Case Study - Full APA and NO PLAGIARISM
Shrikaa
GZS5AS_6912685_10300916_940432976258.docxSmarthinking Tutor Response Form
Your tutor has written overview comments about your essay in the form below. Your tutor has also embedded comments [in bold and in brackets] within your essay. Thank you for choosing Smarthinking to help you improve your writing!
Hello Shrikaa I'm Tatum D., and I look forward to working with you on this Essay Center Review to improve your writing today. Let's get started!
*Writing Strength:
The conclusion summarized your main idea well. It may be subject to change as your discussion develops and you have more detail to include, but summarizing the main idea unifies your discussion. Good job. Main Idea/ Thesis
The body paragraphs don’t unify the discussion because the topic sentences, for example, “[d]ata analytics is really changing the game, and the unending baseball experiences an example situation. Even though 90% of baseball is mental, and the remaining 10% is physical, baseball maths are increasingly becoming different (Abraham & Brendan, 2019)” summarizes the research without showing why it is relevant. The research seems to replace your discussion instead of supplement it.
Research can be interpreted in any way, which could leave readers confused as to why it is relevant, especially since you didn’t summarize the main idea as part of your introduction. Unless your instructor wants you to take this approach, it may be better to show the reader why the research is relevant. How does it apply to your topic?
The topic sentences may contain research, but it shouldn’t be the only thing, for example, while Erikson (1968) and Jung (1912) both argue that individual identity is tied to society, neither accounted for or anticipated the impact of the internet and social media; although their theories remain relevant, developments in technology opens up new fields of inquiry. Here, the sentence summarizes what two researchers do, but it also shows what the writer’s response to the topic is. It shows that they think there is potential for new areas of research based on what is already given. Why are the changes data analytics bring to baseball relevant to your overall discussion?
*Shrikaa 11822442, you requested help with Content Development:
The discussion seems underdeveloped because you didn’t consistently explain or discuss the research or show how the information in one paragraph applies to other parts of the essay. Some paragraphs end with summaries like “[t]he prevailing issues include long-term contracts, which engage players with the team, where they will not bring the best performance (Matt, 2018)” without showing why it is relevant. In this case, you went on to discuss a new topic in the next paragraph.
Because each paragraph is a self-contained entity that focuses on a single point while, at the same time being connected with other parts of the essay, the connections between these ideas need to be elaborated. It may be clear to you why the topics are related but your instructor may want to see your thinking process, or they might not be clear on the topic. If different group members discussed different topics, why would they relate to one another?
Better transitions exist where you explained the topic, for example “[u]nfortunately, the assumption is that the teams should know that the professional players acquired will be paying for the future and not the past (Matt, 2018) […] That might not be the right way to do things because today's available data has made it easy to forecast for the future”. This showed that the data makes things easy to forecast the future. Here, you seem to show why the research applies to the main idea. In cases where the research is more relevant to the point made in the next paragraph, you may need to explain this in order to show that the different paragraphs discuss the same point in different ways. Transitions are complex, so please take some time to review the lesson on > Smooth Transitions in the Smarthinking Writer’s Handbook. The lesson discusses both sentence and paragraph transitions, but for this topic, please pay special attention to how transitions work at the paragraph level, especially since, according to the assignment description, more than one of you are working on the topic. If you have the resources, it may also be appropriate to resubmit your revised draft and ask your tutor to focus on the organization or transitions.
*Shrikaai 11822442, you requested help with Grammar & Mechanics:
I’ve noticed that you don’t use any quotes in your essay, which could limit the degree to which you are able to highlight the research. Using only paraphrases presents readers with a filtered interpretation of the research instead of content that is immediately relevant to the discussion. It shows how you interpreted the research but not necessarily what you are interpreting.
Using quotes can work especially well if you want to draw attention to specific information, for example, the language used in one of the sources or specific details. Of course, this needs to be integrated into your discussion according to guidelines stipulated by the APA. Please consider using some of the following extracts from the Smarthinking APA style guide as a model:
· According to Ravitch (2010), “Tests are necessary and helpful. But tests must be supplemented by human judgment. When we define what matters in education only by what we can measure, we are in serious trouble” (p. 166). [< A narrative that uses signal phrases]
· As research has shown, “Tests are necessary and helpful. But tests must be supplemented by human judgment. When we define what matters in education only by what we can measure, we are in serious trouble” (Ravitch, 2010, p. 166). [<Parenthetical citations]
These approaches will allow you to show the reader, more precisely, which words the author’s used. This structure could make the difference between your own ideas and those of others more precise. Summary of Next Steps:
· Show why the research is relevant to your discussion.
· Reflect on the research more consistently.
· Consider using quotes to support the discussion.
Thank you for submitting your essay for a review, Tharakeswari. I enjoyed helping you with this step in the revision process. Have a good day! - Your tutor, Tatum D.
You can find more information about writing, grammar, and usage in the Smarthinking Writer's Handbook.
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Please look for comments [in bold and in brackets] in your essay below. Thank you for submitting your work to Smarthinking! We hope to see you again soon.
Case Study 4.1: Professional Sports and Data Analytics
Tharakeswari Paladugu
University of the Potomac
CBSC520 – Data Analytics
Prof. Dr. Dennis Hermann
11/21/2020
Professional Sports and Data Analytics
Introduction
Nowadays, several industries are adopting analytical methods when it comes to decision-making. Nonetheless, no industry has the types of analytical initiatives coming underway as the sector of professional sports (Thomas, 2014). The domain is associated with analytical customers, online statistical analysis, and the availability of data. Despite the availability of impressive activity and growth, there is no doubt that the use of analytics in sports has challenges. Foremost, there is the issue of the traditional culture of several teams. Again, a few players, coaches, owners, and managers pursue a career course in professional sports because they are interested in Data Analytics. Even if considerable data and analytics are available to support the significant decision, they might employ them over their experience and intuition. In that case, the demand from decision-makers for sports analytics is considerable less than technology, new metrics, technology, data supply, and analytics (Thomas, 2014). [What do you want to say about the topic? The introduction summarizes the background information without showing what you want to say about data analytics. Unless you were instructed otherwise, please consider summarizing the main idea on both ends of your essay to show the reader what to expect.]
Data Analytics is Changing the Game
Data analytics is really changing the game, and the unending baseball experiences an example situation. Even though 90% of baseball is mental, and the remaining 10% is physical, baseball maths are increasingly becoming different (Abraham & Brendan, 2019). The unrelenting advancement in data analytics is upending long-held baseball, including how to spot stars, predict their performance, and the number of dollars to sign them. There have also been the arising issues of big-name become free agents and looking for a baseball team to engage them. For instance, a free agent can always sign with a franchise or club because their earlier contracts had expired and are yet to be drafted (Ricky, 2019). [<The examples can benefit from some elaboration to show why it is relevant to your main idea. What real-life cases demonstrated the issues that can arise? Why is signing with a franchise and becoming a free-agent relevant to your topic?]
Currently, analytics and statistics are also being blamed for players' top-ranking and loss of deals with bigger sporting clubs (Thomas, 2014). However, with most other industries, data analytics is also becoming the litmus test for the bigger deals in professional baseball. Perhaps, the analytics group has managed to make its mark (Abraham & Brendan, 2019). Data analytics also illustrates how the valuation is done for the corporate deals to give considerations to net present value and the future cash flows upon acquisition. Unfortunately, the assumption is that the teams should know that the professional players acquired will be paying for the future and not the past (Matt, 2018). Therefore, their presence on the team should bring value to the future profitability of the team. Statistically, people should always look at the past to project for future benefits. In that case, analytics of the situation should be handled with care because it is easier to be dragging yourself out to the past. That might not be the right way to do things because today's available data has made it easy to forecast for the future.
The major league of baseball has experienced a two years slow market, and there are several reasons for such. The sporting activity needs time for players’ development because they are also part of the product in the baseball sporting business (Matt, 2018). Smart teams do not want to commit to long-term deals, which will not be profitable. However, many players are finding it hard to survive and hence the start of frustration in life (Ricky, 2019). The advantage is that data analytics could prevent the occurrence of bad deals. Conversely, history indicates that the statistics department has been banging human heads against the wall as fans watch their favorite clubs making ridiculous deals. The prevailing issues include long-term contracts, which engage players with the team, where they will not bring the best performance (Matt, 2018).
Data analytics in the baseball star-spotting will be a new norm, and the focus should always be productivity. Through data analytics, it is possible to caution the teams to engage in bad contracts that might tie their budget into only one player. Maybe, that one player might not be valuable as expected by the assigning baseball team. [The paragraph is underdeveloped because it only has a claim. What research supports this and how does it apply to other parts of your discussion? Please make sure that each paragraph has a claim, supporting research and/ or examples, and a discussion that unifies the discussion.]
Data Analytics for Predicting the Sale of Season Tickets
Ultimately, the purpose of using analytics in the niche of world sports is to make many people purchase the season tickets. Fans are induced through data analytics to purchase seasonal tickets irrespective of the team placed in the standings. Key indicators that can influence supporters to buy season tickets include loyalty. Again, it is always one thing to buy a ticket and another to use it for the pre-planned event. Solutions to such scenarios are solved by scanning the tickets for major league clubs whenever fans attended the games (Ricky, 2019). Clubs also capture the data to find out if the acquired tickets are specifically used for the planned events.
Data analytics and Video Gaming
Normally, gaming companies pay attention to the data collected. The information is structured and used for making business decisions and offer better services to customers. Furthermore, video gaming is a data-driven industry, and of course, game companies will always find ways to dig deeper into the data as they boost their competitive edge (Ricky, 2019). The main issue for customer game recommendations is to entice new users with the most popular games over the past years. Registered users should also be engaged in their apparent preferred genre, especially the ones they have not tried before.
Data analytics is changing the Game
Data analysis is a big part of the experience in any sporting activity. Currently, the game and results of sporting activities are being changed by data analytics (Ricky, 2019). The use of analytics software has advanced, and it is the same data analytics. You are used to watching the video of teams on the field while participating in several games. Perhaps, it is not only baseball teams that have taken advantage of using data analytics to predict future performance (Ricky, 2019).
Data Analytics is essential and soon revolutionizing the Sport Industry.
The amount of data that is currently available in the world due to technological advancement is becoming unimaginable (Molly, 2018). Sports teams are also using the available data to their advantage. The industry of sport is using data analysis to increase revenue, improve teams’ quality of play, prevent injury, and improve player performance. Data is becoming a great resource. However, it will serve no use if there are no people to analyze and interpret its usefulness. In that case, sports analysts are proving to be high in demand, and many sports clubs are developing entire departments for statistical analysis. Similarly, sports teams are also using data analytics for competitive advantages (Molly, 2018).
The specific advancements in data analytics include integrating data sources to enhance completion, creating a different fan experience, and communicating the reason why data is becoming useful (Molly, 2018). Data analytics is beneficial to several sports industry stakeholders, including managers, coaches, marketing professionals, agents, analytics staff, medical personnel, and scouts (Molly, 2018). Therefore, with the availability of technology, sports analysts can use data and create insightful and simple visualizations communicating better ideas to the team's decision-makers.
The emergence of sports data analytics and the new science of winning
An incredible amount of data is currently available, which proves a new science of winning (James, 2010). The only sources for statistics included sports sections in the local newspapers, trading cards, and the weekly sporting news in the previous days. The baseball cards were mainly used to offer the position of the player’s defensive positions, batting average, total hits, triples, number of at-bats, runs scored, run batter, doubles, and home runs for the past seasons (Thomas, 2014). For pitchers, the data was learned from the number of innings and games they managed to pitch. Again, from the basketball cards, it was possible to learn about the player's defensive position, shooting percentage, free throws, rebounds, assist, total points, turnovers, fouls, and blocked assists (James, 2010). There is no need for trading cards because of technological advancement because the information is already available through data analytics for emergence analysis and new strategies for sport winning.
The Future of Sport Analytics
The future of sports analytics is related to the idea of beyond money ball. The field of sports analytics has also been growing rapidly, and it is currently attracting a great deal of interest (Benjamin & Vijay, 2012). The unconventional strategies illustrated in the money ball are soon becoming a reality in the sports industry. Perhaps, it is high time that the teams lurking behind to adopt data analysis while making an informed decision regarding the management of the team's sporting activities (Benjamin & Vijay, 2012). Additionally, data and computing power continues to grow and, hence, contribute to an emerging industry structure. The possibilities for the use of analytics in the sporting industry is rapidly changing, and the future is expected to experience growth in terms of revenue collection and teams’ performance.
Conclusion
Data analytics in sports will continue to grow and evolve as a field. However, the growth and evolution pace will depend on how leaders in the sporting industry are quickly convinced of the significant investments into analytics, which include skilled personnel, data models, and information systems. Ideally, investing in sports analytics is to bring a true competitive advantage to the sports industry. Therefore, for teams to increase their performance, they must use sports analytics in a significant approach.
References
Abraham, W. & Brendan, H. (2019). Changing the Game: How Data Analytics Is Upending Baseball. Retrieved from: https://knowledge.wharton.upenn.edu/article/analytics-in- baseball/
Benjamin, A. & Vijay, M. (2012) Beyond Moneyball: The future of sports analytics. Retrieved from: http://analytics-magazine.org/beyond-moneyball-the-future-of-sports-analytics/
James, C. (2010). The Emergence of Sports Analytics. Retrieved from: http://analytics- magazine.org/the-emergence-of-sport-analytics/
Molly, O. (2018). Why is Data Analytics So Important in Sports? Retrieved from: https://www.samford.edu/sports-analytics/fans/2018/Why-is-Data-Analytics-So-Important-in-Sports
Matt, M. (2018). How Data Analytics in Sports Is Revolutionizing The Game. Retrieved from: https://biztechmagazine.com/article/2018/12/how-data-analytics-revolutionizing-sports
Thomas, H. D (2014). Analytics in Sports: The New Science of Winning. Retrieved from: https://www.sas.com/content/dam/SAS/en_us/doc/whitepaper2/iia-analytics-in-sports-106993.pdf
Ricky, A. (2019). How Data Analysis In Sports Is Changing The Game. https://www.forbes.com/sites/forbestechcouncil/2019/01/31/how-data-analysis-in-sports-is-changing-the-game/?sh=5d9d2dca3f7b
https://knowledge.wharton.upenn.edu/article/telling-data-story-behind-video-gaming/
[Your APA formatting is inaccurate because you didn’t show which container the article belongs to. To which collection or websites do the articles belong? Please refer to the Smarthinking APA style guide (6th edition) for some examples of how to document online articles from news sources more accurately.]
