Estimating player value in American football using plus–minus models

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
R. Paul Sabin
Keyword(s):  
Quantitative Analysis ◽  
Field Performance ◽  
American Football ◽  
Football Players ◽  
Model Framework ◽  
Sports Analytics ◽  
Starting Point ◽  
Out Of Sample ◽  
Sample Testing ◽  
Player Performance

Abstract Calculating the value of football player’s on-field performance has been limited to scouting methods while data-driven methods are mostly limited to quarterbacks. A popular method to calculate player value in other sports are Adjusted Plus–Minus (APM) and Regularized Adjusted Plus–Minus (RAPM) models. These models have been used in other sports, most notably basketball (Rosenbaum, D. T. 2004. Measuring How NBA Players Help Their Teams Win. http://www.82games.com/comm30.htm#_ftn1; Kubatko, J., D. Oliver, K. Pelton, and D. T. Rosenbaum. 2007. “A Starting Point for Analyzing Basketball Statistics.” Journal of Quantitative Analysis in Sports 3 (3); Winston, W. 2009. Player and Lineup Analysis in the NBA. Cambridge, Massachusetts; Sill, J. 2010. “Improved NBA Adjusted +/− Using Regularization and Out-Of-Sample Testing.” In Proceedings of the 2010 MIT Sloan Sports Analytics Conference) to estimate each player’s value by accounting for those in the game at the same time. Football is less amenable to APM models due to its few scoring events, few lineup changes, restrictive positioning, and small quantity of games relative to the number of teams. More recent methods have found ways to incorporate plus–minus models in other sports such as Hockey (Macdonald, B. 2011. “A Regression-Based Adjusted Plus-Minus Statistic for NHL players.” Journal of Quantitative Analysis in Sports 7 (3)) and Soccer (Schultze, S. R., and C.-M. Wellbrock. 2018. “A Weighted Plus/Minus Metric for Individual Soccer Player Performance.” Journal of Sports Analytics 4 (2): 121–31 and Matano, F., L. F. Richardson, T. Pospisil, C. Eubanks, and J. Qin (2018). Augmenting Adjusted Plus-Minus in Soccer with Fifa Ratings. arXiv preprint arXiv:1810.08032). These models are useful in coming up with results-oriented estimation of each player’s value. In American football, many positions such as offensive lineman have no recorded statistics which hinders the ability to estimate a player’s value. I provide a fully hierarchical Bayesian plus–minus (HBPM) model framework that extends RAPM to include position-specific penalization that solves many of the shortcomings of APM and RAPM models in American football. Cross-validated results show the HBPM to be more predictive out of sample than RAPM or APM models. Results for the HBPM models are provided for both Collegiate and NFL football players as well as deeper insights into positional value and position-specific age curves.

scholarly journals Effect of Concussions on National Football League Quarterback Performance

2020 ◽  
Vol 8 (4) ◽  
pp. 19
Author(s):  
Elizabeth C. Heintz ◽  
Emily F. Foret ◽  
Jeremy J. Foreman
Keyword(s):  
Decision Making ◽  
National Football League ◽  
Field Performance ◽  
American Football ◽  
Return To Play ◽  
Football Players ◽  
Professional Football ◽  
Career Outcomes ◽  
Neurocognitive Performance ◽  
Player Performance

Background: Sports-related concussion (SRC) rates are higher in American football than any other sport; therefore, the effects of SRCs on professional football players is a prevalent topic. Previous research has shown that sustaining an SRC has negative financial and overall career outcomes for athletes and may cause performance decrements after an athlete returns to play, however, the results of previous research regarding athlete performance after returning from an SRC are mixed. While some studies found that player performance in the National Football League (NFL) was unaffected upon returning from an SRC, evidence also suggests significant scoring reductions in offensive players. Although previous research has found that NFL running backs and wide receivers perform at levels similar to their performance before sustaining an SRC, little is known about quarterback performance after an SRC. There is also evidence that SRCs decrease neurocognitive performance, a quality that is crucial, especially for quarterbacks. Objective: The purpose of this study is to examine changes in NFL quarterback performances upon return to play from an SRC. Method: Quarterback ratings (QBRs) and concussion data from 2012-2015 were used to determine if changes occurred in NFL quarterback performance following an SRC. Results: QBRs decreased by 13.3 points (p = 0.014) after quarterbacks return from an SRC. Conclusions: Changes in on-field performance for NFL quarterbacks after sustaining an SRC could be the result of neurocognitive decrements that impact quick reaction and decision-making skills, which may have greater impacts on quarterbacks than other positions.

Racial and Athletic Identity of African American Football Players

2009 ◽  
Author(s):  
Jesse A. Steinfeldt ◽  
Courtney Reed ◽  
Clint M. Steinfeldt
Keyword(s):  
African American ◽  
Athletic Identity ◽  
American Football ◽  
Football Players

scholarly journals Machine Learning in Futures Markets

2021 ◽  
Vol 14 (3) ◽  
pp. 119
Author(s):  
Fabian Waldow ◽  
Matthias Schnaubelt ◽  
Christopher Krauss ◽  
Thomas Günter Fischer
Keyword(s):  
Machine Learning ◽  
Futures Markets ◽  
Learning Models ◽  
Cross Sectional ◽  
Data Set ◽  
Statistical Arbitrage ◽  
Out Of Sample ◽  
Sample Testing ◽  
Arbitrage Strategy ◽  
Machine Learning Models

In this paper, we demonstrate how a well-established machine learning-based statistical arbitrage strategy can be successfully transferred from equity to futures markets. First, we preprocess futures time series comprised of front months to render them suitable for our returns-based trading framework and compile a data set comprised of 60 futures covering nearly 10 trading years. Next, we train several machine learning models to predict whether the h-day-ahead return of each future out- or underperforms the corresponding cross-sectional median return. Finally, we enter long/short positions for the top/flop-k futures for a duration of h days and assess the financial performance of the resulting portfolio in an out-of-sample testing period. Thereby, we find the machine learning models to yield statistically significant out-of-sample break-even transaction costs of 6.3 bp—a clear challenge to the semi-strong form of market efficiency. Finally, we discuss sources of profitability and the robustness of our findings.

Physical and performance characteristics related to starter status, position, and division in Japanese collegiate American-football players

2021 ◽  
pp. 1-8
Author(s):  
Junta Iguchi ◽  
Minoru Matsunami ◽  
Tatsuya Hojo ◽  
Yoshihiko Fujisawa ◽  
Kenji Kuzuhara ◽  
...  
Keyword(s):  
Performance Test ◽  
Vertical Jump ◽  
American Football ◽  
Football Players ◽  
Jump Height ◽  
Test Results ◽  
Repetition Maximum ◽  
Vertical Jump Height ◽  
Division 1 ◽  
And Performance

BACKGROUND: Few studies have investigated the variations in body composition and performance in Japanese collegiate American-football players. OBJECTIVE: To clarify what characterizes competitors at the highest levels – in the top division or on the starting lineup – we compared players’ body compositions and performance test results. METHODS: This study included 172 players. Each player’s body composition and performance (one-repetition maximum bench press, one-repetition maximum back squat, and vertical jump height) were measured; power was estimated from vertical jump height and body weight. Players were compared according to status (starter vs. non-starter), position (skill vs. linemen), and division (1 vs. 2). Regression analysis was performed to determine characteristics for being a starter. RESULTS: Players in higher divisions and who were starters were stronger and had more power, greater body size, and better performance test results. Players in skill positions were relatively stronger than those in linemen positions. Vertical jump height was a significant predictor of being a starter in Division 1. CONCLUSION: Power and vertical jump may be a deciding factor for playing as a starter or in a higher division.

Player age and initial helmet contact among American football players

2021 ◽  
Vol 47 ◽  
pp. 115-118
Author(s):  
David X. Wang ◽  
Anthony M. Napoli ◽  
Alex R. Webb ◽  
Christine Etzel ◽  
Janette Baird ◽  
...  
Keyword(s):  
American Football ◽  
Football Players

On-Field Performance of an Instrumented Mouthguard for Detecting Head Impacts in American Football

2020 ◽  
Vol 48 (11) ◽  
pp. 2599-2612
Author(s):  
Lee F. Gabler ◽  
Samuel H. Huddleston ◽  
Nathan Z. Dau ◽  
David J. Lessley ◽  
Kristy B. Arbogast ◽  
...  
Keyword(s):  
Field Performance ◽  
American Football ◽  
Head Impacts

Effect of Turf Toe on Foot Contact Pressures in Professional American Football Players

2009 ◽  
Vol 30 (5) ◽  
pp. 405-409 ◽  
Author(s):  
Robert H. Brophy ◽  
Seth C. Gamradt ◽  
Scott J. Ellis ◽  
Ronnie P. Barnes ◽  
Scott A. Rodeo ◽  
...  
Keyword(s):  
Body Mass Index ◽  
National Football League ◽  
Peak Pressure ◽  
American Football ◽  
Football Players ◽  
Plantar Pressures ◽  
History Of ◽  
Turf Toe ◽  
The Relationship ◽  
Contact Pressures

Background: The relationship between turf toe and plantar foot pressures has not been extensively studied. Two hypotheses were tested in a cohort of professional American football players: first, that a history of turf toe is associated with increased peak hallucal and first metatarsophalangeal (MTP) plantar pressures; second, that decreased range of motion (ROM) of the first MTP correlates with increased peak hallucal and first MTP plantar pressures. Materials and Methods: Forty-four athletes from one National Football League (NFL) team were screened for a history of turf toe during preseason training. Dorsal passive MTP ROM and dynamic plantar pressures were measured in both feet of each player. Anatomical masking was used to assess peak pressure at the first MTP and hallux. Results: First MTP dorsiflexion was significantly lower in halluces with a history of turf toe (40.6 ± 15.1 degrees versus 48.4 ± 12.8 degrees, p = 0.04). Peak hallucal pressures were higher in athletes with turf toe (535 ± 288 kPa versus 414 ± 202 kPa, p = 0.05) even after normalizing for athlete body mass index ( p = 0.0003). Peak MTP pressure was not significantly different between the two groups tested. First MTP dorsiflexion did not correlate with peak hallucal or first MTP pressures. Conclusion: This study showed that turf toe is associated with decreased MTP motion. In addition, increased peak hallucal pressures were found. Further study is warranted to determine whether these pressures correlate with the severity of symptoms or progression of turf toe to first MTP arthritis.

Athletic Scholarships in Intercollegiate Football

2011 ◽  
Vol 13 (5) ◽  
pp. 515-535 ◽  
Author(s):  
Joshua D. Pitts ◽  
Jon Paul Rezek
Keyword(s):  
High School ◽  
Intercollegiate Athletics ◽  
Negative Binomial ◽  
Negative Relationship ◽  
Field Performance ◽  
The United States ◽  
Football Players ◽  
High School Football ◽  
Football Coaches ◽  
Athletic Scholarships

Despite the financial and cultural importance of intercollegiate athletics in the United States, there is a paucity of research into how athletic scholarships are awarded. In this article, the authors empirically examine the factors that universities use in their decision to offer athletic scholarships to high school football players. Using a Zero-Inflated Negative Binomial (ZINB) model, the authors find a player’s weight, height, body mass index (BMI), race, speed, on-the-field performance, and his high school team’s success often have large and significant impacts on the number of scholarship offers he receives. There is also evidence of a negative relationship between academic performance and scholarship offers. In addition, the authors find evidence of a scholarship premium for players from Florida and Texas. The results also show that running backs, wide receivers, and defensive backs appear to generate the most attention from college football coaches, other things equal.

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