Coaching in the Age of AI and Sports Science

What do top college basketball coaches like Bill Self, Tom Izzo, and Scott Drew have in common? Several qualities, of course. To succeed at the top level of college basketball, or any sport for that matter, a coach needs tactical awareness, a sense of innovation, being able to handle pressure, and so on. And, of course, a coach needs to be a good motivator. The legendary John Wooden, for example, has websites, such as “The Wooden Effect”, devoted to his motivational skills.

There shouldn’t, of course, be any conflict between motivation and tactical acumen, but it does also feel like we are at an inflection point in sports, particularly with the rise of data analytics & AI. The latter has become an integral part of modern sports, particularly at the elite level. And for some coaches, it forces them to operate outside of their comfort zone. Data-driven decisions may seem counterintuitive to a coach’s gut feeling. It can become an uneasy alliance.

Data science has been embraced by college basketball

The vast majority of modern coaches look for as many advantages as possible, and that often leads them to sports science. Last year, The Athletic posted a report looking at how college basketball teams are increasingly hiring outside firms for analytics services. There is also a sense that we are only at the beginning of this era. Data and AI will soon be used at every level of sports, helping coaches do everything from predicting injuries to their key players to analyzing opponents’ tactics.

That said, there is only so far that data can take a coach. We’ve all been there before, seeing a team heavily favored in the betting be thwarted by an underdog. Tactics, preparation, and all other metrics point to a victory, only for the shock to occur. When it does, we often say the same thing, that the winning team wanted it more.

None of this is unique to basketball, of course. From soccer to football, cricket to baseball, there is an unquantifiable quality among some teams to be more motivated. It doesn’t always lead to victory, but it can be the difference maker. If a coach is not able to motivate their team, well, even the best players can fail.

Is too much data hurting basketball?

Of course, this is nothing unknown to college basketball fans. But, as we said, there is a point of inflection in sports at the moment. A coach can’t rely on motivational skills alone, but they also cannot rely on sports science alone. There needs to be a balance. And the fear is that sports will soon tip in the favor of the data side. We say that not as criticism, merely a fact. Over the last several years, several important articles have been published broadly on the same subject – too much data can be detrimental to sports.

That fear is borne out of removing the trust in coaches. There have been many stories throughout college sports history of coaches giving a kid a chance to shine, relying only on intuition that the decision is the right one. It’s the kind of thing that cannot be quantified in a spreadsheet. Now, with the multi-billion-dollar sports analytics industry, decisions on recruitment are being largely driven, at least in part, by data. Again, there is nothing wrong with this in and of itself. Moreover, if we look at teams like the Golden State Warriors, we know that technology can hold the keys to success.

But there must always be a place for the motivational coach. The contrarian, who, despite what the numbers say, can inspire a player to do better and a team to rise above their station. The best coaches in the world will all be using AI ten years from now – the genie is out of the bottle – but the true greats can motivate players to rise up to the challenge, making a mockery of the statistics. That’s something that should never be lost.