Data analytics transforming college basketball
In basketball, back in the 1990s, no one considered the three-point shot as the best shot in this sport. The majority of players who controlled the game could not shoot from more than a few meters from the basket.
Even Michael Jordan, the best player in the history of the sport, was a mid-range specialist who attempted no more than two 3-pointers per game throughout his career, while the best players today try a lot of long shots per game, frequently choosing corner shots. What's changed? Analytics.
Adam Petway is the director of strength and conditioning for men's basketball at the University of Louisville. He has an MBA with a focus on sports administration, a PhD in sports science, and has previously worked on the coaching staffs of the NBA's Philadelphia 76ers and Washington Wizards. He just furthered his studies through MIT Professional Education's Applied Data Science Program (ADSP).
When he first started in the profession, data analysis was almost non-existent in training rooms, whereas today there is force platform technology, velocity-based training, GPS tracking during games and training, all to get a more objective analysis to help athletes, so data analysis has increased exponentially.
At MIT, Petway attended live online classes with other people from completely different specialties: lawyers, professors and business executives, him being the only strength and conditioning coach, but he believes that the focus on data gave him and his colleagues a common understanding of each other's work.
He learned two important aspects: learning to write code in Python and using unsupervised learning approaches to put data through artificial intelligence algorithms, considering that since sports teams generate a lot of data, coaches must be able to analyze this data using methods that produce practical insights.
Petway finds it very useful to have access to such high-level data science practitioners, as he is now able to create decision trees, data visualization and run principal component analysis, so he does all these things himself, instead of relying on third-party companies to come and tell him what to do, he takes that data and analyze the results himself, thus saving time and a lot of money.
According to Petway, analytics are advancing the area of strength and conditioning well beyond the time when coaches would only instruct players to complete a particular number of repetitions in the weight room. Wearable technology makes it easier to monitor an athlete's average speed and the amount of practice ground they traverse.
Petway can assess the force with which basketball players jump and land, using data from a force platform, and even calculate how much force an athlete is producing with each leg and he's also able to measure how fast athletes are lifting weights by using a device known as a linear position transducer. He says the main goal is to develop training regimens that reduce the risk of injury while also increasing the performance of athletes.
Ultimately, Petway notes, coaches are primarily interested in just one data point: wins and losses. But as more sports professionals see that data science can lead to more wins, he says, analytics will continue to gain a foothold in the industry.
