Every sport is a game of numbers. Basketball has rebounds, free-throw percentages, and the dual-sided assist-to-turnover ratio. Baseball has batting averages, on-base-percentages, and the all-important RBI (runs batted in). Football has quarterback ratings, receiver catch rates, and the defense-focused DVOA (defense-adjusted value over average). The list goes on. These numbers aren’t meaningless. They measure very specific events within their respective sports, and they can be used to make insightful correlations to other aspects of athlete performance and administrative decision-making. The process of collecting and analyzing these numbers to improve performance is called sports analytics, and it’s a booming field. Below, we provide an introduction to Sports Science today: what it is, where it’s used, and how it might be useful to you.
Sports Analytics: A Definition and Brief History
Put simply, Sports Science is the practice of analyzing various aspects of sports to predict and/or change outcomes. Put less simply (though more comprehensively) by experts Benjamin Alamar and Vijay Mehrotra in their 2011 article for Analytics Magazine:
“We define Sports Science as ‘the management of structured historical data, the application of predictive analytic models that utilize that data, and the use of information systems to inform decision-makers and enable them to help their organizations in gaining a competitive advantage on the field of play.’”
What this elongated definition tells us is that Sports Science can use any kind of data to produce results. Individual player statistics, defensive and offensive schemes, substitutions, even weather conditions can be collected and strategically used to influence future decision making. The trick is finding the right information.
But first: the beginning of sports analytics. The collection of statistics has been going on since the inception of sport, but the practice of applying those statistics to strategy (and actively searching for new statistics and patterns) is a relatively recent development. Most mark the advent of Sports Science with a moment or movement commonly known as “moneyball.” In the mid-1990s, Oakland Athletics’ General Manager Billy Beane used sabermetrics — the collection of empirical statistics in baseball — to influence recruiting and trading decisions. This led to decision-making that was deemed unconventional at the time. Players were selected based on specific stats such as on-base percentage, not common recruiting factors such as player size, speed, and isolated performance as witnessed by recruits.
Though unconventional, moneyball was highly effective. By the new millennium, The Oakland A’s were winning over 90 games each season. Other teams started to take notice; the principle behind moneyball — the use of nuanced statistics to influence decision making — began to spread beyond baseball.
Who Uses Sports Science?
The answer to the question above is easy: everyone. What began as moneyball has turned into a snowball that’s gradually enveloped every sport played on the professional level today. In the NBA and several European soccer leagues, on-court cameras collect Player Tracking data to chart player statistics at every instant of the game. In the NFL, wearables track player performance and obtain data that can be used for a plethora of important analyses. Baseball, the birthplace of moneyball, has also expanded to hardware-driven analytics. The MLB uses platforms to measure a ball’s exit velocity and launch angle—essential factors to consider in determining the effectiveness of each hit. In these instances, and many others, analytics is obtaining new data and using it to drive decision-making. For sports organizations, athletes, and fans, the benefits are boundless.
Sweating the Small Stuff: Why Sports Science Matters
Over the past several decades, Sports Science has proven itself as an invaluable instrument in improving all aspects of sports operations, from athlete performance and competitive strategy to management decision-making and fanbase relationships. The easiest benefit can be seen in the wins column. What started with Billy Beane and moneyball can now be seen in a number of success stories across the globe. In one dramatic example, the implementation of automated video analysis helped propel struggling U.K. football soccer team Lincoln City to the top of the National League. But the benefits don’t stop there. Many sports teams have used analytics to improve sales and revenue. The NBA’s Orlando Magic use the predictive analytics platform to analyze game data and personalize marketing campaigns. The result? The Magic are among the top revenue earners in the NBA, despite being in the 20th-largest market.
Sports Science Today
With success stories like those above, it’s easy to see why Sports Science is on the rise. Each season, today’s top analytics departments strive to outdo each other and find cutting-edge analytic tools to drive successful decision-making. The Sports Science boom has not only led to robust internal analytics divisions within sports teams and leagues, but it’s also led to the rise of new companies developing analytics to sell. The rise of these companies and their widespread success has led to unprecedented growth in the Sports Science market as a whole. A market study conducted by Kenneth Research forecasts a massive CAGR (compound annual growth rate) of 40.1% from 2016 through 2022, with the total market value reaching nearly 4 billion dollars by 2022.
Sports Science with Red Grass Ventures
As the field of Sports Science continues to grow, at Red Grass Ventures, our professionals specialize in this exciting, ever-expanding market. With our insight and professional networks, we can help you make the right moves guiding your company. Reach out to our team to learn more.