Alamar, B. 2010. “Measuring Risk in NFL Playcalling.” *Journal of Quantitative Analysis in Sports* 6(2). https://doi.org/10.2202/1559-0410.1235.

Albert, J. 2006. “Pitching Statistics, Talent and Luck, and the Best Strikeout Seasons of All-Time.” *Journal of Quantitative Analysis in Sports* 2(1). https://doi.org/10.2202/1559-0410.1014.

Balreira, E. C., B. K. Miceli, and T. Tegtmeyer. 2014. “An Oracle Method to Predict NFL Games.” *Journal of Quantitative Analysis in Sports* 10:183–196. Google Scholar

Bates, D., M. Machler, B. Bolker, and S. Walker. 2015: “Fitting Linear Mixed-Effects Models Using lme4.” *Journal of Statistical Software* 67:1–48. Google Scholar

Baumer, B., and P. Badian-Pessot. 2017. “Evaluation of Batters and Base Runners”. Pp. 1–37 in *Handbook of Statistical Methods and Analyses in Sports*, edited by J. Albert, M. E. Glickman, T. B. Swartz and R. H. Koning, Boca Raton, Florida: CRC Press. Google Scholar

Baumer, B., S. Jensen, and G. Matthews. 2015. “Openwar: An Open Source System for Evaluating Overall Player Performance in Major League Baseball”. *Journal of Quantitative Analysis in Sports* 11:69–84. Google Scholar

Becker, A. and X. A. Sun. 2016. “An Analytical Approach for Fantasy Football Draft and Lineup Management”. *Journal of Quantitative Analysis in Sports* 12:17–30. Google Scholar

Brooks, D., H. Pavlidis, and J. Judge. 2015. “Moving Beyond Wowy: A Mixed Approach to Measuring Catcher Framing.” URL https://www.baseballprospectus.com/news/article/25514/moving-beyond-wowy-a-mixed-approach-to-measuring-catcher-framing/.

Burke, B. 2009. “Expected Point Values”. URL http://archive.advancedfootballanalytics.com/2009/12/expected-point-values.html.

Burke, B. 2014. “Expected Points and Expected Points Added Explained”. URL http://www.advancedfootballanalytics.com/index.php/home/stats/stats-explained/expected-points-and-epa-explained.

Cafarelli, R., C. J. Rigdon, and S. E. Rigdon. 2012. “Models for Third Down Conversion in the National Football League.” *Journal of Quantitative Analysis in Sports* 8(3). https://doi.org/10.1515/1559-0410.1383.

Carroll, B., P. Palmer, J. Thorn, and D. Pietrusza. 1988. *The Hidden Game of Football*. New York, New York: Total Sports, Inc. Google Scholar

Carter, V. and R. Machol. 1971. “Operations Research on Football”. *Operations Research* 19:541–544. CrossrefGoogle Scholar

Causey, T. 2013. “Building a Win Probability Model Part 1”. URL http://thespread.us/building-a-win-probability-model-part-1.html.

Causey, T. 2015. “Expected Points Part 1: Building a Model and Estimating Uncertainty”. URL http://thespread.us/expected-points.html.

Citrone, N. and S. L. Ventura. 2017. “A Statistical Analysis of the NFL Draft: Valuing Draft Picks and Predicting Future Player Success”. Presented at the Joint Statistical Meetings. Google Scholar

Clark, T. K., A. W. Johnson, and A. J. Stimpson. 2013. “Going for Three: Predicting the Likelihood of Field Goal Success with Logistic Regression”. *MIT Sloan Sports Analytics Conference*. Google Scholar

Dasarathy, B. V. 1991. *Nearest Neighbor (NN) Norms: NN Pattern Classification Techniques*. Google Scholar

Deshpande, S. K. and S. T. Jensen. 2016. “Estimating an NBA Player’s Impact on his Team’s Chances of Winning”. *Journal of Quantitative Analysis in Sports* 12:51–72. Google Scholar

Drinen, D. 2013. “Approximate Value: Methodolgy.” URL https://www.sports-reference.com/blog/approximate-value-methodology/.

Eager, E. A., G. Chahrouri, and S. Palazzolo. 2017. “Using PFF Grades to Cluster Quarterback Performance”. *Pro Football Focus Research and Development Journal* 1:4–14. Google Scholar

Elmore, R. and P. DeWitt. 2017. *Ballr: Access to Current and Historical Basketball Data*. URL https://CRAN.R-project.org/package=ballr, r package version 0.1.1.

Franks, A. M., A. D’Amour, D. Cervone, and L. Bornn. 2017. “Meta-Analytics: Tools for Understanding the Statistical Properties of Sports Metrics”. *Journal of Quantitative Analysis in Sports* 12:151–165. Google Scholar

Gelman, A. and J. Hill. 2007. *Data Analysis Using Regression and Multilevel/Hierarchical Models*. Cambridge, United Kingdom: Cambridge University Press. Google Scholar

Goldner, K. 2012. “A Markov Model of Football: Using Stochastic Processes to Model a Football Drive”. *Journal of Quantitative Analysis in Sports* 8(1). https://doi.org/10.1515/1559-0410.1400.

Goldner, K. 2017. “Situational Success: Evaluating Decision-Making in Football”. Pp. 183–198 in *Handbook of Statistical Methods and Analyses in Sports*, edited by J. Albert, M. E. Glickman, T. B. Swartz, and R. H. Koning. Boca Raton, Florida: CRC Press. Google Scholar

Gramacy, R. B., M. A. Taddy, and S. T. Jensen. 2013. “Estimating Player Contribution in Hockey with Regularized Logistic Regression”. *Journal of Quantitative Analysis in Sports* 9:97–111. CrossrefGoogle Scholar

Grimshaw, S. D. and S. J. Burwell. 2014. “Choosing the most Popular NFL Games in a Local tv Market”. *Journal of Quantitative Analysis in Sports* 10:329–343. Google Scholar

Horowitz, M., R. Yurko, and S. L. Ventura. 2017. *nflscrapR: Compiling the NFL Play-by-Play API for Easy use in R*. URL https://github.com/maksimhorowitz/nflscrapR, r package version 1.4.0.

James, B. 2017. “Judge and Altuve.” URL https://www.billjamesonline.com/judge_and_altuve/.

Jensen, J. A. and B. A. Turner. 2014. “What if Statisticians Ran College Football? A Re-Conceptualization of the Football Bowl Subdivision”. *Journal of Quantitative Analysis in Sports* 10:37–48. Google Scholar

Jensen, S., K. E. Shirley, and A. Wyner. 2009. “Bayesball: A Bayesian Hierarchical Model for Evaluating Fielding in Major League Baseball”. *The Annals of Applied Statistics* 3:491–520. CrossrefGoogle Scholar

Katz, S. and B. Burke. 2017. “How is Total QBR Calculated? We Explain our Quarterback Rating”. URL http://www.espn.com/blog/statsinfo/post/_/id/123701/how-is-total-qbr-calculated-we-explain-our-quarterback-rating.

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). https://doi.org/10.2202/1559-0410.1070.

Lahman, S. 1996–2017. *Lahman’s Baseball Database*. URL http://www.seanlahman.com/baseball-archive/statistics/.

Lillibridge, M. 2013. “The Anatomy of a 53-Man Roster in the NFL”. URL http://bleacherreport.com/articles/1640782-the-anatomy-of-a-53-man-roster-in-the-nfl.

Lock, D. and D. Nettleton. 2014. “Using Random Forests to Estimate Win Probability before Each Play of an NFL Game”. *Journal of Quantitative Analysis in Sports* 10:1–9. Google Scholar

Lopez, M. 2017. “All Win Probability Models are Wrong Some are Useful.” URL https://statsbylopez.com/2017/03/08/all-win-probability-models-are-wrong-some-are-useful/.

Macdonald, B. 2011. “A Regression-Based Adjusted Plus-Minus Statistic for NHL Players”. *Journal of Quantitative Analysis in Sports* 7(3). https://doi.org/10.2202/1559-0410.1284.

Martin, R., L. Timmons, and M. Powell. 2017. “A Markov Chain Analysis of NFL Overtime Rules”. *Journal of Sports Analytics* 4:95–105. Google Scholar

Meers, K. 2011. “How to Value NFL Draft Picks”. URL https://harvardsportsanalysis.wordpress.com/2011/11/30/how-to-value-nfl-draft-picks/.

Morris, B. 2017. “Running Backs are Finally Getting Paid What Theyre Worth.” URL https://fivethirtyeight.com/features/running-backsare-finally-getting-paid-what-theyre-worth/.

Mulholland, J. and S. T. Jensen. 2014. “Predicting the Draft and Career Success of Tight Ends in the National Football League”. *Journal of Quantitative Analysis in Sports* 10:381–396. Google Scholar

Oliver, D. 2011. “Guide to the Total Quarterback Rating.” URL http://www.espn.com/nfl/story/_/id/6833215/explaining-statistics-total-quarterback-rating.

Paine, N. 2015. “Bryce Harper should have Made $73 Million More”. URL https://fivethirtyeight.com/features/bryce-harper-nl-mvp-mlb/.

Pasteur, D. and K. Cunningham-Rhoads. 2014. “An Expectation-Based Metric for NFL Field Goal Kickers”. *Journal of Quantitative Analysis in Sports* 10:49–66. Google Scholar

Piette, J. and S. Jensen. 2012. “Estimating Fielding Ability in Baseball Players Over Time”. *Journal of Quantitative Analysis in Sports* 8(3). https://doi.org/10.1515/1559-0410.1463.

Pro-Football-Reference. 2018. “Football Glossary and Football Statistics Glossary”. URL https://www.pro-football-reference.com/about/glossary.htm.

Quealy, K., T. Causey, and B. Burke. 2017. “4th Down Bot: Live Analysis of Every n.f.l. 4th Down”. URL http://nyt4thdownbot.com/.

R Core Team. 2017. *R: A Language and Environment for Statistical Computing*. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/.

Romer, D. 2006. “Do Firms Maximize? Evidence from Professional Football”. *Journal of Political Economy* 114:340–365. CrossrefGoogle Scholar

Rosenbaum, D. T. 2004. “Measuring how NBA Players Help their Teams Win”. URL http://www.82games.com/comm30.htm.

Schatz, A. 2003. “Methods to Our Madness”. URL http://www.footballoutsiders.com/info/methods.

Schoenfield, D. 2012. “What we Talk about when we Talk about War”. URL http://espn.go.com/blog/sweetspot/post/_/id/27050/what-we-talk-about-when-we-talk-about-war.

Sievert, C. 2015. *pitchRx: Tools for Harnessing ’MLBAM’ ’Gameday’ Data and Visualizing ’pitchfx’*. URL https://CRAN.R-project.org/package=pitchRx, r package version 1.8.2.

Smith, D., S. Siwoff, and D. Weiss. 1973. “Nfl’s Passer Rating.” URL http://www.profootballhof.com/news/nfl-s-passer-rating.

Snyder, K. and M. Lopez. 2015. “Consistency, Accuracy, and Fairness: A Study of Discretionary Penalties in the NFL”. *Journal of Quantitative Analysis in Sports* 11:219–230. Google Scholar

Tango, T. 2017. “War Podcast”. URL http://tangotiger.com/index.php/site/comments/war-podcast.

Tango, T., M. Lichtman, and A. Dolphin. 2007. *The Book: Playing the Percentages in Baseball*. Washington, D.C: Potomac Book, Inc. Google Scholar

Thomas, A. C. and S. L. Ventura. 2015. “The Road to War”. URL http://blog.war-on-ice.com/index.html%3Fp=429.html.

Thomas, A. and S. L. Ventura. 2017. *nhlscrapr: Compiling the NHL Real Time Scoring System Database for easy use in R*. URL https://CRAN.R-project.org/package=nhlscrapr, r package version 1.8.1.

Thomas, A. C., S. L. Ventura, S. T. Jensen, and S. Ma. 2013. “Competing Process Hazard Function Models for Player Ratings in Ice Hockey”. *The Annals of Applied Statistics* 7:1497–1524. CrossrefGoogle Scholar

Turkenkopf, D., H. Pavlidis, and J. Judge. 2015. “Prospectus Feature: Introducing Deserved Run Average (DRA) and all its Friends”. URL https://www.baseballprospectus.com/news/article/26195/prospectus-feature-introducing-deserved-run-average-draand-all-its-friends/.

Wakefield, K. and A. Rivers. 2012. “The Effect of Fan Passion and Official League Sponsorship on Brand Metrics: A Longitudinal Study of Official NFL Sponsors and Roo”. *MIT Sloan Sports Analytics Conference*. Google Scholar

Yam, D. R. and M. J. Lopez. 2018. “Quantifying the Causal Effects of Conservative Fourth down Decision Making in the National Football League.” URL https://statsbylopez.files.wordpress.com/2018/01/quantifying-causal-effects.pdf, under Review.

Yurko, R., S. Ventura, and M. Horowitz. 2017. “Nfl Player Evaluation Using Expected Points Added with Nflscrapr”. Presented at the Great Lakes Sports Analytics Conference. Google Scholar

Zhou, E. and S. Ventura. 2017. “Wins and Point Differential in the NFL”. URL https://www.cmusportsanalytics.com/wins-point-differential-nfl/.

## Comments (0)

General note:By using the comment function on degruyter.com you agree to our Privacy Statement. A respectful treatment of one another is important to us. Therefore we would like to draw your attention to our House Rules.