from Hacker News

Algorithms predict sports teams' moves with 80% accuracy [pdf]

by mateja on 10/13/22, 1:09 AM with 28 comments

• by krajzeg on 10/13/22, 10:03 AM

  While impressive, volleyball is one of the most formulaic sports when it comes to predicting what happens next. This is not a dig on volleyball (I'm a fan!), but it is how the sport works.

  The first touch is always about receiving the ball and passing it cleanly to the setter. The second touch is about setting up the attacker (if possible). The third touch is a spike or other attempt to get the ball to the other side. The only significant decision points are usually who the setter chooses for the attack (among 2-4 players depending on formation), and on the defense side, where the blockers jump (3 players choosing spots to cover). Since the algorithm only predicts "actions", both of those don't matter (the setter is going to be "setting" regardless of who they choose, the blockers are always going to be "blocking" regardless of the spot they cover).

  The "team strategy" part is in effect just a check of whether the algorithm knows what is happening on the court at all. Volleyball allows the aforementioned three touches, and what the team is doing for each touch is pretty much immutable (the only source of variation is if one of the "steps" fails).

  This is of course still an achievement, but the choice of sport gives the researchers a leg up, since volleyball has significantly fewer "degrees of freedom" than other sports. In that context, ~80% accuracy at predicting an action 2 seconds out is less interesting, and it's unlikely that it's anywhere close to human performance for this particular sport.

• by kayodelycaon on 10/13/22, 2:42 AM

  Title is misleading. This is about classifying volleyball players and predicting their actions up to 2 seconds in advance. Which is really impressive. Humans do this automatically without even thinking about.

  General artificial intelligence is a still long way away, but the slow progress and exploration is fascinating to watch.

• by halflings on 10/13/22, 10:57 AM

  The paper doesn't mention any baseline, and so claims like "86% accuracy" are a bit useless: what if players do the same action 85% of the time? Then the model wouldn't be not predicting much. If on the other hand the most common action happens only 30% of the time, then that would be an incredibly strong result.

• by glouwbug on 10/13/22, 4:11 AM

  I bet it can predict that the Canucks will never win the playoffs either

• by jugg1es on 10/13/22, 1:14 PM

  I'd like to see an attempt to predict the movement of an NFL defense based on the starting positions of both the offense and defense. Seems like a much harder problem than volleyball, yet is something that human experts can clearly do on the fly.

• by thom on 10/13/22, 7:35 AM

  It’d certainly be interesting to see if 80% accuracy over a 2 second window was enough to exploit tactically. If so, you’ve probably just saved a few hours of a video analyst’s time. Interesting approach though. There’s been a lot of work on this over the years, including on (dare I say) more complex sports like soccer. This was from Sloan 5 years ago for example:

  http://www.yisongyue.com/publications/ssac2017_ghosting.pdf

• by uptownfunk on 10/13/22, 3:36 AM

  What will be the effects on betting once the outcomes from the models have been priced in. I suspect odds will get wildly out of balance.