166666667 0 0 0 138 0 0 0 0 0 0
69 19:30 Paris London 1269 180 18,052 24 214 100.2888888889 32 0 0 190 10 0 1003 0 0 1003
69 22:00 Paris London 1103 174 15,439 26 16% 174 88.7298850575 0 0 0 174 0 0 0 0 0 0
69 6:50 London Madrid 1944 180 25,946 8 328 144.1444444444 27 2 0 190 10 2 1441 260 0 1181
69 9:30 London Madrid 934 180 18,251 4 157 101.3944444444 0 0 0 157 0 0 0 0 0 0
69 19:00 Madrid London 2539 180 19,930 13 428 110.7222222222 23 0 0 190 10 0 1107 0 0 1107
69 21:30 Madrid London 850 167 13,595 10 20% 167 81.4071856287 0 0 0 167 0 0 0 0 0 0
69 7:10 London Berlin 1226 180 26,051 10 207 144.7277777778 17 0 0 190 10 0 1447 0 0 1447
69 9:15 London Berlin 748 177 16,265 14 24% 177 91.8926553672 0 0 0 177 0 0 0 0 0 0
69 18:30 Berlin London 1055 180 18,612 22 178 103.4 1 0 0 178 0 0 0 0 0 0
69 20:30 Berlin London 1166 180 22,991 11 197 127.7277777778 0 0 0 190 10 0 1277 0 0 1277
69 6:30 London Brussels 921 180 17,640 13 155 98 93 0 0 155 0 0 0 0 0 0
69 8:45 London Brussels 760 90 6,581 3 12% 90 73.1222222222 0 0 0 90 0 0 0 0 0 0
69 18:50 Brussels London 1783 180 22,554 15 301 125.3 43 0 0 190 10 0 1253 0 0 1253
69 21:05 Brussels London 1238 142 15,117 5 11% 142 106.4577464789 0 0 0 142 0 0 0 0 0 0
70 7:00 London Paris 1873 180 21,294 19 316 118.3 36 0 0 190 10 0 1183 0 0 1183
70 10:15 London Paris 861 149 10,760 5 17% 149 72.2147651007 0 0 0 149 0 0 0 0 0 0
70 19:30 Paris London 1267 180 22,834 5 214 126.8555555556 30 5 0 190 10 5 1269 650 0 619
70 22:00 Paris London 933 180 18,783 7 157 104.35 0 0 0 157 0 0 0 0 0 0
70 6:50 London Madrid 1541 180 22,958 6 260 127.5444444444 22 4 0 190 10 4 1275 520 0 755
70 9:30 London Madrid 988 180 20,578 9 167 114.3222222222 0 0 0 167 0 0 0 0 0 0
70 19:00 Madrid London 1103 180 24,619 14 186 136.7722222222 29 0 0 186 6 0 807 0 0 807
70 21:30 Madrid London 808 156 16,858 5 19% 156 108.0641025641 0 0 0 156 0 0 0 0 0 0
70 7:10 London Berlin 1135 180 17,980 13 191 99.8888888889 50 0 0 190 10 0 999 0 0 999
70 9:15 London Berlin 965 154 12,015 24 16% 154 78.0194805195 0 0 0 154 0 0 0 0 0 0
70 18:30 Berlin London 1373 180 20,995 23 231 116.6388888889 48 0 0 190 10 0 1166 0 0 1166
70 20:30 Berlin London 835 144 15,323 12 17% 144 106.4097222222 0 0 0 144 0 0 0 0 0 0
70 6:30 London Brussels 1408 180 26,178 8 237 145.4333333333 73 2 0 190 10 2 1454 260 0 1194
70 8:45 London Brussels 649 124 9,598 17 19% 124 77.4032258065 0 0 0 124 0 0 0 0 0 0
70 18:50 Brussels London 2272 180 18,570 18 383 103.1666666667 57 0 0 190 10 0 1032 0 0 1032
70 21:05 Brussels London 686 138 12,220 15 20% 138 88.5507246377 0 0 0 138 0 0 0 0 0 0
71 7:00 London Paris 1707 180 25,378 22 288 140.9888888889 27 0 0 190 10 0 1410 0 0 1410
71 10:15 London Paris 1031 180 15,761 21 174 87.5611111111 0 0 0 174 0 0 0 0 0 0
71 19:30 Paris London 1220 180 20,501 14 206 113.8944444444 19 0 0 190 10 0 1139 0 0 1139
71 22:00 Paris London 1263 175 13,124 14 14% 175 74.9942857143 0 0 0 175 0 0 0 0 0 0
71 6:50 London Madrid 1385 180 21,588 14 233 119.9333333333 2 0 0 190 10 0 1199 0 0 1199
71 9:30 London Madrid 1115 180 14,991 10 188 83.2833333333 0 0 0 188 8 0 660 0 0 660
71 19:00 Madrid London 1657 180 20,029 4 279 111.2722222222 49 6 0 190 10 6 1113 780 0 333
71 21:30 Madrid London 956 145 15,284 14 15% 145 105.4068965517 0 0 0 145 0 0 0 0 0 0
71 7:10 London Berlin 1131 180 16,187 18 191 89.9277777778 0 0 0 190 10 0 899 0 0 899
71 9:15 London Berlin 1172 180 20,158 6 198 111.9888888889 0 0 4 190 10 4 1120 0 1120 -0
71 18:30 Berlin London 1242 180 18,764 27 209 104.2444444444 73 0 0 190 10 0 1042 0 0 1042
71 20:30 Berlin London 1133 125 9,723 18 11% 125 77.784 0 0 0 125 0 0 0 0 0 0
71 6:30 London Brussels 1135 180 22,374 7 191 124.3 103 3 0 190 10 3 1243 390 0 853
71 8:45 London Brussels 592 93 7,321 16 16% 93 78.7204301075 0 0 0 93 0 0 0 0 0 0
71 18:50 Brussels London 2415 180 19,833 10 407 110.1833333333 18 0 0 190 10 0 1102 0 0 1102
71 21:05 Brussels London 1140 180 13,404 28 192 74.4666666667 0 0 0 190 10 0 745 0 0 745
72 7:00 London Paris 1965 180 18,626 16 331 103.4777777778 36 0 0 190 10 0 1035 0 0 1035
72 10:15 London Paris 971 180 22,066 20 164 122.5888888889 0 0 0 164 0 0 0 0 0 0
72 19:30 Paris London 1209 180 18,641 24 204 103.5611111111 34 0 0 190 10 0 1036 0 0 1036
72 22:00 Paris London 1169 164 13,539 18 14% 164 82.5548780488 0 0 0 164 0 0 0 0 0 0
72 6:50 London Madrid 1175 180 24,829 12 198 137.9388888889 6 0 0 190 10 0 1379 0 0 1379
72 9:30 London Madrid 909 177 14,744 3 19% 177 83.2994350282 0 0 0 177 0 0 0 0 0 0
72 19:00 Madrid London 1862 180 18,776 6 314 104.3111111111 12 4 0 190 10 4 1043 520 0 523
72 21:30 Madrid London 900 176 18,560 8 20% 176 105.4545454545 0 0 0 176 0 0 0 0 0 0
72 7:10 London Berlin 972 180 20,277 16 164 112.65 15 0 0 164 0 0 0 0 0 0
72 9:15 London Berlin 1336 171 21,298 6 13% 171 124.5497076023 0 0 0 171 0 0 0 0 0 0
72 18:30 Berlin London 1205 180 23,060 16 203 128.1111111111 41 0 0 190 10 0 1281 0 0 1281
72 20:30 Berlin London 857 180 21,999 5 144 122.2166666667 0 0 0 144 0 0 0 0 0 0
72 6:30 London Brussels 1345 180 16,382 21 227 91.0111111111 39 0 0 190 10 0 910 0 0 910
72 8:45 London Brussels 585 155 11,985 14 26% 155 77.3225806452 0 0 0 155 0 0 0 0 0 0
72 18:50 Brussels London 2430 180 19,226 5 410 106.8111111111 28 5 0 190 10 5 1068 650 0 418
72 21:05 Brussels London 893 171 18,616 19 19% 171 108.865497076 0 0 0 171 0 0 0 0 0 0
73 7:00 London Paris 2237 180 27,253 12 377 151.4055555556 15 0 0 190 10 0 1514 0 0 1514
73 10:15 London Paris 995 172 18,632 7 17% 172 108.3255813953 0 0 0 172 0 0 0 0 0 0
73 19:30 Paris London 1281 180 20,934 10 216 116.3 42 0 0 190 10 0 1163 0 0 1163
73 22:00 Paris London 912 180 15,894 16 154 88.3 0 0 0 154 0 0 0 0 0 0
73 6:50 London Madrid 1862 180 19,087 19 314 106.0388888889 52 0 0 190 10 0 1060 0 0 1060
73 9:30 London Madrid 909 180 16,134 25 153 89.6333333333 0 0 0 153 0 0 0 0 0 0
73 19:00 Madrid London 1981 180 26,077 5 334 144.8722222222 27 5 0 190 10 5 1449 650 0 799
73 21:30 Madrid London 781 158 12,526 5 20% 158 79.2784810127 0 0 0 158 0 0 0 0 0 0
73 7:10 London Berlin 1385 180 28,041 17 233 155.7833333333 31 0 0 190 10 0 1558 0 0 1558
73 9:15 London Berlin 1304 171 20,234 22 13% 171 118.3274853801 0 0 0 171 0 0 0 0 0 0
73 18:30 Berlin London 1422 180 19,879 7 240 110.4388888889 46 3 0 190 10 3 1104 390 0 714
73 20:30 Berlin London 772 149 13,531 15 19% 149 90.8120805369 0 0 0 149 0 0 0 0 0 0
73 6:30 London Brussels 902 180 23,879 6 152 132.6611111111 84 0 0 152 0 0 0 0 0 0
73 8:45 London Brussels 864 116 10,123 20 13% 116 87.2672413793 0 0 0 116 0 0 0 0 0 0
73 18:50 Brussels London 1224 180 23,658 27 206 131.4333333333 31 0 0 190 10 0 1314 0 0 1314
73 21:05 Brussels London 1022 177 15,865 28 17% 177 89.6327683616 0 0 0 177 0 0 0 0 0 0
74 7:00 London Paris 1407 180 27,018 15 237 150.1 9 0 0 190 10 0 1501 0 0 1501
74 10:15 London Paris 1153 180 21,234 19 194 117.9666666667 0 0 0 190 10 0 1180 0 0 1180
74 19:30 Paris London 1098 180 21,610 4 185 120.0555555556 45 1 0 185 5 1 607 137 0 470
74 22:00 Paris London 960 145 14,080 10 15% 145 97.1034482759 0 0 0 145 0 0 0 0 0 0
74 6:50 London Madrid 1218 180 21,544 16 205 119.6888888889 15 0 0 190 10 0 1197 0 0 1197
74 9:30 London Madrid 1133 179 15,642 14 16% 179 87.3854748603 0 0 0 179 0 0 0 0 0 0
74 19:00 Madrid London 1444 180 21,806 21 243 121.1444444444 55 0 0 190 10 0 1211 0 0 1211
74 21:30 Madrid London 1081 148 15,261 23 14% 148 103.1148648649 0 0 0 148 0 0 0 0 0 0
74 7:10 London Berlin 1670 180 22,274 27 281 123.7444444444 39 0 0 190 10 0 1237 0 0 1237
74 9:15 London Berlin 1129 146 15,459 5 13% 146 105.8835616438 0 0 0 146 0 0 0 0 0 0
74 18:30 Berlin London 1406 180 23,143 3 237 128.5722222222 0 0 7 190 10 7 1286 0 1960 -674
74 20:30 Berlin London 1298 180 20,510 7 219 113.9444444444 0 0 3 190 10 3 1139 0 840 299
74 6:30 London Brussels 1411 180 21,166 23 238 117.5888888889 78 0 0 190 10 0 1176 0 0 1176
74 8:45 London Brussels 733 117 8,500 15 16% 117 72.6495726496 0 0 0 117 0 0 0 0 0 0
74 18:50 Brussels London 1444 180 20,089 18 243 111.6055555556 32 0 0 190 10 0 1116 0 0 1116
74 21:05 Brussels London 926 180 15,023 8 156 83.4611111111 0 0 0 156 0 0 0 0 0 0
75 7:00 London Paris 1735 180 24,779 4 292 137.6611111111 67 6 0 190 10 6 1377 780 0 597
75 10:15 London Paris 773 180 20,178 17 130 112.1 0 0 0 130 0 0 0 0 0 0
75 19:30 Paris London 1336 180 19,479 3 225 108.2166666667 19 7 0 190 10 7 1082 910 0 172
75 22:00 Paris London 1041 164 12,446 3 16% 164 75.8902439024 0 0 0 164 0 0 0 0 0 0
75 6:50 London Madrid 1515 180 21,315 14 255 118.4166666667 14 0 0 190 10 0 1184 0 0 1184
75 9:30 London Madrid 1042 180 23,903 10 176 132.7944444444 0 0 0 176 0 0 0 0 0 0
75 19:00 Madrid London 1450 180 26,339 21 244 146.3277777778 57 0 0 190 10 0 1463 0 0 1463
75 21:30 Madrid London 1126 139 11,372 16 12% 139 81.8129496403 0 0 0 139 0 0 0 0 0 0
75 7:10 London Berlin 1286 180 16,813 24 217 93.4055555556 0 0 0 190 10 0 934 0 0 934
75 9:15 London Berlin 1429 180 19,264 7 241 107.0222222222 0 0 3 190 10 3 1070 0 840 230
75 18:30 Berlin London 1521 180 21,517 6 256 119.5388888889 53 4 0 190 10 4 1195 520 0 675
75 20:30 Berlin London 935 132 14,399 5 14% 132 109.0833333333 0 0 0 132 0 0 0 0 0 0
75 6:30 London Brussels 1463 180 21,166 11 247 117.5888888889 47 0 0 190 10 0 1176 0 0 1176
75 8:45 London Brussels 865 154 16,135 21 18% 154 104.7727272727 0 0 0 154 0 0 0 0 0 0
75 18:50 Brussels London 1475 180 24,816 25 249 137.8666666667 21 0 0 190 10 0 1379 0 0 1379
75 21:05 Brussels London 1294 162 11,781 3 13% 162 72.7222222222 0 0 0 162 0 0 0 0 0 0
76 7:00 London Paris 2124 180 22,008 16 358 122.2666666667 21 0 0 190 10 0 1223 0 0 1223
76 10:15 London Paris 985 173 15,795 14 18% 173 91.3005780347 0 0 0 173 0 0 0 0 0 0
76 19:30 Paris London 1115 180 21,443 5 188 119.1277777778 24 3 0 188 8 3 944 380 0 564
76 22:00 Paris London 789 172 13,158 16 22% 172 76.5 0 0 0 172 0 0 0 0 0 0
76 6:50 London Madrid 1417 180 20,934 17 239 116.3 45 0 0 190 10 0 1163 0 0 1163
76 9:30 London Madrid 739 148 13,733 13 20% 148 92.7905405405 0 0 0 148 0 0 0 0 0 0
76 19:00 Madrid London 1373 180 23,004 29 231 127.8 25 0 0 190 10 0 1278 0 0 1278
76 21:30 Madrid London 676 173 14,902 18 26% 173 86.1387283237 0 0 0 173 0 0 0 0 0 0
76 7:10 London Berlin 1055 161 15,971 8 15% 161 99.198757764 45 0 0 161 0 0 0 0 0 0
76 9:15 London Berlin 1079 151 14,413 16 14% 151 95.4503311258 0 0 0 151 0 0 0 0 0 0
76 18:30 Berlin London 1224 180 24,779 16 206 137.6611111111 22 0 0 190 10 0 1377 0 0 1377
76 20:30 Berlin London 944 166 15,990 8 18% 166 96.3253012048 0 0 0 166 0 0 0 0 0 0
76 6:30 London Brussels 1071 180 23,538 8 181 130.7666666667 72 0 0 181 1 0 66 0 0 66
76 8:45 London Brussels 484 122 9,452 14 25% 122 77.4754098361 0 0 0 122 0 0 0 0 0 0
76 18:50 Brussels London 1795 180 27,045 28 303 150.25 16 0 0 190 10 0 1503 0 0 1503
76 21:05 Brussels London 808 169 16,916 5 21% 169 100.0946745562 0 0 0 169 0 0 0 0 0 0
77 7:00 London Paris 2194 180 21,697 19 370 120.5388888889 30 0 0 190 10 0 1205 0 0 1205
77 10:15 London Paris 982 157 15,386 7 16% 157 98 0 0 0 157 0 0 0 0 0 0
77 19:30 Paris London 1194 180 26,104 3 201 145.0222222222 40 7 0 190 10 7 1450 910 0 540
77 22:00 Paris London 857 180 17,909 4 144 99.4944444444 0 0 0 144 0 0 0 0 0 0
77 6:50 London Madrid 1687 180 23,351 17 284 129.7277777778 43 0 0 190 10 0 1297 0 0 1297
77 9:30 London Madrid 946 150 10,714 13 16% 150 71.4266666667 0 0 0 150 0 0 0 0 0 0
77 19:00 Madrid London 1433 180 26,623 5 242 147.9055555556 35 5 0 190 10 5 1479 650 0 829
77 21:30 Madrid London 917 161 16,535 16 18% 161 102.701863354 0 0 0 161 0 0 0 0 0 0
77 7:10 London Berlin 1576 180 24,680 9 266 137.1111111111 80 1 0 190 10 1 1371 130 0 1241
77 9:15 London Berlin 781 123 9,038 23 16% 123 73.4796747967 0 0 0 123 0 0 0 0 0 0
77 18:30 Berlin London 1368 180 20,820 15 231 115.6666666667 47 0 0 190 10 0 1157 0 0 1157
77 20:30 Berlin London 833 149 12,203 16 18% 149 81.8993288591 0 0 0 149 0 0 0 0 0 0
77 6:30 London Brussels 1796 180 28,069 19 303 155.9388888889 65 0 0 190 10 0 1559 0 0 1559
77 8:45 London Brussels 584 132 9,428 17 23% 132 71.4242424242 0 0 0 132 0 0 0 0 0 0
77 18:50 Brussels London 1609 180 19,830 19 271 110.1666666667 43 0 0 190 10 0 1102 0 0 1102
77 21:05 Brussels London 993 155 15,251 18 16% 155 98.3935483871 0 0 0 155 0 0 0 0 0 0
78 7:00 London Paris 1707 180 25,213 15 288 140.0722222222 7 0 0 190 10 0 1401 0 0 1401
78 10:15 London Paris 1389 176 17,651 3 13% 176 100.2897727273 0 0 0 176 0 0 0 0 0 0
78 19:30 Paris London 1035 180 27,707 17 174 153.9277777778 53 0 0 174 0 0 0 0 0 0
78 22:00 Paris London 883 135 9,671 8 15% 135 71.637037037 0 0 0 135 0 0 0 0 0 0
78 6:50 London Madrid 1117 180 24,913 13 188 138.4055555556 63 0 0 188 8 0 1143 0 0 1143
78 9:30 London Madrid 972 138 10,784 21 14% 138 78.1449275362 0 0 0 138 0 0 0 0 0 0
78 19:00 Madrid London 1364 180 22,262 9 230 123.6777777778 53 1 0 190 10 1 1237 130 0 1107
78 21:30 Madrid London 1018 139 14,219 12 14% 139 102.2949640288 0 0 0 139 0 0 0 0 0 0
78 7:10 London Berlin 1749 180 23,387 15 295 129.9277777778 5 0 0 190 10 0 1299 0 0 1299
78 9:15 London Berlin 1424 180 20,977 15 240 116.5388888889 0 0 0 190 10 0 1165 0 0 1165
78 18:30 Berlin London 1399 169 15,600 12 12% 169 92.3076923077 43 0 0 169 0 0 0 0 0 0
78 20:30 Berlin London 868 147 14,360 10 17% 147 97.6870748299 0 0 0 147 0 0 0 0 0 0
78 6:30 London Brussels 1446 180 22,442 13 244 124.6777777778 49 0 0 190 10 0 1247 0 0 1247
78 8:45 London Brussels 990 144 12,777 13 15% 144 88.7291666667 0 0 0 144 0 0 0 0 0 0
78 18:50 Brussels London 1305 180 19,322 16 220 107.3444444444 32 0 0 190 10 0 1073 0 0 1073
78 21:05 Brussels London 1047 167 14,924 19 16% 167 89.3652694611 0 0 0 167 0 0 0 0 0 0
79 7:00 London Paris 1918 180 27,144 19 323 150.8 52 0 0 190 10 0 1508 0 0 1508
79 10:15 London Paris 869 180 17,499 18 146 97.2166666667 0 0 0 146 0 0 0 0 0 0
79 19:30 Paris London 1884 180 26,313 3 318 146.1833333333 46 7 0 190 10 7 1462 910 0 552
79 22:00 Paris London 840 154 13,350 20 18% 154 86.6883116883 0 0 0 154 0 0 0 0 0 0
79 6:50 London Madrid 1605 180 27,595 22 271 153.3055555556 16 0 0 190 10 0 1533 0 0 1533
79 9:30 London Madrid 1073 169 21,672 5 16% 169 128.2366863905 0 0 0 169 0 0 0 0 0 0
79 19:00 Madrid London 1424 180 25,761 11 240 143.1166666667 32 0 0 190 10 0 1431 0 0 1431
79 21:30 Madrid London 1301 173 18,714 25 13% 173 108.1734104046 0 0 0 173 0 0 0 0 0 0
79 7:10 London Berlin 1463 180 27,883 20 247 154.9055555556 6 0 0 190 10 0 1549 0 0 1549
79 9:15 London Berlin 1286 180 22,656 16 217 125.8666666667 0 0 0 190 10 0 1259 0 0 1259
79 18:30 Berlin London 1672 180 26,495 15 282 147.1944444444 29 0 0 190 10 0 1472 0 0 1472
79 20:30 Berlin London 885 174 17,261 23 20% 174 99.2011494253 0 0 0 174 0 0 0 0 0 0
79 6:30 London Brussels 1383 180 24,668 23 233 137.0444444444 19 0 0 190 10 0 1370 0 0 1370
79 8:45 London Brussels 674 172 15,790 11 26% 172 91.8023255814 0 0 0 172 0 0 0 0 0 0
79 18:50 Brussels London 1188 180 27,117 6 200 150.65 31 4 0 190 10 4 1507 520 0 987
79 21:05 Brussels London 934 165 14,850 16 18% 165 90 0 0 0 165 0 0 0 0 0 0
80 7:00 London Paris 1436 180 20,154 21 242 111.9666666667 10 0 0 190 10 0 1120 0 0 1120
80 10:15 London Paris 1045 180 18,742 6 176 104.1222222222 0 0 0 176 0 0 0 0 0 0
80 19:30 Paris London 1422 180 25,637 9 240 142.4277777778 57 1 0 190 10 1 1424 130 0 1294
80 22:00 Paris London 876 143 15,263 20 16% 143 106.7342657343 0 0 0 143 0 0 0 0 0 0
80 6:50 London Madrid 1341 180 21,018 10 226 116.7666666667 36 0 0 190 10 0 1168 0 0 1168
80 9:30 London Madrid 741 162 12,235 18 22% 162 75.524691358 0 0 0 162 0 0 0 0 0 0
80 19:00 Madrid London 1238 180 25,378 14 209 140.9888888889 58 0 0 190 10 0 1410 0 0 1410
80 21:30 Madrid London 852 132 13,900 10 15% 132 105.303030303 0 0 0 132 0 0 0 0 0 0
80 7:10 London Berlin 1812 180 16,434 25 305 91.3 19 0 0 190 10 0 913 0 0 913
80 9:15 London Berlin 1210 180 19,398 29 204 107.7666666667 0 0 0 190 10 0 1078 0 0 1078
80 18:30 Berlin London 1623 180 25,843 19 274 143.5722222222 47 0 0 190 10 0 1436 0 0 1436
80 20:30 Berlin London 867 149 14,052 16 17% 149 94.3087248322 0 0 0 149 0 0 0 0 0 0
80 6:30 London Brussels 1110 180 24,556 17 187 136.4222222222 88 0 0 187 7 0 966 0 0 966
80 8:45 London Brussels 570 115 9,465 23 20% 115 82.3043478261 0 0 0 115 0 0 0 0 0 0
80 18:50 Brussels London 1785 180 18,897 5 301 104.9833333333 16 5 0 190 10 5 1050 650 0 400
80 21:05 Brussels London 947 178 14,564 14 19% 178 81.8202247191 0 0 0 178 0 0 0 0 0 0
81 7:00 London Paris 1535 180 21,631 16 259 120.1722222222 12 0 0 190 10 0 1202 0 0 1202
81 10:15 London Paris 720 175 13,791 7 24% 175 78.8057142857 0 0 0 175 0 0 0 0 0 0
81 19:30 Paris London 1487 180 26,391 15 251 146.6166666667 64 0 0 190 10 0 1466 0 0 1466
81 22:00 Paris London 1085 141 11,743 25 13% 141 83.2836879433 0 0 0 141 0 0 0 0 0 0
81 6:50 London Madrid 1637 180 25,188 18 276 139.9333333333 55 0 0 190 10 0 1399 0 0 1399
81 9:30 London Madrid 902 140 13,428 15 16% 140 95.9142857143 0 0 0 140 0 0 0 0 0 0
81 19:00 Madrid London 1823 180 24,006 13 307 133.3666666667 20 0 0 190 10 0 1334 0 0 1334
81 21:30 Madrid London 596 167 13,003 7 28% 167 77.8622754491 0 0 0 167 0 0 0 0 0 0
81 7:10 London Berlin 1694 180 18,878 16 286 104.8777777778 10 0 0 190 10 0 1049 0 0 1049
81 9:15 London Berlin 1541 175 15,292 5 11% 175 87.3828571429 0 0 0 175 0 0 0 0 0 0
81 18:30 Berlin London 1909 180 26,516 10 322 147.3111111111 57 0 0 190 10 0 1473 0 0 1473
81 20:30 Berlin London 1033 144 11,473 21 14% 144 79.6736111111 0 0 0 144 0 0 0 0 0 0
81 6:30 London Brussels 1663 180 22,509 7 280 125.05 90 3 0 190 10 3 1251 390 0 861
81 8:45 London Brussels 608 112 10,070 22 18% 112 89.9107142857 0 0 0 112 0 0 0 0 0 0
81 18:50 Brussels London 1662 180 25,637 16 280 142.4277777778 40 0 0 190 10 0 1424 0 0 1424
81 21:05 Brussels London 942 147 11,332 7 16% 147 77.0884353741 0 0 0 147 0 0 0 0 0 0
82 7:00 London Paris 2039 180 26,641 11 344 148.0055555556 14 0 0 190 10 0 1480 0 0 1480
82 10:15 London Paris 1037 176 17,037 10 17% 176 96.8011363636 0 0 0 176 0 0 0 0 0 0
82 19:30 Paris London 1357 180 28,305 10 229 157.25 51 0 0 190 10 0 1573 0 0 1573
82 22:00 Paris London 1116 150 14,416 21 13% 150 96.1066666667 0 0 0 150 0 0 0 0 0 0
82 6:50 London Madrid 1231 180 27,152 6 207 150.8444444444 22 4 0 190 10 4 1508 520 0 988
82 9:30 London Madrid 1194 161 14,168 3 13% 161 88 0 0 0 161 0 0 0 0 0 0
82 19:00 Madrid London 1641 180 25,302 7 277 140.5666666667 23 3 0 190 10 3 1406 390 0 1016
82 21:30 Madrid London 681 165 16,794 8 24% 165 101.7818181818 0 0 0 165 0 0 0 0 0 0
82 7:10 London Berlin 1163 158 20,447 13 14% 158 129.4113924051 41 0 0 158 0 0 0 0 0 0
82 9:15 London Berlin 1106 158 12,901 19 14% 158 81.6518987342 0 0 0 158 0 0 0 0 0 0
82 18:30 Berlin London 1062 180 19,340 6 179 107.4444444444 30 0 0 179 0 0 0 0 0 0
82 20:30 Berlin London 937 180 13,312 8 158 73.9555555556 0 0 0 158 0 0 0 0 0 0
82 6:30 London Brussels 1002 180 23,235 19 169 129.0833333333 48 0 0 169 0 0 0 0 0 0
82 8:45 London Brussels 654 138 13,869 6 21% 138 100.5 0 0 0 138 0 0 0 0 0 0
82 18:50 Brussels London 1979 180 21,039 3 334 116.8833333333 56 7 0 190 10 7 1169 910 0 259
82 21:05 Brussels London 773 147 13,589 23 19% 147 92.4421768707 0 0 0 147 0 0 0 0 0 0
83 7:00 London Paris 1589 180 18,683 22 268 103.7944444444 62 0 0 190 10 0 1038 0 0 1038
83 10:15 London Paris 781 180 14,595 14 132 81.0833333333 0 0 0 132 0 0 0 0 0 0
83 19:30 Paris London 1642 180 20,784 12 277 115.4666666667 34 0 0 190 10 0 1155 0 0 1155
83 22:00 Paris London 1306 149 14,396 3 11% 149 96.6174496644 0 0 0 149 0 0 0 0 0 0
83 6:50 London Madrid 1476 180 20,325 5 249 112.9166666667 24 5 0 190 10 5 1129 650 0 479
83 9:30 London Madrid 1012 173 18,308 17 17% 173 105.8265895954 0 0 0 173 0 0 0 0 0 0
83 19:00 Madrid London 1321 180 22,771 21 223 126.5055555556 57 0 0 190 10 0 1265 0 0 1265
83 21:30 Madrid London 791 180 15,152 10 133 84.1777777778 0 0 0 133 0 0 0 0 0 0
83 7:10 London Berlin 1454 180 19,168 5 245 106.4888888889 50 5 0 190 10 5 1065 650 0 415
83 9:15 London Berlin 1243 144 11,592 14 12% 144 80.5 0 0 0 144 0 0 0 0 0 0
83 18:30 Berlin London 1298 180 18,829 17 219 104.6055555556 21 0 0 190 10 0 1046 0 0 1046
83 20:30 Berlin London 964 180 23,097 3 162 128.3166666667 0 0 0 162 0 0 0 0 0 0
83 6:30 London Brussels 1204 180 18,271 22 203 101.5055555556 31 0 0 190 10 0 1015 0 0 1015
83 8:45 London Brussels 750 154 12,348 5 21% 154 80.1818181818 0 0 0 154 0 0 0 0 0 0
83 18:50 Brussels London 1711 180 24,791 27 288 137.7277777778 44 0 0 190 10 0 1377 0 0 1377
83 21:05 Brussels London 987 145 14,733 9 15% 145 101.6068965517 0 0 0 145 0 0 0 0 0 0
84 7:00 London Paris 2388 180 23,868 17 402 132.6 54 0 0 190 10 0 1326 0 0 1326
84 10:15 London Paris 1154 139 13,430 13 12% 139 96.618705036 0 0 0 139 0 0 0 0 0 0
84 19:30 Paris London 1168 180 25,685 15 197 142.6944444444 29 0 0 190 10 0 1427 0 0 1427
84 22:00 Paris London 825 165 14,702 14 20% 165 89.103030303 0 0 0 165 0 0 0 0 0 0
84 6:50 London Madrid 1174 180 27,790 18 198 154.3888888889 28 0 0 190 10 0 1544 0 0 1544
84 9:30 London Madrid 849 160 12,228 8 19% 160 76.425 0 0 0 160 0 0 0 0 0 0
84 19:00 Madrid London 1224 180 20,934 10 206 116.3 16 0 0 190 10 0 1163 0 0 1163
84 21:30 Madrid London 1049 171 13,652 7 16% 171 79.8362573099 0 0 0 171 0 0 0 0 0 0
84 7:10 London Berlin 992 180 18,754 16 167 104.1888888889 0 0 0 167 0 0 0 0 0 0
84 9:15 London Berlin 1530 180 17,856 3 258 99.2 0 0 7 190 10 7 992 0 1960 -968
84 18:30 Berlin London 1316 180 19,111 13 222 106.1722222222 65 0 0 190 10 0 1062 0 0 1062
84 20:30 Berlin London 832 137 12,856 22 16% 137 93.8394160584 0 0 0 137 0 0 0 0 0 0
84 6:30 London Brussels 1959 180 20,399 8 330 113.3277777778 84 2 0 190 10 2 1133 260 0 873
84 8:45 London Brussels 655 114 8,696 18 17% 114 76.2807017544 0 0 0 114 0 0 0 0 0 0
84 18:50 Brussels London 1406 180 20,265 9 237 112.5833333333 23 1 0 190 10 1 1126 130 0 996
84 21:05 Brussels London 749 167 15,921 10 22% 167 95.3353293413 0 0 0 167 0 0 0 0 0 0
85 7:00 London Paris 1966 180 22,297 4 331 123.8722222222 57 6 0 190 10 6 1239 780 0 459
85 10:15 London Paris 857 180 18,217 21 144 101.2055555556 0 0 0 144 0 0 0 0 0 0
85 19:30 Paris London 1688 180 18,463 20 284 102.5722222222 46 0 0 190 10 0 1026 0 0 1026
85 22:00 Paris London 894 180 14,370 17 151 79.8333333333 0 0 0 151 0 0 0 0 0 0
85 6:50 London Madrid 1687 180 27,750 17 284 154.1666666667 65 0 0 190 10 0 1542 0 0 1542
85 9:30 London Madrid 897 144 11,485 29 16% 144 79.7569444444 0 0 0 144 0 0 0 0 0 0
85 19:00 Madrid London 1793 180 24,953 4 302 138.6277777778 79 6 0 190 10 6 1386 780 0 606
85 21:30 Madrid London 937 129 10,638 28 14% 129 82.4651162791 0 0 0 129 0 0 0 0 0 0
85 7:10 London Berlin 951 180 19,543 4 160 108.5722222222 16 0 0 160 0 0 0 0 0 0
85 9:15 London Berlin 1045 180 14,227 12 176 79.0388888889 0 0 0 176 0 0 0 0 0 0
85 18:30 Berlin London 1199 180 18,678 27 202 103.7666666667 85 0 0 190 10 0 1038 0 0 1038
85 20:30 Berlin London 780 122 11,546 27 16% 122 94.6393442623 0 0 0 122 0 0 0 0 0 0
85 6:30 London Brussels 1396 180 24,531 6 235 136.2833333333 47 4 0 190 10 4 1363 520 0 843
85 8:45 London Brussels 852 141 12,804 8 17% 141 90.8085106383 0 0 0 141 0 0 0 0 0 0
85 18:50 Brussels London 1896 180 24,423 14 320 135.6833333333 0 0 0 190 10 0 1357 0 0 1357
85 21:05 Brussels London 1163 180 18,905 6 196 105.0277777778 0 0 4 190 10 4 1050 0 1120 -70
86 7:00 London Paris 1556 180 27,778 20 262 154.3222222222 20 0 0 190 10 0 1543 0 0 1543
86 10:15 London Paris 972 179 13,979 19 18% 179 78.094972067 0 0 0 179 0 0 0 0 0 0
86 19:30 Paris London 1024 180 21,030 3 173 116.8333333333 41 0 0 173 0 0 0 0 0 0
86 22:00 Paris London 1163 167 17,129 28 14% 167 102.5688622754 0 0 0 167 0 0 0 0 0 0
86 6:50 London Madrid 1464 180 23,681 24 247 131.5611111111 30 0 0 190 10 0 1316 0 0 1316
86 9:30 London Madrid 957 180 16,653 11 161 92.5166666667 0 0 0 161 0 0 0 0 0 0
86 19:00 Madrid London 2125 180 27,667 16 358 153.7055555556 19 0 0 190 10 0 1537 0 0 1537
86 21:30 Madrid London 991 180 13,526 6 167 75.1444444444 0 0 0 167 0 0 0 0 0 0
86 7:10 London Berlin 1051 166 15,870 11 16% 166 95.6024096386 57 0 0 166 0 0 0 0 0 0
86 9:15 London Berlin 969 127 13,702 4 13% 127 107.8897637795 0 0 0 127 0 0 0 0 0 0
86 18:30 Berlin London 1152 180 23,831 8 194 132.3944444444 14 2 0 190 10 2 1324 260 0 1064
86 20:30 Berlin London 1071 180 21,398 15 181 118.8777777778 0 0 0 181 1 0 60 0 0 60
86 6:30 London Brussels 1957 180 25,163 6 330 139.7944444444 37 4 0 190 10 4 1398 520 0 878
86 8:45 London Brussels 871 162 17,385 19 19% 162 107.3148148148 0 0 0 162 0 0 0 0 0 0
86 18:50 Brussels London 1720 180 19,054 3 290 105.8555555556 1 1 6 190 10 7 1059 130 1680 -751
86 21:05 Brussels London 1191 180 13,567 11 201 75.3722222222 0 0 0 190 10 0 754 0 0 754
87 7:00 London Paris 1607 180 25,685 18 271 142.6944444444 22 0 0 190 10 0 1427 0 0 1427
87 10:15 London Paris 769 176 17,600 18 23% 176 100 0 0 0 176 0 0 0 0 0 0
87 19:30 Paris London 1471 180 21,145 16 248 117.4722222222 31 0 0 190 10 0 1175 0 0 1175
87 22:00 Paris London 1258 169 13,951 20 13% 169 82.550295858 0 0 0 169 0 0 0 0 0 0
87 6:50 London Madrid 1976 180 21,034 18 333 116.8555555556 54 0 0 190 10 0 1169 0 0 1169
87 9:30 London Madrid 1023 134 10,403 8 13% 134 77.6343283582 0 0 0 134 0 0 0 0 0 0
87 19:00 Madrid London 2080 180 25,608 13 351 142.2666666667 23 0 0 190 10 0 1423 0 0 1423
87 21:30 Madrid London 816 177 14,656 20 22% 177 82.802259887 0 0 0 177 0 0 0 0 0 0
87 7:10 London Berlin 1088 180 19,046 18 183 105.8111111111 7 0 0 183 3 0 357 0 0 357
87 9:15 London Berlin 1439 180 19,225 17 243 106.8055555556 0 0 0 190 10 0 1068 0 0 1068
87 18:30 Berlin London 1238 180 19,622 13 209 109.0111111111 13 0 0 190 10 0 1090 0 0 1090
87 20:30 Berlin London 1132 180 16,780 23 191 93.2222222222 0 0 0 190 10 0 932 0 0 932
87 6:30 London Brussels 1410 180 21,177 4 238 117.65 63 6 0 190 10 6 1177 780 0 397
87 8:45 London Brussels 939 125 12,462 8 13% 125 99.696 0 0 0 125 0 0 0 0 0 0
87 18:50 Brussels London 1585 180 26,025 23 267 144.5833333333 11 0 0 190 10 0 1446 0 0 1446
87 21:05 Brussels London 1324 180 13,662 21 223 75.9 0 0 0 190 10 0 759 0 0 759
88 7:00 London Paris 1466 180 19,286 12 247 107.1444444444 36 0 0 190 10 0 1071 0 0 1071
88 10:15 London Paris 1136 164 20,165 20 14% 164 122.9573170732 0 0 0 164 0 0 0 0 0 0
88 19:30 Paris London 1322 180 23,658 18 223 131.4333333333 12 0 0 190 10 0 1314 0 0 1314
88 22:00 Paris London 1097 180 12,895 17 185 71.6388888889 0 0 0 185 5 0 350 0 0 350
88 6:50 London Madrid 1748 180 26,208 5 295 145.6 64 5 0 190 10 5 1456 650 0 806
88 9:30 London Madrid 686 134 10,189 18 20% 134 76.0373134328 0 0 0 134 0 0 0 0 0 0
88 19:00 Madrid London 2003 180 22,689 9 338 126.05 34 1 0 190 10 1 1261 130 0 1131
88 21:30 Madrid London 937 180 18,736 12 158 104.0888888889 0 0 0 158 0 0 0 0 0 0
88 7:10 London Berlin 1116 180 18,622 4 188 103.4555555556 45 4 0 188 8 4 837 532 0 305
88 9:15 London Berlin 888 180 18,143 15 150 100.7944444444 0 0 0 150 0 0 0 0 0 0
88 18:30 Berlin London 1515 180 19,700 10 255 109.4444444444 32 0 0 190 10 0 1094 0 0 1094
88 20:30 Berlin London 828 166 16,549 18 20% 166 99.6927710843 0 0 0 166 0 0 0 0 0 0
88 6:30 London Brussels 1927 180 23,868 9 325 132.6 62 1 0 190 10 1 1326 130 0 1196
88 8:45 London Brussels 822 141 14,254 23 17% 141 101.0921985816 0 0 0 141 0 0 0 0 0 0
88 18:50 Brussels London 1513 180 25,213 6 255 140.0722222222 14 4 0 190 10 4 1401 520 0 881
88 21:05 Brussels London 1034 180 13,325 8 174 74.0277777778 0 0 0 174 0 0 0 0 0 0
89 7:00 London Paris 1244 180 19,636 9 210 109.0888888889 12 1 0 190 10 1 1091 130 0 961
89 10:15 London Paris 1056 176 15,540 8 17% 176 88.2954545455 0 0 0 176 0 0 0 0 0 0
89 19:30 Paris London 1392 180 21,593 18 235 119.9611111111 34 0 0 190 10 0 1200 0 0 1200
89 22:00 Paris London 868 159 12,492 13 18% 159 78.5660377358 0 0 0 159 0 0 0 0 0 0
89 6:50 London Madrid 1484 180 20,909 16 250 116.1611111111 43 0 0 190 10 0 1162 0 0 1162
89 9:30 London Madrid 929 180 19,278 20 157 107.1 0 0 0 157 0 0 0 0 0 0
89 19:00 Madrid London 1346 180 25,714 2 227 142.8555555556 44 8 0 190 10 8 1429 1040 0 389
89 21:30 Madrid London 1211 148 15,740 12 12% 148 106.3513513514 0 0 0 148 0 0 0 0 0 0
89 7:10 London Berlin 1020 180 20,716 14 172 115.0888888889 2 0 0 172 0 0 0 0 0 0
89 9:15 London Berlin 1197 180 18,506 12 202 102.8111111111 0 0 0 190 10 0 1028 0 0 1028
89 18:30 Berlin London 1642 180 24,730 9 277 137.3888888889 31 1 0 190 10 1 1374 130 0 1244
89 20:30 Berlin London 876 162 13,004 13 18% 162 80.2716049383 0 0 0 162 0 0 0 0 0 0
89 6:30 London Brussels 1185 180 18,575 6 200 103.1944444444 61 4 0 190 10 4 1032 520 0 512
89 8:45 London Brussels 606 128 11,416 9 21% 128 89.1875 0 0 0 128 0 0 0 0 0 0
89 18:50 Brussels London 1968 180 22,703 22 332 126.1277777778 52 0 0 190 10 0 1261 0 0 1261
89 21:05 Brussels London 957 144 12,856 16 15% 144 89.2777777778 0 0 0 144 0 0 0 0 0 0
90 7:00 London Paris 1914 180 20,489 17 323 113.8277777778 73 0 0 190 10 0 1138 0 0 1138
90 10:15 London Paris 700 130 13,522 23 19% 130 104.0153846154 0 0 0 130 0 0 0 0 0 0
90 19:30 Paris London 1119 180 20,049 10 189 111.3833333333 43 0 0 189 9 0 957 0 0 957
90 22:00 Paris London 1221 153 12,554 16 13% 153 82.0522875817 0 0 0 153 0 0 0 0 0 0
90 6:50 London Madrid 1994 180 26,596 7 336 147.7555555556 28 3 0 190 10 3 1478 390 0 1088
90 9:30 London Madrid 629 174 14,549 22 28% 174 83.6149425287 0 0 0 174 0 0 0 0 0 0
90 19:00 Madrid London 1922 180 25,506 19 324 141.7 47 0 0 190 10 0 1417 0 0 1417
90 21:30 Madrid London 824 180 13,554 6 139 75.3 0 0 0 139 0 0 0 0 0 0
90 7:10 London Berlin 1547 180 22,504 6 261 125.0222222222 24 4 0 190 10 4 1250 520 0 730
90 9:15 London Berlin 937 169 17,035 13 18% 169 100.798816568 0 0 0 169 0 0 0 0 0 0
90 18:30 Berlin London 1513 180 22,975 26 255 127.6388888889 38 0 0 190 10 0 1276 0 0 1276
90 20:30 Berlin London 918 180 17,767 13 155 98.7055555556 0 0 0 155 0 0 0 0 0 0
90 6:30 London Brussels 1419 180 21,337 12 239 118.5388888889 96 0 0 190 10 0 1185 0 0 1185
90 8:45 London Brussels 672 105 7,586 21 16% 105 72.2476190476 0 0 0 105 0 0 0 0 0 0
90 18:50 Brussels London 1441 180 22,721 26 243 126.2277777778 31 0 0 190 10 0 1262 0 0 1262
90 21:05 Brussels London 1175 165 17,295 16 14% 165 104.8181818182 0 0 0 165 0 0 0 0 0 0
91 7:00 London Paris 1738 180 25,894 20 293 143.8555555556 3 0 0 190 10 0 1439 0 0 1439
91 10:15 London Paris 1107 180 20,257 10 187 112.5388888889 0 0 0 187 7 0 740 0 0 740
91 19:30 Paris London 1549 180 23,447 16 261 130.2611111111 17 0 0 190 10 0 1303 0 0 1303
91 22:00 Paris London 1293 177 13,990 14 14% 177 79.0395480226 0 0 0 177 0 0 0 0 0 0
91 6:50 London Madrid 1874 180 19,558 25 316 108.6555555556 45 0 0 190 10 0 1087 0 0 1087
91 9:30 London Madrid 989 143 12,077 8 14% 143 84.4545454545 0 0 0 143 0 0 0 0 0 0
91 19:00 Madrid London 1616 180 22,675 3 272 125.9722222222 40 7 0 190 10 7 1260 910 0 350
91 21:30 Madrid London 815 163 12,871 23 20% 163 78.963190184 0 0 0 163 0 0 0 0 0 0
91 7:10 London Berlin 1248 168 15,865 27 13% 168 94.4345238095 63 0 0 168 0 0 0 0 0 0
91 9:15 London Berlin 815 180 20,665 20 137 114.8055555556 0 0 0 137 0 0 0 0 0 0
91 18:30 Berlin London 1100 180 18,380 21 185 102.1111111111 49 0 0 185 5 0 551 0 0 551
91 20:30 Berlin London 1129 153 13,714 22 14% 153 89.6339869281 0 0 0 153 0 0 0 0 0 0
91 6:30 London Brussels 1015 180 24,198 6 171 134.4333333333 48 0 0 171 0 0 0 0 0 0
91 8:45 London Brussels 739 154 11,607 22 21% 154 75.3701298701 0 0 0 154 0 0 0 0 0 0
91 18:50 Brussels London 1889 180 21,013 19 318 116.7388888889 62 0 0 190 10 0 1167 0 0 1167
91 21:05 Brussels London 887 136 13,776 18 15% 136 101.2941176471 0 0 0 136 0 0 0 0 0 0

Quizes Examples/Charts in Depth exam.xlsx

Q13

2008 2009 2010 2011 2012 2013
North America 5,514,108 7,603,948 7,270,520 7,312,962 6,229,256 7,269,462
Europe 2,757,054 3,801,974 3,635,260 3,656,481 3,114,628 3,634,731
South America 2,122,932 2,965,540 2,581,035 2,486,407 2,304,825 2,762,396
Asia 1,213,104 1,977,026 2,181,156 1,901,370 1,868,777 2,108,144

Quizes Examples/Charts in Depth.docx

1. If all the data you want to chart is in one data range, how should you create the chart?

Insert a chart, then add each data series individually

Create a column chart, then decide if you should change to a different chart

Create a chart from the axis labels, then add the data points

Select the data, then insert the chart type you want

2. Which axis of a chart should time series data usually appear on?

Whichever axis Excel places it on

Vertical axis

Horizontal Axis

Either axis

3. How should data be arranged on a horizontal bar chart?

Largest to smallest from top to bottom

Smallest to largest from top to bottom

Largest to smallest from left to right

Smallest to largest from left to right

4. In a chart, the largest vertical axis label is '3,000,000', which represents a dollar amount. Which of these label options is the most preferable?

300k

$3m

$3,000,000

$300k

5. When are you most likely to need to format the horizontal axis?

When the axis has a large number of data points

When the axis is time based

When dealing with data about employees

When you are creating a bar chart

6. Which of these would not be a reason to change the color scheme of your charts?

To add a legend to your charts

To apply a consistent style to all of your charts

To match your company's color templates

To create a clearer color scheme than the Excel default

7. When can you safely remove the vertical axis of a chart?

When the chart has a small number of points

When the chart is a stacked column chart

When the horizontal axis is time based

When the chart is a line chart

8. Which of these is an advantage of using a vertical axis instead of data labels on a column chart?

A vertical axis makes it easier to view actual values from the chart

A vertical axis is easier to format than data labels

A vertical axis takes up less space on a chart

A vertical axis makes a chart with many values less cluttered

9. On which of these line charts are data labels not likely to work well?

A single line chart with 4 data points

A multiple line chart with 20 points on each line

A multiple line chart with 4 points on each line

A single line chart with 8 data points

10. What primary advantage do 100% stacked column charts hold over pie charts?

100% stacked column charts are better at visualizing larger data sets

Multiple 100% stacked column charts are much easier to compare visually than multiple pie-charts

100% stacked column charts are much easier to build

100% stacked column charts are much easier to format

11. Cell B2 has a value of 6%, representing annual growth projections. Which of these formulas correctly includes cell B2 in a chart title?

="Revenue projection for "&"B2"&" annual growth rate, $USD"

="Revenue projection for "&B2&" annual growth rate, $USD"

="Revenue projection for "&TEXT(B2,"0%")&" annual growth rate, $USD"

="Revenue projection for "&TEXT(B2","6%")&" annual growth rate, $USD"

12. When should your chart have a legend?

When you have multiple data series

When you have the space to add one

When your audience is unfamiliar with the data

When your chart doesn't include a data table

13. Consider the Excel sheet 'Q13'. Which chart should be used to display this data set?

Line chart

Stacked column chart

Horizontal bar chart

Clustered column chart

14. Which of these data sets should be plotted with a stacked column chart?

Daily oil prices for the last 3 years

Annual revenue and profit for the last 5 years

Annual revenue by region for the last 5 years

Total customers gained and lost by sales person in the last month

15. Which of these charts is a reasonable option for comparing actual revenue figures to target revenue figures over a period of several years?

Horizontal bar chart

Pie chart100% stacked column chart

Clustered column chart

16. Which of these is an issue that can arise when you copy and paste a chart from Excel to PowerPoint as a Microsoft object?

You cannot modify the chart in PowerPoint

If sharing the PowerPoint file, you must also distribute the Excel file

The chart in PowerPoint will not update if the data in Excel changes

You can only adjust the size of the chart in PowerPoint

Quizes Examples/Construct Charts for Your Data.docx

1. Which Microsoft application is used to edit the data in a PowerPoint chart?

Power BI

Excel

Outlook

Word

2. Which of these is the correct definition of data labels when applied to a column chart?

A label attached to each axis indicating the information on that axis

A label attached to each column indicating the numeric value of that column

A label attached to the chart containing the title for the chart

A label attached to the slide containing an insight from the chart

3. Which of these situations is most likely to justify the use of a clustered column chart?

Analyzing the price of a commodity over a long period of time

Analyzing the market share over time of several competitor companies

Analyzing revenue over time for a single company with several products

Analyzing revenue over time for several competitor companies

4. How should market share values be formatted in a PowerPoint chart?

As a whole number

As a decimal number

As a currency value

As a percentage

5. Which of these statements about copying and pasting charts from Excel to PowerPoint is false?

We can format the chart in PowerPoint as if the chart was created in PowerPoint

If we change the data in Excel, the chart in PowerPoint will update automatically

We can update the chart data in PowerPoint without affecting the data in Excel

If we delete the data in Excel, the chart in PowerPoint may be broken

6. Which of these situations would justify the use of a line chart?

You want to track the market share of several competitors over several years

You want to track revenue for several competitors over several years

You have a small number of data points tracking a single variable over time

You have a large number of data points tracking a single variable over time

7. Which of these actions would not make the x-axis labels on a line chart more readable?

Arranging the data labels vertically instead of horizontally

Changing the format of the labels from day-month-year to month-year

Reducing the number of labels on the x-axis

Adjusting the font size of the labels

8. What option in the Format Axis window determines the length of time between each label on the x-axis of an area chart?

Major Units

Minor Units

Minimum Bounds

Maximum Bounds

9. What is the main disadvantage of expanding the size of all the bubbles on a bubble chart?

The data labels may become too small to read

The bubbles may overlap with each other

The chart area may expand and become too large

The color of the bubbles may change

10. You are creating a bubble chart containing the variables market size, growth rate, and profit margin. Which variables should be placed on the x-axis and y-axis of this chart?

Any two variables

Market size and profit margin

Growth rate and market size

Growth rate and profit margin

11. Which of these charts is ideal for identifying data clusters?

Line chart

Bubble chart

X-Y scatter plot

Radar chart

12. Which of these techniques will increase the R-Squared value of the trendline on a scatter plot?

Adjusting the thickness of the trendline

Adding more variables to the trendline equation

Reducing the amount of data in the scatter plot

Swapping the x-axis and y-axis on the scatter plot

13. Which of these tools is generally necessary when combining two charts that have different values?

A chart title

Axis labels

Data labels

A secondary axis

14. Which of these situations would justify the use of a waterfall chart?

You want to track the growth and decline of a company's employee numbers over time

You want to analyze sales over time for various different product categories

You want to track the daily price of a commodity for a one year period

You want to compare annual revenue for several competitor companies over a five year period

15. Which of these methods of adding a baseline to a chart allows you to easily add a label to the baseline?

Adding a baseline by adding new data to the chart

Adding a baseline by drawing the line on the chart

Both of the above methods

Neither of the above methods

16. What is the main problem associated with radar charts?

It is difficult to compare segments that are similarly sized

They contain multiple axes that are difficult to compare

They contain 3D effects that are difficult to understand

It is not possible to change their color scheme in PowerPoint

Quizes Examples/Creating Business Presentations .docx

1. Which of these is a typical characteristic of a sit-down presentation?

Your presentation will contain little detail on the subject

Your slides should use a large font size

It is usually given to a large crowd

The audience will have seen a copy of your presentation beforehand

2. Which type of presentation would you create when presenting an overview of your company to a large group of recent hires?

Sit-down presentation

Stand-up presentation

Both of these options work

Neither of these options work

3. Which of these statements about creating a presentation using the pyramid principle is false?

You should place the main finding at the start of your presentation

Your presentation should address all the issues raised by your main finding

The interest level of the audience will be highest at the end of your presentation

The main challenge of the principle is identifying the issues that will be raised by your main finding

4. Which of these statements would work best as the top level of a pyramid?

What can our city do with this financial windfall

Our city has a large amount of money to spend

Where did we get this financial windfall from

We should invest our financial windfall in public transport infrastructure by building a monorail

5. What term is used to refer to a set of issues that cover every aspect of the relevant problem?

Collectively exhaustive

Collectively exclusive

Mutually exhaustive

Mutually exclusive

6. Which of these statements about building a MECE issue tree is true?

Domain and industry knowledge is equally important when creating every level of the tree

Domain and industry knowledge is particularly important when creating the lower levels of an issue tree

Domain and industry knowledge is particularly important when creating the higher levels of an issue tree

Domain and industry knowledge is not important when building an issue tree

7. Which of these is generally not a property of a dynamic table of contents?

It includes the full text of the executive summary

It appears before each section of the presentation

It includes each of the MECE issues covered in the presentation

It highlights the current section of the presentation

8. Which of these is the best example of an action title that could be added to a slide?

Several new products will be launched next year

Product roadmap and development costs

Product development costs will increase next year due to a 20% rise in labor costs

Product development costs will continue to rise in the future

9. Which of these situations would justify not using quantitative data to validate the action title of a slide?

Our analysis already includes some quantitative data

Our analysis only includes qualitative data

We are not confident of the accuracy of the quantitative data

The quantitative data comes from multiple different sources

10. Which of these statements about using a matrix to visualize qualitative information is false?

It can be used to compare three different dimensions of data

We should include Harvey balls as the circles on a matrix

It consists of a series of circles placed on a chart area

It can be used to visualize qualitative data

11. Which of these levels of uncertainty describes a market where there is so much uncertainty that it is impossible to predict future outcomes?

True ambiguity

A clear future

Alternative futures

A range of futures

12. Which of these strategic postures describes a company that plays a leadership role in prompting changes in the industry?

Shape the future

Adapt the fastest

Reserve right to play

Exit the market

13. Which of these should not be included on the cover page of a presentation?

Presentation title

Location

Date

Number of slides

14. Which of these situations is most likely to justify using a 4:3 aspect ratio when creating slides in PowerPoint?

You will be presenting the slides on a wide screen

You will be distributing the slides to a person using a recent version of PowerPoint

Your slides will be printed as a handout

Your presentation contains a large number of slides

15. How should you create the executive summary of a presentation?

Write a series of bullet points summarizing each of the MECE issues

Write one paragraph of text summarizing your main findings

Summarize the MECE issues, then insert a recommended course of action

Combine all the action titles of your slides in order

16. Which of these should be the main focus of the conclusion to a PowerPoint presentation?

A summary of the MECE issues you have considered

A recommendation based on your analysis

A discussion of factors that affected your analysis

A list of all the sources used in your analysis

Quizes Examples/Custom Templates for Your Business .docx

1. Which of these is the best definition of templates in PowerPoint?

A series of colors that can be used when creating PowerPoint slides

A series of layouts that can be used to create PowerPoint slides

A series of fonts that can be used when creating PowerPoint slides

A series of slides that can be added to PowerPoint presentations

2. How can you load a saved custom PowerPoint template to the current presentation?

Create a new template file containing the desired template and apply it to the presentation

Load the PowerPoint template file into the presentation

Create a new presentation that uses the desired template

Load a presentation that uses the desired template and modify that presentation

3. What view is used to edit the layouts in a template?

Outline view

Handout master view

Slide master view

Notes master view

4. Which of these situations would justify increasing the size of the title banner in your template?

Your slides generally contain very little text

Your slides generally contain a lot of text

Your presentation generally contains a small number of slides

Your presentation generally contains a large number of slides

5. What are RGB values used for when designing a color palette?

Indicating the number of colors on a slide

Defining the precise shade of a color

Defining the contrast of two different colors

Indicating the overall amount of color on a slide

6. Which of these is not a color type found in a PowerPoint color palette?

Border color

Accent color

Text/Background color

Hyperlink color

7. Which of these changes needs to be made outside the Slide Master view?

Adding a title banner to the template

Adjusting the color palette of a template

Creating a layout for charts

Changing the default shape formatting

8. Which of these situations is most likely if a company PowerPoint template has a default font size of 36 in text placeholders?

The company's PowerPoint presentations are generally presented to external clients

The company's PowerPoint presentations generally contain a large number of charts

The company's PowerPoint presentations are generally read like reports

The company's PowerPoint presentations are generally presented to large audiences

9. What happens when you add a large image to a smaller image placeholder?

The image is shrunk to fit the placeholder

The placeholder expands to be the same size as the image

The image is cropped to fit the placeholder

You will see an error message

10. How many slide layouts does PowerPoint automatically provide for each template?

351119

11. What combination of placeholders would be used to create a layout containing a chart and a title for the chart?

Table placeholder and content placeholder

Chart placeholder and content placeholder

Chart placeholder and text placeholder

Table placeholder and text placeholder

12. Which of these conditions must be met if we want to add a video that covers an entire slide?

The video and the slide must have different aspect ratios

The video and the slide must have the same aspect ratio

The media placeholder must be created before the slide is created

The media placeholder must be created after the slide is created

13. What is the best way to create a unique title slide design for a template?

Modify the existing title slide layout that comes with the template

Add a title slide to a presentation, then create a layout using that slide

Create a new layout in the Slide Master view and name it "Title Slide"

Create a second title slide layout then add the new layout to a presentation

14. Which of these statements about footers and page numbers in a template is true?

If a presentation includes page numbers, then the title page must include a page number as well

Footers and page numbers are included in all PowerPoint presentations by default

Placeholders for the footer and page number are included in the master slide by default

Any footer placeholders added to the master slide are automatically added to presentations using the template

15. Which of these cannot be included on handout pages when you are printing a PowerPoint presentation?

Page number

Presentation title

Header

Footer

16. Which of these is not a step you should take before saving a presentation as the default PowerPoint presentation?

Remove all content from the title slide except placeholders

Remove all slides from the presentation except the title slide

Ensure the presentation contains appropriate company branding

Remove all layouts from the template except the master slide

Quizes Examples/Developing and Visualizing Your Data Model exam.xlsx

Sheet1

Developing and Visualizing Your Data Model Exam

The data for this exam is in the Power Pivot data model. To access the data: • Ensure the Power Pivot add-in is enabled. • From the Power Pivot tab in the ribbon, select Manage Data Model.

Quizes Examples/Developing and Visualizing Your Data Model.docx

1. Which of these statements about dates in Power Pivot is false?

Date functions can only return dates that already appear in the data model

Date functions may return blank values if a date tables is not included in the model

Date tables can be created directly in Power Pivot

The data in your model must include every date between the earliest date and the latest date

2. Which of these is not a characteristic of date tables?

The date table can contain other columns containing more information about each date

The date table must be created in a separate Excel sheet

There are no gaps between the start and end date in the date table

Date tables should always be used when you want to conduct time intelligence analysis

3. In this exam's Excel file, each sale is confirmed in the company's accounts the day after it is recorded. What was the total revenue from transactions confirmed in this way on 27 March 2016? (Hint: Use the NEXTDAY function to find the date each transaction is confirmed.)

4. In this exam's Excel file, create a hierarchy called Geography, containing the fields region, sub-region and state. How many regions had at least one sub-region which generated at least $4 million of revenue?

5. In this exam's Excel file, what percentage of states in the East North Central sub-region of the Midwest region had over 20,000 users?

6. In this exam's Excel file, sort the Month Name column by the Month column. What was the latest month of the year where revenue was above $2,000,000?

May

July

September

November

7. In this exam's Excel file, create a KPI comparing actual revenue to target revenue. Set the low threshold to 90%, and the high threshold to 110%. How many sales people had revenue more than 10% above their target?

8. Which of these is not a property of a Key Performance Indicator that can be adjusted in Power Pivot?

The measure to be used as the target value

The thresholds that define each output for the visual indicator

The colors used in the visual indicator

The icons to be used as part of the visual indicator

9. What will happen if we right click a table header in Diagram View, and select the option Hide from Client Tools?

The table will no longer be visible in the Field List in Excel when we are creating a Pivot Table

The table will be at the bottom of the Field List in Excel when we are creating a Pivot Table

The table will appear to have no columns in the Field List in Excel when we are creating a Pivot Table

The table will be at the top of the Field List in Excel when we are creating a Pivot Table

10. Which of these is not a data type in Power Pivot?

Scientific

Text

Decimal Number

Currency

11. Which of these is a possible issue that can arise when changing a column from a decimal number to a currency?

Any information in the number beyond two decimal places will be lost

Thousand separators may be removed from the number

We will not be able to adjust which currency is used

This change cannot be reversed using the undo button

12. Which of these areas in the layer pane of 3D Maps is used to indicate the geographic areas that we want to map?

Time

Category

Height

Location

13. In this exam's Excel file, create a 3D Maps bar chart showing revenue by state. What is the total revenue for Florida (FL)? (Hint if needed: Florida is in the Southeast corner of the country.)

14. In this exam's Excel file, create a 3D Maps bar chart showing revenue by state for the Mountain sub-region only. Which state in this sub-region has the highest Revenue?

Montana (MT)

Arizona (AZ)

Idaho (ID

)Nevada (NV)

15. In this exam's Excel file, which of these 3D Maps has the highest mapping confidence percentage? (Note: Remove any filters before creating the maps.)

A heat map of revenue by state, city, and street

A heat map of revenue by city

A heat map of revenue by Zip code

A heat map of revenue by state and city

16. Which of these settings cannot be modified when saving a video of a 3D Maps tour?

Quality settings for the video

File type of the video

Soundtrack for the video

File name of the video

Quizes Examples/Finance Functions .docx

1. In the 'Investment' Excel sheet, calculate the discounted cash flows for Project A in Year 3.

2. In the 'Investment' Excel sheet, calculate the Internal Rate of Return (IRR) for Project A.

3. In the 'Investment' Excel sheet, calculate the Net Present Value (NPV) for Project A.

4. In the 'Investment' Excel sheet, calculate the Internal Rate of Return (IRR) for Project B.

5. In the 'Investment' Excel sheet, calculate the Net Present Value (NPV) for Project B.

6. In the 'Loan calculations' Excel sheet, calculate the annual repayment amount for the 15-year loan. Please ensure you enter your answer as a positive number.

7. In the 'Loan calculations' Excel sheet, calculate the interest paid on the loan in Year 5. Please ensure you enter your answer as a positive number.

8. In the 'Loan calculations' Excel sheet, calculate the principal paid back during Year 13. Please ensure you enter your answer as a positive number.

9. In the 'CAGR' Excel sheet, calculate the compound annual growth rate of revenue over the previous 6 years.

10. What is the payback period in years for Project 1 shown in the 'Payback Period’ sheet' in the Excel file?

11. What is the payback period in years for Project 2 shown in the 'Payback Period’ sheet' in the Excel file?

12. Which project would you choose - Project 1 or Project 2?

Project

1Project 2

Quizes Examples/Finance Functions exam.xlsx

Investment

Project A - NPV and IRR Project B - XNPV and XIRR
The table below shows the cashflow profile for a small investment opportunity. Calculate the Net Present Value and Internal Rate of Return of this investment. Assume a discount rate of 12%. The table below shows the cashflow profile for a small investment opportunity. Calculate the Net Present Value and Internal Rate of Return of this investment. Assume a discount rate of 12%.
Year # 0 1 2 3 4 5 Date 4/23/11 5/20/12 3/22/13 4/15/14 5/11/15 4/29/16
Cashflow $ -25,000 $ 6,000 $ 6,000 $ 8,000 $ 8,500 $ 12,000 Cashflow $ -20,000 $ 6,000 $ 5,000 $ 4,500 $ 7,000 $ 7,500
Discounted cashflows Discounted cashflows
Discounted cashflows in Year 3 Internal Rate of Return
Internal Rate of Return Net Present Value
Net Present Value

Loan calculations

Amortising loan repayments
The table belows shows the detail for a 15-year loan. Answer the 3 questions in the blue cells. Note: Answers should be negative.
Loan Amount $ 450,000
Interest rate 4.80%
Loan term (in years) 15
Calculate the annual repayment amount
Calculate the interest paid in Year 5
Calculate the principal paid back during Year 13

CAGR

The table below shows a company's annual revenue for the last 6 years. Find the compound annual growth rate (CAGR) for this company.
Year # 2010 2011 2012 2013 2014 2015
Annual revenue $ 3,000 $ 4,500 $ 6,000 $ 7,500 $ 10,500 $ 11,000
Calculate CAGR

Payback Period

Year # 0 1 2 3 4 5 6
Project 1 -$15,000 $6,000 $5,000 $5,500 $7,000 $3,500 $3,400
Project 2 -$15,000 $4,000 $6,000 $4,500 $5,000 $6,450 $9,000
IRR for Project 1 27.22%
IRR for Project 2 27.23%
Payback period for Project 1
Payback period for Project 2

Quizes Examples/Forward-Looking Models exam.xlsx

Model

2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026
Reference plant
Reference plant cost -14,500,000 - - - - - - - - - - - -
Commercial plant
Commercial plant cost - - -230,000,000 - - - - - - - - - -
Operating cashflows
Revenue - - - 566,000,000 566,000,000 566,000,000 566,000,000 566,000,000 566,000,000 566,000,000 - - -
Production cost - - - -360,000,000 -360,000,000 -360,000,000 -360,000,000 -360,000,000 -360,000,000 -360,000,000 - -
Depreciation - - - -46,000,000 -46,000,000 -46,000,000 -46,000,000 -46,000,000 - - - - -
Taxable income - - - 160,000,000 160,000,000 160,000,000 160,000,000 160,000,000 206,000,000 206,000,000 - - -
Taxes paid - - - -56,000,000 -56,000,000 -56,000,000 -56,000,000 -56,000,000 -72,100,000 -72,100,000 - - -
Annual cashflows -14,500,000 - -230,000,000 150,000,000 150,000,000 150,000,000 150,000,000 150,000,000 133,900,000 133,900,000 - - -
Risk weighted cashflows

Control panel

Blue indicates hard-coded numbers or inputs
Black indicates formulas or text
Green indicates links from other worksheets
Inputs (Parameters) Select scenario Base Outcome
Reference plant cost Pessimistic Base Optimistic Live Project cashflows - 0
Reference plant cost $ -19,500,000 $ -14,500,000 $ -11,500,000 $ -14,500,000
Ref plant start 2014 2014 2014 2014 Return on investment - 0
Ref plant duration 2 2 2 2
Success Probability 13% 16% 18% 16% Decision NO
Commercial plant
Commmercial plant cost $ -280,000,000 $ -230,000,000 $ -190,000,000 $ -230,000,000
Market price, $/gallon $ 2.55 $ 2.83 $ 3.05 $ 2.83
Capacity, gallons 200,000,000 200,000,000 200,000,000 200,000,000
Operating life, years 6 7 8 7
Construction duration, years 1 1 1 1
Unit variable cost, $/gallon $ -2.00 $ -1.80 $ -1.65 $ -1.80
Depreciation, years 5 5 5 5
Tax rate 35% 35% 35% 35%
Target time duration, years 10 10 10 10
Target return 5.00 5.00 5.00 5.00
Intermediate variables
Operation start year 2017
Operation end year 2024

Quizes Examples/Forward-Looking Models.docx

1. What shape is used to represent a decision node in a decision tree?

Rectangle

Triangle

Octagon

Circle

2. You are preparing for an exam using a new study method. If the method works, you expect to score 95 on the exam. If it does not work, you expect to score 80. Research suggests the method has a 60% chance of working. What is the expected value of your grade on the exam?

3. You need to take an exam which costs $100. You can also take an optional preparation course for the exam which costs $150. If you take the course, you will definitely pass the exam. If you do not take the course, there is a 50% chance you will pass the exam and a 50% chance you will fail. If you fail, you must take the course and then pay to take the exam for a second time. Using a decision tree to analyze the problem, what is the expected cost of not taking the course?

4. Where should changes to model inputs be made if you want to create a responsive Excel model?

In the control panel

In the data set

In the model

In the cover sheet

5. In the 'Model' sheet of this exam's Excel file, calculate the risk-weighted cash flows using the success probability in the 'Control panel' sheet. (Hint: the cash flow in the year that the reference plant is built is not subject to the success probability.) What is the risk-weighted cash flow for 2022?

6. Which of these tasks would a tornado chart be used for?

Analyzing which scenario produces the highest output values

Auditing formulas and identifying formula errors

Incorporating taxes and depreciation into a model

Identifying which variables have the greatest impact on the model output

7. Which of these is a weakness of a tornado chart?

It can only show a single model parameter at any time

It does not consider the time value of money

It can be difficult to format it correctly

The chart may need to be updated manually when you adjust the model

8. Based on the data in the 'Control panel' sheet of this exam's data file, which of the following variables has the biggest positive impact on Return on Investment if decreased by 10% in the base scenario?

Variable cost

Reference plant cost

Probability of success

Market price

9. Which of these statements about the data in the 'Model' sheet of this exam's Excel file is true?

Taxable income is lower in 2022 than in 2017

The commercial plant is depreciated over a period of 7 years

The model uses the straight line method of depreciation

Taxes paid are higher in the years which have a depreciation expense

10. What is the INDEX function used for when creating a Live column that is linked to multiple scenarios?

Identifying the scenario to be used in the Live column

Identifying the correct row to be used in the Live scenario

Combining the correct row and column together to return the correct value

Assigning a name to the different scenarios

11. In the 'Control Panel' sheet of this exam's Excel file, link the live column to the three scenarios shown. What is the difference in project cash flows between the optimistic and base scenarios?

12. In this exam's Excel file, which of the following variables causes the smallest increase of Return on investment when changed from its base value to its optimistic value?

Variable cost

Reference plant cost

Probability of success

Market price

13. Which of these best describes how the Colorize Formulas feature of the XLTest plugin works?

It colors the background of cells based on the formulas in those cells

It colors the text in cells based on the results from their formulas

It colors the text in cells based on the formulas in those cells

It colors the background of cells based on the results from their formulas

14. Which of these tools allows you to restrict the allowed values in a cell?

Remove duplicates

Data validation

What-if analysis

Data tables

15. Which of the following model input fields would be most likely to require a restriction in an Excel model?

Reference plant cost (e.g. 100,000)Unit variable cost (e.g. $1.80)Construction duration (e.g. 1 year)Tax rate (e.g. 21%)

16. Which of these is not a weakness of the model in this exam's Excel file?

It does not consider the time value of money

It does not consider cash flows that could occur after the target time to return the initial investment

It assumes that inputs such as the market price will vary throughout the time period of the model

It does not consider the possibility of the plant operating more efficiently in future years

Quizes Examples/Introducing Statistics .docx

1. Calculate the average debtor days for all clients.

2. Clients with over $5,000 of revenue are considered large clients. Calculate the average debtor days for large clients.

3. Compare the average debtor days for all clients to the average debtor days for large clients (clients with greater than $5,000 revenue). Which of these statements is true?

Larger clients pay much sooner than the average

Larger clients pay much later than the average

Larger clients pay about the same as the average

4. Calculate the average revenue for all clients.

5. What is the median revenue for all clients?

6. Which of these statements is true regarding the company's client base? (Hint: compare average and median revenue figures)

The company has a small number of very large clients

The company's client base is evenly spread

The company has a small number of very small clients

The company has a large number of very large clients

7. What is the mode of the debtor days column for all clients?

8. What is the 25th percentile for revenue?

9. Calculate the revenue percentile rank for Soar Airlines.

10. Divide the debtor days data into bins with a size of 50. Which bin contains the highest frequency?

100 to 150

150 to 200

200 to 250

250 to 300

11. Find the number of companies with debtor days between 150 and 200.

12. What is the variance of debtor days?

13. What is the standard deviation for revenue?

14. Create a Green-Yellow-Red color scale for the revenue column. What color is the revenue figure for Onion Pacific Railroad?

Green

Yellow

Red

15. What is the correlation coefficient between revenue and debtor days?

16. What is indicated by a correlation coefficient of 0.03?

Weak positive correlation exists

Strong positive correlation exists

Strong negative correlation exists

Almost no correlation exists

Quizes Examples/Introducing Statistics exam.xlsx

debtor_days

Client Debtor Days Revenue
Onion Pacific Railroad 0 1468.64
Big Belly Burger 0 2287.32
Zorin Industries 0 10269.99
Ipsum Dolor LLC 3 442.57
Sed Molestie Sed Incorporated 3 440.80
Virtucon 4 40632.67
Demo Company 4 56.84
Sed Industries 6 1365.50
Cyberdyne Systems 7 4632.19
PediaCorp 7 91.67
Soar Airlines 7 209.09
St. Anky Beer 8 1585.92
Urna Ut Tincidunt Company 9 419.43
Ante Vivamus Institute 11 4075.14
Brown Streak Railroad 11 54.60
Blue Sun Corporation 11 624.80
Roboto Industries 11 931.20
Duis Limited 12 17749.87
Egestas Foundation 14 2036.00
Nascetur Ridiculus PC 16 90.67
A Tortor Nunc Foundation 17 138.81
Arlesdale Railway 17 4627.93
Phasellus Vitae Mauris Institute 18 1294.80
Iaculis Quis Corporation 19 863.10
Diam At Corporation 21 5912.59
Ipsum Corporation 21 1880.99
Omni Consumer Products 22 69344.23
Lacus Quisque PC 22 2821.95
Sample Company 25 4923.52
Quantum Airlines 25 1650.96
Senectus Consulting 26 156.00
Nam Ligula Consulting 26 744.10
Ut Incorporated 27 74.10
North Western Railway 28 32.76
Nec Leo Associates 29 10399.03
Incom Corporation 30 2887.24
Purus Sapien LLP 31 2048.96
Neque Incorporated 32 1524.03
Egestas Institute 33 2718.98
Et Inc. 34 1000.13
Natoque Penatibus Company 35 14391.46
Semper Et Lacinia Corporation 35 3244.75
Monarch Playing Card Co. 35 108.00
Justo Company 38 5532.64
Water and Power 39 766.48
Sample Inc. 39 1435.84
Gravida Foundation 40 9119.20
Lacinia Vitae Sodales Associates 40 11781.85
Sagittis Augue Eu Ltd 41 509.32
Sombra Corporation 43 5457.34
Purus Corporation 44 1236.90
Spade and Archer 46 3758.29
Initech 47 4153.63
Dis Consulting 48 94.50
Parrish Communications 48 1114.12
Global Airways 49 336.30
Globo Gym American Corp 50 95.00
Petrox Oil Company 50 12321.01
Colonial Movers 51 608.90
Trans Allied Airlines 52 6936.93
Sem LLP 53 442.00
XYZ Corp 53 4622.14
Nibh PC 54 1450.40
Southern Railway of Northern Ireland 56 1734.48
Aliquam Adipiscing Company 58 49.05
Trans Regional Airlines 59 2925.52
KrebStar 60 26.13
Judgment Six 64 18145.79
Sapien Incorporated 67 13410.06
Ut Limited 68 1276.13
Mainway Toys 69 12472.74
Fake Brothers 70 5185.84
Eu Institute 73 86448.62
Eget Ipsum Consulting 74 13340.44
Primatech Paper Co. 75 1891.96
Contoso Corporation 75 77.14
Rossum Corporation 77 654.96
Sudden Pacific Railroad 77 222.75
Uplink Corporation 78 2118.50
Vel Turpis PC 79 557.46
Mainco 79 849.60
Egestas Blandit Foundation 79 504.63
BLAND Corporation 81 299.00
Thatherton Fuels 81 1853.67
Carrys Candles 82 1724.41
TetraCorp 82 1334.00
Tip Top Cafe 82 3241.58
Gadgetron 83 139.44
Nordyne Defense Dynamics 85 102.88
Donec Incorporated 86 262.38
Trans Continental Airlines 86 240.87
Accumsan Neque Et Inc. 86 704.00
Edgars Industries 87 1018.77
Minco 88 1252.34
Eget Ipsum Limited 89 361.85
Iaculis Lacus Pede Limited 89 12153.26
Quark Industries 89 120.75
The Dot Grill 89 212.40
Sto Plains Holdings 90 5049.64
Vitae Company 91 4965.11
Data Systems 92 364.99
Lectus Ltd 92 43.32
Energy Corporation 92 2968.82
Blammo Corp 93 217.98
Lacinia Vitae Sodales LLP 95 1546.89
Wayne Enterprises 96 355.18
Aliquam Rutrum Lorem LLC 99 943.50
CC Corporation 100 257.55
Sed LLP 100 1150.39
Shinra Electric Power Company 101 445.44
Matsumura Fishworks 102 21623.02
Charles Townsend Agency 102 246.79
Caliban Industries 104 354.25
Wernham Hogg 104 652.65
Pede Ac Urna Corporation 106 4721.10
QuantCo 107 9255.76
Massive Dynamic 107 9189.31
Flowers By Irene 107 732.94
Nulla Corp. 107 3198.72
Urna PC 108 133.65
Federation World Airlines 108 2098.53
Axis Chemical Co. 109 8938.56
Allied Biscuit 110 3881.66
McMahon and Tate 110 1465.52
Eu Placerat LLC 112 5373.24
Proin Incorporated 112 92.40
Vandelay Industries 112 29852.80
Donec Porttitor Company 113 9135.42
Arcu Ltd 114 52.29
North Central Positronics 114 12747.90
Aliquam Auctor Velit Incorporated 115 277.42
Big T Burgers and Fries 115 14.01
Zorg Industries 117 3870.86
Sed Malesuada Augue Corp. 118 2533.65
Laoreet Posuere Associates 120 40.13
Atlantic Corporation 121 3554.27
VersaLife Corporation 124 281.40
General Products 127 456.00
Ut Mi Duis Corporation 129 1780.51
Praxis Corporation 129 24996.04
Non Justo Proin Industries 129 104.16
General Forge and Foundry 129 8526.48
Nunc Inc. 129 116.64
Plow King 129 758.06
Universal Exports 131 1418.92
Demo Inc. 131 2841.30
Oceanic Airlines 132 1692.64
Trans Pacific Airlines 133 278.92
Extensive Enterprise 133 5506.95
Sonky Rubber Goods 133 47.23
Roxxon 134 22.66
Springfield Nuclear Power Plant 134 329.28
Northern & Southern Railway 134 120.15
TranCon Airways 136 69.00
OmniCo 137 3765.62
Ajax Corporation 137 43.33
Semper Cursus Integer Corp. 137 1637.74
Gizmonic Institute 138 1358.00
Bibendum Ullamcorper Duis Inc. 141 7438.92
Enim Sit Limited 141 9685.17
Consequat Ltd 141 135.20
Osato Chemicals 143 6621.40
Wallaby Airlines 143 3663.07
NorthAm Robotics 144 539.84
QWERTY Logistics 145 126.63
Lorem Company 145 22090.14
Suscipit Nonummy Limited 145 5102.08
Zevo Toys 148 2744.56
The Hanso Foundation 148 127.68
Arcu Curabitur Ut LLC 150 5023.20
The New Firm 151 2704.24
Duis Inc. 151 9818.85
Sit Amet Incorporated 151 5608.87
Mattis Semper Foundation 154 925.94
Chez Quis 154 860.74
MARS Industries 154 213.33
Malesuada Fames Ltd 154 2567.61
Tempor Lorem Eget Industries 154 859.01
Trans United Airways 156 1700.16
Videlectrix 157 1541.56
Megadodo Publications 157 2389.94
Fabrikam Corporation 157 9962.83
InGen Corporation 158 783.00
ZiffCorp 159 53.35
Feugiat Non Lobortis Ltd 159 1077.93
Donec Porttitor Tellus Institute 160 29706.24
Rouster and Sideways 160 169.92
Primatech 163 5128.00
Faucibus Consulting 163 1009.79
Cursus Nunc Company 163 7761.60
Proin Foundation 164 176.75
Mammoth Pictures 164 1044.00
Stark Industries 165 587.10
Vestibulum Ltd 165 3493.15
Varius Industries 165 634.86
Buy and Large Corporation 166 13552.58
Biffco 167 1581.10
Varius Orci In LLC 169 351.50
Canada World Airways 171 420.24
Phasellus Corporation 171 1108.80
Maecenas Malesuada PC 171 1292.00
Ankh-Sto Associates 172 29190.15
Erat Eget PC 172 6187.93
Foo Bars 173 11463.66
United Robotronics 175 1122.24
Initrode 176 109.87
Slate Rock and Gravel Company 176 40.18
Sit Amet Nulla Company 177 10883.37
Trans Global Airlines 177 2887.29
Suspendisse Institute 178 5267.58
TriOptimum Corporation 179 1156.85
Atlantic Northern 180 2440.04
Western Gas & Electric 181 41.04
Rutrum Eu Ultrices Corporation 182 2594.43
The Drunken Clam 184 286.65
Amet Incorporated 184 721.88
Iaculis Quis Industries 184 145.99
Blarg Factory 184 6620.25
Input Inc. 187 1519.67
Vel Arcu Institute 187 3568.87
ABC Corp 189 5685.33
Powell Motors 189 1949.01
LexCorp 190 26346.04
ABC Telecom 191 38.40
Globex Corporation 192 147599.56
Gringotts 193 69854.52
Crudgington Brewery 193 2611.76
Industrial Automation 193 123.36
Tessier-Ashpool 193 526.52
Atlantic International Airlines 194 63.00
Acme Corp 195 1652.22
Hishii Industries 195 90.25
Fringilla Porttitor Vulputate Consulting 195 4173.56
Erat Eget Corporation 196 126.10
Kumatsu Motors 196 1195.11
Augue Limited 201 9526.97
Bluth Company 201 19210.80
Transworld Consortium 204 789.12
The Queen Victoria 204 392.98
Jupiter Mining Corporation 205 8153.17
Ewing Oil 206 3365.32
Dignissim Lacus Consulting 207 252.00
Benthic Petroleum 207 116.96
Lobortis Mauris Company 208 308.20
Trans American Airlines 208 117.45
C.H. Lavatory and Sons 210 2510.98
Nibh Sit Corporation 210 6316.80
Global Dynamics 211 4525.54
Euismod Urna Inc. 212 7337.46
Imperdiet Ullamcorper Duis LLP 212 1338.33
Sixty Second Avenue 212 69.55
Sheinhardt Wig Company 213 2690.56
London and West Coast Railway 213 388.06
Umbrella Corporation 213 6339.20
Dui Incorporated 214 251.92
Paradise Airlines 214 126.00
Purus LLP 216 200.38
Union Aerospace Corporation 217 568.00
Galaxy Corp 219 227.36
Ante Lectus Convallis Ltd 220 204.25
Diam Sed Company 220 128.09
Lectus Pede Associates 222 16353.93
United Fried Chicken 223 653.38
Orci LLC 223 2369.01
Cathedral Software 226 347.62
Eros Associates 227 1678.10
Klimpys 227 1705.99
Sirius Cybernetics Corporation 228 4120.09
Mauris A LLP 228 90.09
Three Waters 228 2748.60
Congue Elit Sed Corporation 228 76.00
Amet Consectetuer Ltd 229 1819.12
Pede Cum Sociis LLP 231 162.02
Monks Diner 231 77249.92
Barrytron 232 419.30
Nibh Sit PC 232 14726.25
Ace Tomato Company 232 1305.87
Faucibus Corporation 233 1518.64
Queen Industries 234 794.50
Purus Nullam Scelerisque Industries 235 1288.90
Columbia Airlines 235 18.96
Smith and Co. 235 288.00
Phasellus In Corp. 237 1740.59
Sit Amet Corporation 237 1383.80
Neque Nullam Nisl LLP 239 52.50
Trade Federation 241 9958.78
Milliways 243 9209.16
Sem Inc. 243 12604.88
Curious Goods 243 3824.52
Elit Industries 249 547.52
Egestas Sed Company 250 76.47
123 Warehousing 250 89.60
Mishima Zaibatsu 251 1011.06
Morbi Vehicula LLP 251 2601.10
Bad Wolf Corporation 252 688.95
Amet Massa Quisque Company 254 2687.94
Gravida Incorporated 255 782.71
Rutrum Magna LLC 258 78534.43
Scelerisque Neque Sed Ltd 259 203.84
SpringShield 260 3804.36
Globo-Chem 263 2098.93
Elit Pede LLC 263 12965.12
General Services Corporation 265 255.20
Accumsan Neque LLP 266 1013.84
Leeding Engines Ltd. 266 993.93
Enim Corporation 269 576.00
The Lanford Lunch Box 271 556.60
Maecenas Libero Inc. 271 1154.30
Culdee Fell Railway 273 1037.87
Minuteman Cafe 281 1599.36
Keedsler Motors 282 3543.60
Ipsum Phasellus Limited 284 25.20
Phasellus In Incorporated 284 1327.02
Ornare Libero At Industries 284 4257.70
U.S. Robotics and Mechanical Men 290 158.40
Conubia Nostra Per Associates 292 2692.33
Thrift Bank 295 2118.39
Vulputate Corporation 297 1981.21

Quizes Examples/Introduction to Excel Macros .docx

1. What tasks are recorded macros typically used for?

Creating dynamic algorithms and complex statistical models

Automating repetitive tasks (e.g. cell formatting)

Data import and export

Creating graphical user interfaces for other users

2. What happens when you record a macro?

Excel records the screen and stores the actions for repeated use

Underlying code is written that represents the actions taken during the recording

Excel records the user's action and uses this information to make suggestions for future actions

Excel does not make this information known

3. Using the 'Q3' sheet in this exam's Excel file, create a macro that automatically adds a border, changes the background fill color and changes the number format to currency in the selected cell. Which of the following lines of code does not appear in your macro?

.LineStyle = xlContinuous

Selection.NumberFormat = "$#,##0.00"

.Pattern = Solid.

PatternTintAndShade = 0

4. Using the 'Q4' sheet in this exam's Excel file, create a macro which merges and centers a number of pre-selected horizontal cells. Which of the following lines of code does not appear in your macro?

.AddIndent = False.

HorizontalAlignment = xlCenter

.MergeCells = False.

LineStyle = xlContinuous

5. Where are macros stored in Excel?

They are stored in the cloud

They are stored only in the Excel file itself

They are stored only in a local file called Personal.xlsb

They can be stored in two locations, within the Excel file or in Personal.xlsb

6. Which of these is a weakness of macros?

You cannot undo a macro once it has been run

You cannot distribute macros easily in Excel

You cannot edit macros once they have been recorded

It can be difficult to delete macros

7. Which of the following is the safest way to receive a macro from a colleague?

Share via the cloud

Accept a file with a .xlsm extension

Accept a version of the Personal.xlsb file from your colleague

Copy and paste the underlying code of the macro into your current Excel sheet

8. Which of the macro security settings is recommended in this course?

Disable all macros without notification

Disable all macros with notification

Disable all macros except digitally signed macros

Enable all macros

9. You have a macro that applies formatting to the selected cell. Which of these changes can be made to the macro without editing the VBA code or re-recording the macro?

Renaming the macro

Changing the macro's keyboard shortcut

Adding an additional formatting task (e.g. adding a cell border)

Modifying a task in the macro (e.g. making text bold instead of italics)

10. When will you be unable to delete a macro using the Delete button in the macros window?

When the macro is saved in a macro-enabled workbook

When the macro uses absolute references

When the macro is saved to the Personal.xlsb file

When the macro uses relative references

11. What is the easiest way to select only the blank cells within a pre-selected column?

Create a formula that combines an IF function and the ISBLANK() function

Select the Special option from the Go To dialog box and click on 'Blanks'

Create a formula that combines an IF function and the ISNULL() function

Create a formula that combines an IF function and the ZN() function

12. Using the 'Q12' sheet in this exam's Excel file, create a macro which removes blank rows from a selected range of cells. Cells should be shifted up when blank rows are deleted. Which of these lines of code appears in the macro?

Selection.Shift:=xlUp

Selection.Shift xlUp

Selection.Delete Shift:=xlUp

Selection.Delete.Shift xlUp

13. In which of these situations would you always want to use relative references in a macro?

When applying a macro to multiple cells at the same time

When the macro accesses cells outside the selected cells

Only when the macro accesses cells in a separate sheet

When dealing with cell comments

14. What type of reference is used in the following line of code: 'Range("B2").Select'?

Absolute references

Relative references

Both absolute and relative references are used

Neither absolute or relative references are used

15. Using the 'Q15' sheet in this exam's Excel file, create a macro which removes comments from a pre-selected range of cells. (Hint: Right click a cell and select Delete Comments to remove the comments.) Which of the following lines of code appears in the macro?

Selection.ClearComments

Selection.SpecialCells(xlCelltTypeComments).Select

With Selection.Interior

With Selection.Exterior

16. Explain the following command: 'ActiveCell.Offset(0,2).Value = cellComment'

Insert value of the variable cellComment two columns from the ActiveCell

Insert value of the variable cellComment two rows from the ActiveCell

Insert the text string "cellComment" two rows from the ActiveCell

Insert the text string "cellComment" two columns from the ActiveCell

Quizes Examples/Introduction to Excel Macros exam.xlsx

Q3

Question 3
Use some of these cells to create a formatting macro.
1500 0.24
665 0.67
1453 0.11
112358 0.246
314159 0.248
113 0.97
893 0.47

Q4

Question 4
Use these cells to create a merge and center macro.
Table column headers
Table row headers

Q12

Question 12
Customer List
Crudgington Brewery
Culdee Fell Railway
Edgars Industries
Blue Sun Corporation
Bad Wolf Corporation
Blammo Corp
Trade Federation
Ankh-Sto Associates
Quark Industries
Water and Power
InGen Corporation
United Robotronics
Sixty Second Avenue
Petrox Oil Company
Atlantic Northern
Klimpys
Globex Corporation
Union Aerospace Corporation
Three Waters
Columbia Airlines
Extensive Enterprise
TriOptimum Corporation

Q15

Question 15
Customer
Crudgington Brewery
Aidan: Super customer!
Culdee Fell Railway
Aidan: Does not pay on time.
Edgars Industries
Aidan: Large customer we can't lose
Blue Sun Corporation
Aidan: Super customer!
Bad Wolf Corporation
Aidan: Super customer!
Blammo Corp
Aidan: Low maintenance customer
Trade Federation
Aidan: Always comes to annual conferences.
Ankh-Sto Associates
Aidan: Given discount due to long-term relationship.
Quark Industries
Aidan: Always pays on time.
Water and Power
Aidan: Very reliable.
InGen Corporation
Aidan: Very reliable
United Robotronics
Aidan: Special discount due to large size
Sixty Second Avenue
Aidan: Growing customer - expect more users.
Petrox Oil Company
Aidan: Big advocate for products and services in the South.
Atlantic Northern
Aidan: Great for referrals.
Klimpys
Aidan: Always pays on time.
Globex Corporation
Aidan: Does not pay on time.
Union Aerospace Corporation
Aidan: Super customer!
Three Waters
Aidan: Low maintenance customer
Columbia Airlines
Aidan: Does not pay on time.
Extensive Enterprise
Aidan: Large invoice outstanding
TriOptimum Corporation
Aidan: Great for referrals.

Quizes Examples/Introduction to Valuation .docx

1. Which of these describes the principle of the time value of money?

Money is worth more the later it is received

The value of an amount of money rises and falls over time

An amount of money received today is worth more than the same amount received in the future

An amount of money received in the future has greater earning power than the same amount would have today

2. What is the present value of the cash flows in the 'Present Value' sheet of this exam's Excel file?

3. If the discount rate in the 'Present Value' sheet of this exam's Excel file increases from 8% to 12%, what is the decrease in the present value of the cash flows?

4. What is the Net Present Value of the cash flows shown in the 'NPV and IRR' sheet of this exam's Excel file?

5. What is the Internal Rate of Return for the cash flows in the 'NPV and IRR' sheet of this exam's Excel file?

6. You are considering using NPV or IRR to make a choice between several possible investments. What investments are more likely to be recommended if you use NPV to make a decision?

Investments that return a high monetary amount

Investments which deliver returns over a longer period of time

Investments which have more volatile returns

Investments that have high returns relative to the initial investment

7. What is the annual loan repayment amount for the project shown in the 'Loan Investment' sheet in this exam's Excel file? (Note: Enter your answer as a positive number)

8. What is the total of the interest payments from year 1 to year 10 of the loan in the 'Loan Investment' sheet in this exam's Excel file? (Note: Enter your answer as a positive number)

9. What are the total earnings before tax over the life of the project detailed in the 'Loan Investment' sheet in this exam's Excel file?

10. What are the total annual cash flows received from year 1 to year 10 of the project detailed in the 'Loan Investment' sheet in this exam's Excel file?

11. What is the Net Present Value for the project in the 'Loan Investment' sheet of this exam's Excel file?

12. The investment project on the 'Terminal Value' sheet has a stable growth rate of 3% after Year 6. Based on the terminal value method, what is the Net Present Value of this project?

13. In the 'Terminal Value' sheet of this exam's Excel file, what percentage of the Net Present Value for the investment is accounted for by the terminal value?

14. Which of these factors has the greatest effect on a company's price/earnings multiple?

The industry the company operates in

The company's future growth prospects

The current size of the company

The most recent annual sales for the company

15. Which of these is not good practice when calculating multiples?

Exclude loan interest repayments from the multiple

Exclude one-off revenues and costs

Use historical data, not future estimates

Avoid valuing large diversified companies as a single entity

16. Which of these statements about tangible and intangible assets is false?

It can be difficult for competitors to replicate intangible assets

When a company is being liquidated, its entire value comes from tangible assets

Intangible assets can often be a company's most valuable assets

Cost-based valuation is most commonly used to value intangible assets

Quizes Examples/Introduction to Valuation exam.xlsx

Present Value

Years remaining on the project 9
Annual Cashflows $ 450,000
Discount rate 8%
Year # 1 2 3 4 5 6 7 8 9
Annual cashflows
Discounted cashflows
Present value of cashflows
Sensitivity analysis
Input discount rates 8% 9% 10% 11% 12%
PV output

NPV and IRR

Year # 1/1/14 4/1/14 7/1/15 8/1/16 2/1/17 3/1/18 4/1/20 5/1/20
Annual cashflows -$100,000 $13,000 $17,000 $15,000 $14,000 $19,000 $15,000 $200,000
Discount rate 12%
Net present value
Internal rate of return

Loan Investment

Windfarm project assumptions
Sale price $ 6,000,000
Years remaining on the project 10
Earnings before Interest & Tax $ 1,100,000
Tax rate 35%
Discount rate 8%
Loan assumptions
Loan as % of Sale price 70%
Loan term (in years) 10
Interest rate on loan 8%
Annual loan repayment
Year # 0 1 2 3 4 5 6 7 8 9 10
Earnings before Interest and Tax $1,100,000 $1,100,000 $1,100,000 $1,100,000 $1,100,000 $1,100,000 $1,100,000 $1,100,000 $1,100,000 $1,100,000
Interest payments
Earnings before Tax
Taxes paid
Principal payment
Annual cashflows
Discounted cashflows

Terminal Value

Growth rate 3%
Discount rate 10%
Year # 0 1 2 3 4 5 6
Annual cashflows $0 $430 $640 $820 $1,400 $1,450 $1,550
Terminal value
Discounted cashflows
Net present value

Quizes Examples/Valuing a Real Estate Investment .docx

1. Which factor affecting cash flows in a property investment would include the rental income earned between buying the property and selling it?

Revenues

Holding period

Mortgage

Taxes

2. Which of these is the correct definition of collection losses for a property investment?

The amount of rent that is not collected from the tenant

The costs incurred in finding a new tenant

The amount of money spent renovating the property before a tenant moves in

The costs of collecting the rent on a property

3. Which of these metrics represents the annual rent generated by a property if vacancy rates and collection losses are both zero?

Effective Gross Income

After-Tax Cash Flow

Potential Gross Rent

Net Operating Income

4. In the 'Effective Gross Income' sheet of this exam's Excel file, what is the total potential gross rent over the life of the investment?

5. In the 'Effective Gross Income' sheet of this exam's Excel file, what is the total vacancy allowance over the life of the investment? (Note: Enter your answer as a positive number.)

6. In the 'Effective Gross Income' sheet of this exam's Excel file, what is the total effective gross income over the life of the investment?

7. In the 'Net Operating Income' sheet of this exam's Excel file, what are the total expenses incurred over the life of the investment?

8. In the 'Net Operating Income' sheet of this exam's Excel file, what is the total net operating income over the life of the investment?

9. In the 'Mortgage Payments' sheet of this exam's Excel file, what is the mortgage balance in 2021?

10. What year in the 'Mortgage Payments' sheet of this exam's Excel file has a principal payment approximately twice as large as its interest payment?

2017

2018

2019

2020

11. Which of these cash flows in a property investment is subject to capital gains taxes?

The negative cash flow incurred when purchasing the property

The positive cash flows earned while owning the property (e.g. rent payments)

The negative cash flows incurred while owning the property (e.g. expenses)

The positive cash flow earned when selling the property

12. In the 'Operating Cash Flows' sheet of this exam's Excel file, what are the total after-tax cash flows in 2020?

13. You are planning to sell a property, and you propose to value it using a 20x multiple of potential gross rent. Which of the below statements describes how this valuation works?

The value of the property will be 20 times the average gross rent for the holding period of the property

The value of the property will be 20 times the potential gross rent in the year of selling the property

The value of the property will be 20 times the sum of potential gross rent for the holding period of the property

The value of the property will be 20 times the potential gross rent in the year of purchasing the property

14. Which of these is not used to calculate the adjusted basis of an asset?

Selling costs of the asset

Purchase costs of the asset

Selling price of the asset

Purchase price of the asset

15. Which of these cash flows in a property investment does not occur when the asset is sold?

Rental income

Capital gains tax paid

Selling costs

Pay off mortgage balance

16. Which of these would decrease the IRR of a property investment?

Increasing the loan term

Increasing the holding period

Reducing the loan interest rate

Increasing the loan amount

Quizes Examples/Valuing a Real Estate Investment exam.xlsx

Effective Gross Income

Revenue projections for sample property investment Before After
Year Units 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024
Current annual rent $ 30,000
Rental price changes % 5% 4% 4% 3% 3% 3% 2% 2% 2%
Estimated vacancy rates % 10.0% 5.0% 5.0% 5.0% 5.0% 5.0% 5.0% 5.0% 5.0%
Collection losses % 2% 2% 2% 2% 2% 2% 2% 2% 2%
Effective Gross Income Before After
Year Units 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024
Potential Gross Rent $ 30,000
Vacancy Allowance $
Collection Losses Allowance $
Effective Gross Income $

Net Operating Income

Revenue projections for sample property investment Before After
Year Units 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024
Current annual rent $ 90,000
Rental price changes % 9% 6% 4% 3% 4% 3% 2% 2% 2%
Estimated vacancy rates % 9.4% 7.7% 7.7% 7.7% 7.7% 7.7% 7.7% 7.7% 7.7%
Collection losses % 1% 1% 1% 1% 1% 1% 1% 1% 1%
Expense projections Before
Year Units 2015
Annual Expense inflation % 2%
Current operating expenses
Management fee $ 2000
Utilities $ 0
Insurance $ 150
Supplies $ 70
Advertising $ 150
Maintenance & Repairs $ 250
Property Taxes $ 890
Total expenses $ 3510
Effective Gross Income Before After
Year Units 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024
Potential Gross Rent $ 90,000 98,100 103,986 108,145 111,390 115,845 119,321 121,707 124,141 126,624
Vacancy Allowance $ (9,221) (7,999) (8,319) (8,568) (8,911) (9,179) (9,362) (9,549) (9,740)
Collection Losses Allowance $ (981) (1,040) (1,081) (1,114) (1,158) (1,193) (1,217) (1,241) (1,266)
Effective Gross Income $ 87,898 94,947 98,745 101,707 105,776 108,949 111,128 113,351 115,618
Operating Expenses
Management fee
Utilities
Insurance
Supplies
Advertising
Maintenance & Repairs
Property Taxes
Total Expenses
Net Operating Income

Mortgage Payments

Mortgage terms
Interest rate 7%
Start year 2016
Principal 1,400,000
Term (in years) 9
Mortgage payments for a sample real estate asset
Before After
Year Units 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024
Interest paid
Principal paid
Total Debt service
Mortgage balance 1,400,000

Operating Cash Flows

Mortgage terms
Interest rate 7%
Start year 2016
Principal 750,000
Term (in years) 9
Operating cashflows
Before After
Units 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024
Net Operating Income 200,000 206,000 212,180 218,545 225,102 231,855 238,810 245,975 253,354
Less Debt Service
Before-Tax Cash Flow
Less Income Taxes (92,000) (94,760) (97,603) (100,531) (103,547) (106,653) (109,853) (113,148) (116,543)
After-Tax Cash Flow