A Simple Random Walk Model for Predicting Track and Field World Records
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Jeff T Terpstra
This article proposes a simple model for the prediction of track and field world records. It is best characterized as a one-sided random walk model with a mixture distribution for the error term. The mixture distribution contains one discrete and one continuous component. The discrete piece pertains to the probability that a record is broken and can be modeled as a function of time. The continuous component corresponds to a positive-valued random variable that may also depend on time and essentially models the amount by which a record is broken. The proposed model and corresponding inference procedures are grounded in maximum likelihood principles. Monte Carlo techniques can be used to obtain prediction intervals for future records. Data for the men's 100 meter dash is used to illustrate the proposed methodology.
©2011 Walter de Gruyter GmbH & Co. KG, Berlin/Boston
Articles in the same Issue
- Article
- A Starting Point for Analyzing Basketball Statistics
- Evaluating Throwing Ability in Baseball
- Football Rating Systems for Top-Level Competition: A Critical Survey
- A Simple Random Walk Model for Predicting Track and Field World Records
- Inter-arrival Times of Goals in Ice Hockey
- On Probabilistic Excitement of Sports Games
Articles in the same Issue
- Article
- A Starting Point for Analyzing Basketball Statistics
- Evaluating Throwing Ability in Baseball
- Football Rating Systems for Top-Level Competition: A Critical Survey
- A Simple Random Walk Model for Predicting Track and Field World Records
- Inter-arrival Times of Goals in Ice Hockey
- On Probabilistic Excitement of Sports Games
