5 ms·
Cool project! It sounds like you've run this in previous years, so I'm curious - how well has the model done in the past?
by rococode 8y ago
Cool project! It sounds like you've run this in previous years, so I'm curious - how well has the model done in the past?
- aaaaaaaaaaab 8y agoProbably about as well as trying to predict the result of a coin toss.
- klohto 8y agoSo, 50%? :)
- throwawaymath 8y agoIf that were actually the case, this model would be far and away the best ever developed!
- jjuel 8y agoI mean do you really think NCAA basketball games are just a random coin toss? If that were the case wouldn't more than 1 16 seed have won a game? Wouldn't more lower seeds have won the whole tournament? In that case theoretically every team has the same chance to win it all yet the lowest seed ever to win was an 8 seed.
- tonmoy 8y agoHe has predictions from 2017 and 2018 in this blog post I think https://adeshpande3.github.io/adeshpande3.github.io/Applying-Machine-Learning-to-March-Madness https://adeshpande3.github.io/adeshpande3.github.io/Applying...
- adeshpande3 8y agoYeah tonmoy linked to the blog post that had the predictions. Unfortunately, the model pretty much predicted a higher probability for the higher seeded team in the matchup which lead to some relatively expected predictions. If I remember correctly, it led to a pretty average percentile (50-60) when I submitted it to the ESPN leaderboards.