Evaluating the Performance of Offensive Lineman in the NFL
In this paper we objectively measure the performance of an individual offensive lineman in the NFL. The existing literature proposes various measures that rely on subjective assessments of game film, but has yet to develop an objective methodology to evaluate performance. Using a variety of statistics related to an offensive lineman’s performance, we develop a framework to objectively analyze the overall performance of an individual offensive lineman and determine specific linemen who are overvalued or undervalued relative to their salary. We identify eight players across the 2013-2014 and 2014-2015 NFL seasons that are considered to be overvalued or undervalued and corroborate the results with existing metrics that are based on subjective evaluation. To the best of our knowledge, the techniques set forth in this work have not been utilized in previous works to evaluate the performance of NFL players at any position, including offensive linemen.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 240
 Oliver, Dean. (2011). Guide to the Total Quarterback Rating. Retrieved from http://espn.go.com/nfl/story/_/id/6833215/explaining-statistics-total-quarterback-rating.
 Burke, Brian. (2010). Win Probability Added (WPA) Explained. Retrieved from http://archive.advancedfootballanalytics.com/2010/01/win-probability-added-wpa-explained.html.
 Grading. (n.d.) Retrieved from https://www.profootballfocus.com/about/grading/
 Pro Football Reference. (2014). 2014 NFL All-Pros. Retrieved from http://www.pro-football-reference.com/years/2014/allpro.htm
 Pro Football Reference. (2014). 2014 NFL Pro Bowlers. Retrieved from http://www.pro-football-reference.com/years/2014/probowl.htm
 Pro Football Focus. (2015). Cumulative Guard Summary. Retrieved from https://www.profootballfocus.com/data/by_position.php?tab=by_position
 Hartigan, J. A., & Wong, M. A. (1979). Algorithm AS 136: A k-means clustering algorithm. Applied statistics, 100-108.
 Krzanowski, W. J., & Lai, Y. T. (1988). A criterion for determining the number of groups in a data set using sum-of-squares clustering. Biometrics, 23-34.
 McDonald, J. B. (1984). Some generalized functions for the size distribution of income. Econometrica: Journal of the Econometric Society, 647-663.
 Rousseeuw, P. J. (1987). Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics, 20, 53-65.
 Kaufman, L., & Rousseeuw, P. J. (1990). Finding groups in data: an introduction to cluster analysis. New York: Wiley Print
 Chapelle, Olivier, Bernhard Scholkopf, and Alexander Zien. "Semi-supervised learning (chapelle, o. et al., eds.; 2006)
[book reviews]." IEEE Transactions on Neural Networks 20.3 (2009): 542-542.