This article explores why bookmaker odds often diverge from the actual statistical probabilities of sports outcomes.

It touches on topics like overrounds, market efficiency, and how bettor psychology and liquidity shape the implied probabilities.

I found it interesting because it connects data modeling, behavioral economics, and prediction theory — fields that are usually discussed separately.

Curious what the HN community thinks: – Are betting markets efficient in the long run? – How would you model the “bias” in odds vs true probability?