| A similar fun example is the distribution of Elo ratings on a chess site, e.g. here's the weekly distribution on Lichess for Bullet games (less than 3 minutes): https://lichess.org/stat/rating/distribution/bullet It's easy to understand why this happens: - Player ratings will fluctuate by small amounts as they win and lose individual games. - People are happy to stop playing when their rating is at e.g. 1503, but if it's 1497, they'd rather play just one more game than leave it that way. - At any given time, most accounts are not playing, so the distribution shows a bias towards values just over a 100 Elo threshold. The other neat thing is that you can see this effect reduce as you look at longer time controls: Blitz (less than 10 min): https://lichess.org/stat/rating/distribution/blitz Rapid (less than 30 min): https://lichess.org/stat/rating/distribution/rapid Which makes sense because the time and effort of gambling just one more game to get the rating back over the line is higher at the longer time controls. |