This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.
Abstract Details
Activity Number:
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671
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Type:
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Contributed
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Date/Time:
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Thursday, August 5, 2010 : 10:30 AM to 12:20 PM
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Sponsor:
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Section on Statistics in Sports
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Abstract - #307798 |
Title:
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Motocycle Grand Prix (MotoGP) Lap Time Models
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Author(s):
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Leanne Streja*+ and Robert E. Weiss and Catherine A. Sugar
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Companies:
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University of California, Los Angeles School of Public Health and University of California, Los Angeles School of Public Health and University of California, Los Angeles School of Public Health
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Address:
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, Los Angeles, CA, 90095-177, United States
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Keywords:
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Motorcycle Racing ;
Motor Sports ;
Spline Models
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Abstract:
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I model lap times in Motorcycle Grand Prix (MotoGP) races as a function of lap, year, and rider characteristics such as grid position, years of racing experience, and prior race finish position. I develop graphs to identify how these characteristics influence lap times. Initially I fit an analysis of variance model with factors for lap, year, and rider. This model has many parameters which were not easily interpretable. Therefore I looked for a parsimonious lower-dimensional model with interpretable parameters that would capture the variability and provide a good explanation for the patterns of lap times. I simplified the model using cubic splines for the lap effect and continuous year. The model was fit to data from six different tracks.
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