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Related papers: Predicting play calls in the National Football Lea…

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Based on NFL game data we try to predict the outcome of a play in multiple different ways. An application of this is the following: by plugging in various play options one could determine the best play for a given situation in real time.…

Machine Learning · Computer Science 2016-01-05 Brendan Teich , Roman Lutz , Valentin Kassarnig

Continuous-time assessments of game outcomes in sports have become increasingly common in the last decade. In American football, only discrete-time estimates of play value were possible, since the most advanced public football datasets were…

We study the relationship between social media output and National Football League (NFL) games, using a dataset containing messages from Twitter and NFL game statistics. Specifically, we consider tweets pertaining to specific teams and…

Social and Information Networks · Computer Science 2013-10-28 Shiladitya Sinha , Chris Dyer , Kevin Gimpel , Noah A. Smith

American football is an increasingly popular sport, with a growing audience in many countries in the world. The most watched American football league in the world is the United States' National Football League (NFL), where every offensive…

Machine Learning · Statistics 2021-09-17 Gustavo Pompeu da Silva , Rafael de Andrade Moral

Do NFL teams make rational decisions? What factors potentially affect the probability of wining a game in NFL? How can a team come back from a demoralizing interception? In this study we begin by examining the hypothesis of rational…

Applications · Statistics 2017-02-08 Konstantinos Pelechrinis , Evangelos Papalexakis

Predicting the results of sport matches and competitions is an arising research field, benefiting from the growing amount of available data and the novel data analytics techniques. Excellent forecasts can be achieved by advanced machine…

Applications · Statistics 2015-11-20 Giuseppe Jurman

Although the data-driven analysis of football players' performance has been developed for years, most research only focuses on the on-ball event including shots and passes, while the off-ball movement remains a little-explored area in this…

Machine Learning · Computer Science 2023-09-06 Yisheng Pei , Varuna De Silva , Mike Caine

Most historical National Football League (NFL) analysis, both mainstream and academic, has relied on public, play-level data to generate team and player comparisons. Given the number of oft omitted variables that impact on-field results,…

Applications · Statistics 2020-05-14 Michael J. Lopez

With the vast amount of data collected on football and the growth of computing abilities, many games involving decision choices can be optimized. The underlying rule is the maximization of an expected utility of outcomes and the law of…

Machine Learning · Computer Science 2021-03-15 Preston Biro , Stephen G. Walker

Predicting outcomes in sports is important for teams, leagues, bettors, media, and fans. Given the growing amount of player tracking data, sports analytics models are increasingly utilizing spatially-derived features built upon player…

Machine Learning · Computer Science 2022-07-29 Peter Xenopoulos , Claudio Silva

Unlike other major professional sports, American football lacks comprehensive statistical ratings for player evaluation that are both reproducible and easily interpretable in terms of game outcomes. Existing methods for player evaluation in…

Applications · Statistics 2018-07-13 Ronald Yurko , Samuel Ventura , Maksim Horowitz

We investigated the performance of the collective intelligence of NFL fans predicting the outcome of games as realized through the Vegas betting lines. Using data from 2560 games (all post-expansion, regular- and post-season games from…

Social and Information Networks · Computer Science 2012-11-19 Greg Szalkowski , Michael L. Nelson

Sports competitions are widely researched in computer and social science, with the goal of understanding how players act under uncertainty. While there is an abundance of computational work on player metrics prediction based on past…

Computation and Language · Computer Science 2020-07-02 Nadav Oved , Amir Feder , Roi Reichart

In sports analytics, player tracking data have driven significant advancements in the task of player evaluation. We present a novel generative framework for evaluating the observed frame-by-frame player positioning against a distribution of…

Applications · Statistics 2026-03-24 Quang Nguyen , Ronald Yurko

This paper considers the use of observed and predicted match statistics as inputs to forecasts of the outcomes of football matches. It is shown that, were it possible to know the match statistics in advance, highly informative forecasts of…

Applications · Statistics 2020-01-27 Edward Wheatcroft

Over the last few decades, the player recruitment process in professional football has evolved into a multi-billion industry and has thus become of vital importance. To gain insights into the general level of their candidate reinforcements,…

Machine Learning · Statistics 2018-09-17 Bart Aalbers , Jan Van Haaren

Fantasy Premier League (FPL) performance predictors tend to base their algorithms purely on historical statistical data. The main problems with this approach is that external factors such as injuries, managerial decisions and other…

Machine Learning · Computer Science 2019-12-17 Nicholas Bonello , Joeran Beel , Seamus Lawless , Jeremy Debattista

Although academic research on the 'hot hand' effect (in particular, in sports, especially in basketball) has been going on for more than 30 years, it still remains a central question in different areas of research whether such an effect…

Applications · Statistics 2019-11-20 Marius Ötting , Andreas Groll

Predicting the outcomes of future events is a challenging problem for which a variety of solution methods have been explored and attempted. We present an empirical comparison of a variety of online and offline adaptive algorithms for…

Artificial Intelligence · Computer Science 2012-07-02 Varsha Dani , Omid Madani , David M Pennock , Sumit Sanghai , Brian Galebach

Anticipating defensive coverage schemes is a crucial yet challenging task for offenses in American football. Because defenders' assignments are intentionally disguised before the snap, they remain difficult to recognize in real time. To…

Applications · Statistics 2026-02-12 Rouven Michels , Robert Bajons , Jan-Ole Fischer
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