In the last few years, big data has started to transform many areas of human activity, from share dealing to retail, and sport has been no exception.
The rise of sports analytics was given a major boost by the release of the book Moneyball: The Art of Winning an Unfair Game in 2003. The story of how the Oakland Athletics were able to make the most of their meagre resources by making data-based decisions caught the imagination of baseball fans, managers, and coaches, and 15 years later, analytics is used in all major sports.
Analytics has been embraced by a range of sports and there’s no better example of this than in soccer, where subscription player-monitoring platform Wyscout is now used in 500 leagues worldwide to scout and track players. Agents, managers, journalists, and even sports betting sites are now making use of the analytical data that Wyscout produces.
There’s no doubt that one of the most notable impact of sports analytics has been in baseball. Both of the 2017 World Series contenders are driven by analytics. The Houston Astros began to rely on analytics for insights and decision-making evidence back in 2011 when Jim Crane purchased the franchise and overhauled the team’s structure. He brought in big data experts, a move that laid the groundwork for their Championship-winning side. These days, most teams in MLB are using analytics in some form or other, with the Astros, Dodgers, Red Sox, Yankees, and Cubs being particularly data-driven.
The benefits of analytics are now being felt in college baseball. The success of the Iowa Hawkeyes is just one example of how big data can boost performance. Under head coach Rick Heller, who took over in 2013, the Hawkeyes have won at least 30 games every season and are one of the top baseball programs in the Big Ten. One of Heller’s main innovations was the incorporation of analytics into the program. Iowa employ numerous pieces of analytical technology, including TrackMan, PitchGrader, Senaptec, Zepp, and others.
The University of Missouri Tigers is another college baseball program benefiting from analytics. Tigers head coach Steve Bieser and hitting coach Dillon Lawson adopted analytic technology while they were at Southeast Missouri State and have taken that approach to the Tigers, with great success. In their first season, the Tigers won 36 games – their best performance since 2008 – improving in every important statistical measure.
While analytics has made a major impact in MLB, it could prove to be even more important at college level. With no trading or free-agent market to rely on, colleges have to focus on recruiting and developing young players, and that is where analytics can have the most effect, in identifying potential and areas that a player needs to work on. This is where data analytics becomes not just a means to identify players who might be good value but also a way to help individuals improve their performance.
Another reason why analytics is taking off in a big way at college level is that there is less resistance to change in a college environment. Baseball is a conservative sport, and in the early years of analytics, there was considerable push-back from traditionalists in the coaching, scouting, playing, and journalistic ranks, who felt that using data rather than instinct or intuition was either foolish or against the spirit of the sport. However, there are fewer such obstacles in the fiercely competitive world of college baseball.
It’s also the case that younger baseball players who have grown up in the information age are more comfortable with data and the use of analytics than their forebears. College baseball players will have grown up watching MLB Network, which features Statcast-based replays and leaderboards that feature analytical technology such as details on pitch exit velocity and spin rate analysis. For the new breed of baseball players entering college, data analysis is part of the landscape, not an innovation to be feared.
There are still opponents of analytics in the game – those who think that baseball should be about instinct rather than intellect, and who see analytics as tools for nerds. However, they are fighting a losing battle. Analytics has transformed MLB, just as it has begun to revolutionize many sports, and it is starting to produce the same effect at college level. Thanks to Moneyball, big data, and analytics, baseball is at the cutting edge of sports technology, and with new analytical tools being developed all the time, the data revolution is only likely to gather pace. Welcome to the future, baseball fans!
