Scoring strategies for the underdog: A general, quantitative method for determining optimal sports strategies
When facing a heavily-favored opponent, an underdog must be willing to assume greater-than-average risk. In statistical language, one would say that an underdog must be willing to adopt a strategy whose outcome has a larger-than-average variance. The difficult question is how much risk a team should be willing to accept. This is equivalent to asking how much the team should be willing to sacrifice from its mean score in order to increase the score`s variance. In this paper a general analytical method is developed for addressing this question quantitatively. Under the assumption that every play in a game is statistically independent, both the mean and the variance of a team`s offensive output can be described using the binomial distribution. This allows for direct calculations of the winning probability when a particular strategy is employed, and therefore allows one to calculate optimal offensive strategies. This paper develops this method for calculating optimal strategies exactly and then presents a simple heuristic for determining whether a given strategy should be adopted. A number of interesting and counterintuitive examples are then explored, including the merits of stalling for time, the run/pass/Hail Mary choice in football, and the correct use of Hack-a-Shaq.
© Copyright 2011 Journal of Quantitative Analysis in Sports. de Gruyter. All rights reserved.
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| Notations: | training science |
| Published in: | Journal of Quantitative Analysis in Sports |
| Language: | English |
| Published: |
2011
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| Volume: | 7 |
| Issue: | 4 |
| Pages: | Art. 11 |
| Document types: | article |
| Level: | advanced |