An Empirical Review of the Favourite In-Running Model

In the previous blog we reviewed a series of binary logits that modelled a favourite's probability of victory given its pre-game bookmaker-assessed head-to-head probability and its lead at the end of a particular quarter. There I provided just a single indication of the quality of those models: the accuracy with which they correctly predicted the final result of the game. That's a crude and very broad measure. In this blog we'll take a closer look at the empirical model fits to investigate their performance in games with different leads and probabilities.

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Hanging Onto a Favourite: Assessing a Favourite's In-Running Chances of Victory

Over the weekend I was paying particular attention to the in-running odds being offered on various games and remain convinced that punters overestimate the probability of the favourite ultimately winning, especially when the favourite trails.

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Setting a Target for Mean Absolute Prediction Error

Until today I've never known why an MAPE of 30 was a sensible target, other than that this seemed to be roughly the figure that the TAB Sportsbet bookmaker achieved each year.

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Line Fund Profitability and Probability Scores

Over on the Simulations blog as part of a more general investigation into the dynamics of the contest between punter and bookmaker in head-to-head wagering I've looked at the relationship between the probability score attained by the Head-to-Head Fund in each season and its profitability. What I found, among other things, was that the Fund's profitability was related not to the absolute probability score of the Fund algorithm, but to its probability score relative to the bookmaker's.

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Framing a Line Market: How Hard Can It Be?

This week, for the first time that I can remember, every line market has moved from its initial pricing on Wednesday at noon. More generally, I've noticed a greater sensitivity in the line market than in the head-to-head market and wondered why that might be the case.

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