Statistics Papers

Document Type

Journal Article

Date of this Version

10-2014

Publication Source

Journal of Quantitative Analysis in Sports

Volume

10

Issue

4

Start Page

381

Last Page

396

DOI

10.1515/jqas-2013-0134

Abstract

National Football League teams have complex drafting strategies based on college and combine performance that are intended to predict success in the NFL. In this paper, we focus on the tight end position, which is seeing growing importance as the NFL moves towards a more passing-oriented league. We create separate prediction models for 1. the NFL Draft and 2. NFL career performance based on data available prior to the NFL Draft: college performance, the NFL combine, and physical measures. We use linear regression and recursive partitioning decision trees to predict both NFL draft order and NFL career success based on this pre-draft data. With both modeling approaches, we find that the measures that are most predictive of NFL draft order are not necessarily the most predictive measures of NFL career success. This finding suggests that we can improve upon current drafting strategies for tight ends. After factoring the salary cost of drafted players into our analysis in order to predict tight ends with the highest value, we find that size measures (BMI, weight, height) are over-emphasized in the NFL draft.

Copyright/Permission Statement

The article was originally published by De Gruyter Publishing and is available at: https://www.degruyter.com/view/j/jqas.2014.10.issue-4/jqas-2013-0134/jqas-2013-0134.xml

Keywords

football, prediction, regression

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Date Posted: 27 November 2017

This document has been peer reviewed.