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01-03-2015 | Original Paper

Delusions of Expertise: The High Standard of Proof Needed to Demonstrate Skills at Horserace Handicapping

Authors: Matthew Browne, Matthew J. Rockloff, Alex Blaszcynski, Clive Allcock, Allen Windross

Published in: Journal of Gambling Studies | Issue 1/2015

Abstract

Gamblers who participate in skill-oriented games (such as poker and sports-betting) are motivated to win over the long-term, and some monitor their betting outcomes to evaluate their performance and proficiency. In this study of Australian off-track horserace betting, we investigated which levels of sustained returns would be required to establish evidence of skill/expertise. We modelled a random strategy to simulate ‘naïve’ play, in which equal bets were placed on randomly selected horses using a representative sample of 211 weekend races. Results from a Monte Carlo simulation yielded a distribution of return-on-investments for varying number of bets (N), showing surprising volatility, even after a large number of repeated bets. After adjusting for the house advantage, a gambler would have to place over 10,000 bets in individual races with net returns exceeding 9 % to be reasonably considered an expert punter (α = .05). Moreover, a record of fewer bets would require even greater returns for demonstrating expertise. As such, validated expertise is likely to be rare among race bettors. We argue that the counter-intuitively high threshold for demonstrating expertise by tracking historical performance is likely to exacerbate known cognitive biases in self-evaluation of expertise.

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This bias against the player may take form of share-transaction fees, or the operator dividend incorporated into racing totalisator systems. By definition, at least 50 % (probably far more, since the distribution of expertise/knowledge tends to be positively skewed) of players participating in games with a skill component do not possess above-average knowledge or proficiency. Furthermore, above-average proficiency may not be sufficient to overcome the intrinsic bias against the player in the return schedule.

Note that, by this definition, expert strategies may still yield long-term negative aggregate returns, if the benefit conferred by the expert strategy is outweighed by the intrinsic weighting of the game against the player.

Equal prior probabilities assumes that non-expert players Other forms of random play may also be defined. Possibilities include using probabilities determined by starter number, starting odds, or by a particular player’s prior probabilities of with respect to starter or odds. These would generally result in a more sensitive benchmark for comparison (at the expense of increased complexity), so the impact of varying the random model might warrant further investigation.

Once again, more complex random models may be defined that place variable bet sizes, potentially matched according to the distribution of bet sizes for the particular play record under consideration. For clarity, we omit such elaborations in the present paper.

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Title: Delusions of Expertise: The High Standard of Proof Needed to Demonstrate Skills at Horserace Handicapping
Authors: Matthew Browne
Matthew J. Rockloff
Alex Blaszcynski
Clive Allcock
Allen Windross
Publication date: 01-03-2015
Publisher: Springer US
Published in: Journal of Gambling Studies / Issue 1/2015
Electronic ISSN: 1573-3602
DOI: https://doi.org/10.1007/s10899-013-9420-7

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Delusions of Expertise: The High Standard of Proof Needed to Demonstrate Skills at Horserace Handicapping

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