Overall, this paper approached the analysis of player prediction in a very different way than others have done in the past with a longitudinal analysis of player production and word analysis. In analyzing players throughout their careers, we have seen the quickly diminishing returns for experience. Whereas in other occupations experience has positive returns for a prolonged period of time, we can see through our analyses that productivity begins to decline after only a few years. We have also looked at the impact of word characteristics, in this case acting as proxy for football traits in players, in scouting reports on various different factors of player evaluation. Specifically, in quarterbacks, we have discovered that although NFL teams might value characteristics such as a quick release and throwing catchable balls while ignoring accuracy, what actually drives higher quarterback performance is the ability to throw accurate passes and that an inability in throwing short passes significantly hurts quarterback performance.
In terms of contribution to the existing literature, the word characteristics are by far the most interesting component of this paper as it combines both the quantitative aspect of player analysis in physical characteristics and the qualitative aspect of a player’s football characteristics in scouting reports. To show the explanatory power/joint significance of the word characteristics
45
as a group, F-tests were conducted for each of the expected return, played/produced probit, and panel approximate value models. As you can see in Tables 20-23 below, in 36 of the 40
regressions, the word characteristics were significant at the 10% level, and in 27 of the 40 regressions, the word characteristics were significant at the 5% level.
[INSERT TABLE 20] [INSERT TABLE 21] [INSERT TABLE 22] [INSERT TABLE 23]
Moreover, through our theoretical model, we have examined the impact of drafting ability, measured by the sum of differences in expected return and actual return by offense and defense, has on offensive and defensive performance. The models tell us that, controlling for the ability of the individual player outputs, drafting ability does not have a significant impact on performance. It’ll be an interesting topic to explore in future papers how to specifically isolate the effects of drafting ability on team success without the confounding factors of individual player inputs that lower the significance of the draft ability variable.
In conclusion, despite the limitations of the scouting report data, it is nonetheless clear that there are plenty of insights that can be unearthed through this approach. In addition, what this study aimed to do was not lay out definitive results for each characteristic in each player, but rather, lay down the framework for more research to be conducted through use of more robust and numerous scouting reports. It is clear that there is more than enough room for more research and analysis to be conducted, where natural language processing and economic model work in conjunction to provide significant and interesting results.
46 VI. Bibliography
1. Berri, David J., and Rob Simmons. "Catching a Draft: On the Process of Selecting Quarterbacks in the National Football League Amateur Draft." Journal of Productivity Analysis 35, no. 1 (2011): 37-49. http://www.jstor.org/stable/23883795.
2. Binney, Zachary. "NFL Injuries Part IV: Variation by Position." Football Outsiders. October 23, 2015. Accessed March 05, 2017. http://www.footballoutsiders.com/stat- analysis/2015/nfl-injuries-part-iv-variation-position.
3. Boulier, Bryan L., H.O. Stekler, Jason Coburn and Timothy Rankins (2010),`Evaluating National Football League draft choices: The passing game',Inter- national Journal of Forecasting 26(3), 589-605.
4. Drinen, Doug. "Approximate Value: Methodology." Approximate Value: Methodology » Pro-football-reference.com blog. January 15, 2008. Accessed March 13, 2017. http://www.pro-football-reference.com/blog/indexd961.html?page_id=8061.
5. Lyons, Robert S and Don Shula. On Any Given Sunday: A Life of Bert Bell. Philadelphia: Temple University Press,U.S., 2009.
6. Manning, Christopher D., Mihai Surdeanu, John Bauer, Jenny Finkel, Steven J. Bethard, and David McClosky. 2014. The Stanford CoreNLP Natural Language Processing Toolkit In Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics: System Demonstrations, pp. 55-60.
7. Massey, C., & Thaler, R. “Overconfidence vs. market efficiency in the National Football League.” National Bureau of Economic Research, no. w11270 (2005).
8. "Methods To Our Madness." Football Outsiders . Accessed March 13, 2017. http://www.footballoutsiders.com/info/methods.
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9. Mogotsi, I.C. (2009) ‘Christopher D. Manning, Prabhakar Raghavan, and Hinrich Schütze: Introduction to information retrieval’, Information Retrieval, 13(2), pp. 192–195. doi: 10.1007/s10791-009-9115-y.
10.Nicholson, W. and Snyder, C.M. (2011) Microeconomic theory: Basic principles and extensions (with economic applications, Infotrac printed access card) - 11th edition. 11th edn. Boston, MA, United States: CENGAGE Learning Custom Publishing.
11.Oates, Tom. "Russell Wilson's height a big issue for scouts." Madison.com. May 23, 2012. Accessed February 28, 2017. http://host.madison.com/sports/columnists/tom_oates/tom- oates-russell-wilson-s-height-a-big-issue-for/article_544b7734-640e-11e1-809b-
0019bb2963f4.html.
12.Reynolds, Z., Bonds, T., Thompson, S., & LeCrom, C. W. (2015). Deconstructing the draft: An evaluation of the NFL draft as a predictor of team success. Journal of Applied Sport Management, 7(3) Retrieved from http://js.sagamorepub.com/jasm/article/view/5695. 13.Stuart, Chase. “Creating a Draft Value Chart, Part II.” November 19, 2012. Accessed
February 28, 2017. http://www.footballperspective.com/creating-a-draft-value-chart-part- ii/.
14.“ESPN Sees Slight Bump for Draft Viewership, While NFL Net Sets Weekend Records.”
May 2, 2016. Accessed February 28, 2017.
http://www.sportsbusinessdaily.com/Daily/Issues/2016/05/02/Media/NFL-Draft-TV.aspx. 15.Wolf, A., Malmgren, D. and Stringer, M. (2012) The chance of a bust in the NFL draft.
Available at: https://datascopeanalytics.com/blog/the-chance-of-a-bust-in-the-nfl-draft/ (Accessed: 28 February 2017).
Figure 1: Approximate Value by Draft Slot
Source: (Stuart 2012)
Figure 2: Chance a Player is a Bust
Source: (Wolf, Malmgren, and Stringer, 2012)
Table 0: Position Abbreviation
Abbreviation Full Word
QB Quarterback
RB Runningback
WR Wide Receiver
TE Tight Ends
OL Offensive Lineman
INT Interior Defensive Lineman
EDGE EDGE Defender
CB Cornerback