Scoring Bias in Springboard and Platform Diving: A Bayesian Approach to Revision of DD Tables |
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| Authors: | James E Bruno |
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| Institution: | Graduate School of Education , University of California , Los Angeles , CA , 90024 , USA |
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| Abstract: | Abstract Springboard and platform diving, unlike other sports competitions that use absolute performance measures, relies instead on a panel of judges to assess the aesthetic and technical quality of the athlete's performance. Using data from the 1983 U.S.A. Indoor Diving Nationals, regression analysis was used to determine if there was a statistically significant relationship between degree of difficulty (DD) and scores awarded for a dive. Surprisingly, the analysis revealed that as divers attempted higher degree of difficulty dives, judges became less inclined to award lower scores. Even though the average scores were lower for high DD dives, they were not low enough to compensate for the higher DD rating. Further analysis revealed that the women's competition had less scoring bias towards high DD dives than the men's competition. Even a small amount of scoring bias towards high DD dives is important since typically small total point differences in scores separate the finishing order of divers at a national or international competition. Bayesian analysis, based upon actual diver performance at national and international competitions, is suggested as one method of dealing with the problem of scoring bias towards high DD dives. Using this approach, probability of a score given the DD P(DD/Score)] is derived from the initially observed P(Scores/DD). Monte Carlo methods can then be used to simulate large numbers of divers performing at each DD level to obtain more precise DD measures for a particular dive. |
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| Keywords: | regression analysis degree of difficulty Bayesian analysis scoring bias Monte Carlo simulation |
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