I’ve noticed the Data Golf model seems to like the rounds 1-3 leader’s odds of winning relative to what the books have. For example, this week, a bet on Niemann to win (3 stroke lead after round 1) is +0.16 EV on most books. Last week, a bet on Theegala to win was about +0.40 EV on a few books after round 2. Is there any particular reason for this, and should I assume these are good bets to make?
We adjust for ‘pressure’ effects, i.e. downgrading players’ predicted skill as a function of their position on the leaderboard. Full blog here. However we don’t make player-specific adjustments. The market seems to downgrade win probabilities for non-superstar players a lot more than we do, so we will often show value on the leaders as long as they aren’t top players.
As for whether they are good bets… I’m not sure. We had a lot of success betting them 2-3 years ago, but last year wasn’t a good year for in-play outrights. I plan on revisiting our pressure adjustments to see if there are any tweaks we should be making that we currently aren’t.
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Cool, that all makes sense. Thank you for the response.