Leverage your Students’ Love for Sports to Teach Them Data Science
Do your high school students love sports? Many students love watching, playing, or analyzing sports, are unsure about what they want to study after high school, and might have discovered that being a professional athlete – perhaps an ultimate dream – is not an option. So, how can one combine a love of sports with a solid career opportunity? The answer might be data science, one of the fastest-growing career fields, which happens to be integral to a wide range of industries, including “the game” they love to watch!
What is data science?
As a relatively new field, the phrase “data science” might sound new to you or your students. The US Bureau of Labor Statistics defines it as “using analytical tools and techniques to extract meaningful insights from data.” The field is also projected to “grow 36 percent from 2021 to 2031,” significantly faster than the average occupational growth. What kind of fields utilize data science? Pretty much any you can think of. Data science is applicable to social media, healthcare, education, law enforcement, transportation, and any organization that makes informed decisions – including the national sports leagues. Besides a wide array of potential career opportunities, these companies are willing to pay top dollar for recent graduates; an average of $109,802 is awarded to first-time hires according to Indeed. FORTUNE says it best: there is a “robust demand for data science grads… resulting in a steady stream of job offers and large compensation packages.”
How do sports teams use data science?
The use of data science in sports was popularized in the mainstream over 20 years ago in the book and movie ‘Moneyball,’ starring Brad Pitt. Moneyball told the story of how Billy Beane, the general manager of the Oakland A’s, used data and advanced statistical analysis to field a highly competitive professional baseball team on a low budget.
Fast forward to present day: nearly all professional sports teams utilize data science and employ a robust data science team. According to ESPN, National Football League teams use data for decision-making in scouting, coaching, marketing, and the rest: quantitative analysis is integrated into all decisions a team can make. The Cleveland Browns lead the way analytically, with the Baltimore Ravens and Los Angeles Rams following close behind. Amber Williams, the first African American female data analyst for the Rams, notes that her day-to-day consists of collecting “data on the business side of the organization,” and every week she “leads various teams through the data to present it to them and say: this is what we did well last week, this is what we didn’t do well, this is how we can improve as a business, and this is what we can target more strategically.”
For Amber, studying data science and working for the Rams was a “no-brainer,” creating a “marriage between my professional interests of analytics and data and understanding consumer behavior, and my passion and love for the team.”
Amber has also held data analytical jobs for Pepsi and Netflix, but finds the work similar to her current position with the NFL, noting, “At the end of the day, if you’re part of the marketing or on the business side of the organization, the ultimate goal is to make more money… we want to sell tickets, we want to gain more fans… you’re using data to say… this is what’s working and this is what isn’t resonating… to build really solid ideas.” A plus? “Working for a football team, game day is the best experience because all the things you’re working on throughout the week: the campaigns, the reports, those are all used for the next game day and you can watch it come to life. You don’t control what happens on the field, but you can control everyone’s game day experience from start to finish.”
The rapid growth of data in sports
Data in sports is moving past marketing decisions and on-the-field player statistics; it can even be used to track players’ sleep behavior using sensors to identify how patterns relate to performance. The rapid growth of the field, and the growing concerns surrounding artificial intelligence, privacy, data mining, injury prevention, and even sports betting, have opened the door for creative problem-solving for data analysts entering a previously un-discovered field or opportunity.
Do you have students who you believe would be interested in careers in data science?
Expose them to this career path early by giving them a foundational understanding of data science and the opportunities it might bring. The skills gained in studying data science, such as decision-making, identifying efficiency, and communication, can be applied to multiple careers and help them find the right fit.
Everfi’s free-to-teachers Data Science Foundation curriculum offers four lessons to build students’ understanding of data science concepts and prepare them for real-world opportunities and success, including:
- Data Science Basics
- Collecting, Cleaning, and Validating Data
- Analyzing and Visualizing Data
- Reporting and Action on Data
These lessons are a great fit in high school courses utilizing statistics, economics, math, or college and career exploration.
Love for sports easily translates to love for data science
Introducing students to this exciting and emerging career field while still in high school can help develop an interest, introduce them to data science careers in fields they admire and support, and connect their love of sports with valuable and engaging opportunities.
References
Bean, R. (2022, November 8). Moneyball 20 years later: A progress report on data and analytics in professional sports. Forbes. https://www.forbes.com/sites/randybean/2022/09/18/moneyball-20-years-later-a-progress-report-on-data-and-analytics-in-professional-sports/?sh=3a3fa9a1773d
Business Woman Media. (2022, May 29). Data Science is the now fastest growing career field. The Business Woman Media. https://www.thebusinesswomanmedia.com/data-science-is-fastest-growing-career/
Data scientist salary in United States – Indeed. (2023, June 5). https://www.indeed.com/career/data-scientist/salaries
Griset, R. (2022, January 19). Who should pursue a master’s degree in Data Science? Fortune. https://fortune.com/education/articles/who-should-pursue-a-masters-degree-in-data-science/
Parameshwaran, S. (2023, January 31). How analytics can boost competitiveness in sports. Knowledge at Wharton. https://knowledge.wharton.upenn.edu/article/how-analytics-can-boost-competitiveness-in-sports/
U.S. Bureau of Labor Statistics. (2023, May 1). Data scientists : Occupational outlook handbook. U.S. Bureau of Labor Statistics. https://www.bls.gov/ooh/math/data-scientists.html
Walder, S. (2022, December 6). NFL Analytics Survey 2022: Teams that use advanced metrics most, least. ESPN. https://www.espn.com/nfl/story/_/id/35189929/2022-nfl-analytics-survey-most-least-analytically-inclined-teams-overrated-underrated-players-more
YouTube. (2022). Amber Williams – Super Bowl Winning Analytics (Ep. 43). YouTube. Retrieved June 5, 2023, from https://www.youtube.com/watch?v=iUZv8uapHgU.
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Kira is an Enterprise Manager on the Customer Marketing team at Everfi. She holds an M. Ed. in secondary English Education from Virginia Tech and an Integrated Learning Certificate in arts-integrated curriculum design from the University of Richmond. She has over six years of experience in education and marketing, working as an English teacher in Richmond Public Schools prior to joining the Everfi team. She now works with Everfi’s top partners to drive impact in communities and empower learners with the essential skills they need to thrive.
Greg is the Sr. Principal, K-12 Marketing at Everfi. He holds an MBA degree from the University of Maryland and has worked in the Education field for over 7 years, along with prior experience in digital marketing at a major online publisher. He has utilized data science practices throughout his career, as well as in his current role, to build impactful marketing campaigns. He has two sports-obsessed sons who both love watching, playing, and analyzing sports.
