Abstract Number:
2958
Submission Type:
Contributed Abstract
Contributed Abstract Type:
Speed
Participants:
Bob Downer (1)
Institutions:
(1) Grand Valley State University, N/A
First Author:
Presenting Author:
Abstract Text:
Highly drafted running backs are becoming increasingly rare in the NFL Running back contracts are also not typically as lucrative and lengthy as other positions due to injuries and lack of longevity in the league. As a potential instructional data set to compare traditional regression techniques and tree modeling, a data set was compiled that investigated NFL running back production in the period from 1999 to 2021. Responses such as years with original draft team and total career NFL rushing yards were investigated. Predictors included total college attempts, college conference and overall draft pick number. Results revealed some anticipated predictor significance as well as some less anticipated predictor importance. Furthermore, tree modeling revealed interesting ranges of predictor variables that might be useful in evaluating college players and predicting NFL performance.
Keywords:
regression|trees|modeling|prediction|teaching|sports
Sponsors:
Section on Statistics in Sports
Tracks:
Miscellaneous
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