Metrics for Analyzing Top Offensive Lineman in This Years Nfl Draft

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Clint Warren

Mentor Department

Kinesiology & Recreation


When fans debate who the Most Valuable Player of the National Football League (NFL) is they tend to focus on the quarterback position. On some occasions other offensive skill position players like running backs and wide receivers will make it into the conversation. However, offensive lineman are never brought into these conversations. Offensive line play is critical to the success of football teams. Often, offensive line play will be analyzed in terms of the entire unit rather than the individual lineman that make up the unit of players. While surface-level statistics such as rushing yards, sacks allowed, and tackles for loss allowed are descriptive of an offensive line units play, these statistics do little to provide an assessment of individual linemen. The purpose of this research is to develop a metric that will help organizations scout and track individual offensive line play. Using game film from various college football teams this study will collect and analyze individual offensive lineman actions during games. Dummy variables will be used to quantify successful and unsuccessful lineman activities on each play. Lineman will be attributed a 1 for a successful assignment as well as a 0 for an unsuccessful assignment. These variables will serve as dependent variables in a logistic regression model. Dependent variables in this study will include factors such as play type, play side, and opponent attributes. Upon the conclusion of game film analysis, data collection, and metric development via logistic regression, this study will provide initial results as to individual players strengths and weaknesses, what style of offenses they might fit best in, and lastly who is the most 'ready' for NFL competition. This project will represent one of the first attempts to rank offensive lineman using an unbiased analytical approach. This study's findings will be relevant to football coaches, general managers, and the wider sport analytics community.



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