How Data Analysis in Sports Is Changing the Game
When it comes to data analysis, sports have been miles ahead of most other industries. Scouts, coaches, and GMs have always looked at stats sheets for any given player in sports such as baseball or basketball, but rarely did they venture beyond points per game, batting averages, or field goal percentages. But that all changed in 2002, thanks to Billy Beane, who was hired as the general manager for the Oakland Athletics.
He managed to put together a baseball team on a shoestring budget that would make it to the playoffs. Beane used sabermetrics to discover and sign undervalued players, which ultimately changed the way teams valued players in the future. The data analysis approach pioneered by Beane and the Oakland Athletics’ playoff run became the subject of a book, Moneyball, as well as a movie of the same name.
That’s all great, but data analysis has changed and is still changing sports in many other ways. Let’s check out some of them.
1. Helping Players Improve
Shane Battier, a former NBA player who played for Memphis Grizzlies, Houston Rockets, and Miami Heat, was instrumental in helping the star-studded Heat team win two NBA titles. Battier was also dubbed by the media as the “No Stats All-Star.” Even when he would score zero points, advanced data analysis would show that he was still one of the most useful players on the court. Battier helped the team in many intangible ways, and on top of that, he relied on analytics himself.
Whereas other Miami Heat players would receive a one-page scouting report, Battier’s scouting report would be 15 pages long. He was one of the first players to embrace data analytics in order to improve his game and guard the likes of Kobe Bryant and Carmelo Antony. The takeaway: players can improve their performance not just by running indoor baseball drills or pick and roll plays in basketball but also by analyzing statistical data.
2. More Accurate Player Scouting
Thanks to tools like automated video analysis, scouts are now able to make a more informed summary of every player they are looking at. They can also rely on advanced stats such as positional and tracking data to narrow down their choices. Data analysis even enables professional scouts to assess player skills and view their biometric and medical information. This especially came in handy during the pandemic because they were able to do all of that remotely.
This not only enables teams to save money by getting players who are undervalued but also to find just the right fit for their roster, even if the player in question doesn’t appear to be the ideal choice at first sight.
3. Predicting Fan Behavior
With data analytics, sports franchises and their business teams can improve factors that extend beyond the court or the locker room. This means it’s possible to analyze fan behavior in order to sell more beverages and snacks during games or to create an optimal path for fans to leave the arena without congesting the exit routes.
By gaining more insights into customer behavior, sports event organizers can create a better overall experience for visitors and earn more money by delivering key messages and special offers at just the right time. In other words, data analysis can help improve the entire ecosystem that revolves around a particular team.
4. Reducing Season Ticket Churn
The most common reasons why fans might give up on getting season tickets are prolonged losing streaks, not making the playoffs despite expectations, low attendance, and poor fan engagement. In every industry, and that includes sports, it’s always cheaper to retain existing customers than acquire new ones, which is why teams are using data analysis and prediction models in order to identify fans who are most likely to churn. To reduce ticket churn, sports teams can run different campaigns and promotions based on the data they were able to gather.
5. Injury Prevention
Medical data insights can help teams create an optimal training regimen for each player, depending on their level of fitness and exertion, in order to prevent injuries. The impact of this is two-fold:
- It helps on the business end of things – The team can keep their players healthy and save on medical expenses and recovery. They can also keep their sponsorship deals and ticket sales, as fans don’t like to see their team fail to reach the playoffs or its star player sidelined due to injury.
- Players benefit as well – They can use this data in order to have longer careers and, ultimately, higher earnings.
Although data analysis is something that can no longer be ignored by any sports team or franchise, we have yet to see the full extent of its impact on all areas of sport, from the game itself, players, and scouting, to customer engagement and ticket sales. One thing is for sure: it’s here to stay.
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