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As a dedicated follower of sports statistics and with the MLB season beginning in late March, I set out to predict how many wins each team would accumulate by the end of the 162 game season. The goal was to build a simulation framework…

Applications · Statistics 2025-05-09 Simon Cha

Two-player zero-sum repeated games are well understood. Computing the value of such a game is straightforward. Additionally, if the payoffs are dependent on a random state of the game known to one, both, or neither of the players, the…

Information Theory · Computer Science 2009-11-05 Paul Cuff

One of the most important problems in system identification and statistics is how to estimate the unknown parameters of a given model. Optimization methods and specialized procedures, such as Empirical Minimization (EM) can be used in case…

Methodology · Statistics 2024-02-09 Braghadeesh Lakshminarayanan , Cristian R. Rojas

We showcase in this paper the use of some tools from network theory to describe the strategy of football teams. Using passing data made available by FIFA during the 2010 World Cup, we construct for each team a weighted and directed network…

Combinatorics · Mathematics 2013-12-03 Javier López Peña , Hugo Touchette

We analyze how coaching strategies affect goal difference and home win probabilities using hand-coded Serie A match commentary (2011/12--2013/14). Our dataset captures in-game dynamics, referee actions, and team behavior. Applying…

In economy, markets are denoted as efficient when it is impossible to systematically generate profits which outperform the average. In the past years, the concept has been tested in other domains such as the growing sports betting market.…

Physics and Society · Physics 2023-03-30 Ralph Stömmer

We introduce a Bayesian mean-value approach for ranking all college football teams using only win-loss data. This approach is unique in that the prior distribution necessary to handle undefeated and winless teams is calculated…

Popular Physics · Physics 2007-06-26 James R. Ashburn , Paul M. Colvert

Stochastic games are an important class of problems that generalize Markov decision processes to game theoretic scenarios. We consider finite state two-player zero-sum stochastic games over an infinite time horizon with discounted rewards.…

Optimization and Control · Mathematics 2008-06-17 Parikshit Shah , Pablo A. Parrilo

The majority game, modelling a system of heterogeneous agents trying to behave in a similar way, is introduced and studied using methods of statistical mechanics. The stationary states of the game are given by the (local) minima of a…

Statistical Mechanics · Physics 2026-04-08 P. Kozlowski , M. Marsili

In the paper it is proven that the two-players turn-based stochastic game "Risk or Safety" has a unique solution. Both players need to play the same strategy if they want to maximize their winning chances. An analytical method based on the…

Combinatorics · Mathematics 2026-03-03 Rüdiger Jehn

The most important factors which contribute to the efficiency of game-theoretical algorithms are time and game complexity. In this study, we have offered an elegant method to deal with high complexity of game theoretic multi-objective…

Computer Science and Game Theory · Computer Science 2015-03-13 Mahsa Badami , Ali Hamzeh , Sattar Hashemi

This work proposes a scheme that allows learning complex multi-agent behaviors in a sample efficient manner, applied to 2v2 soccer. The problem is formulated as a Markov game, and solved using deep reinforcement learning. We propose a basic…

Machine Learning · Computer Science 2021-03-10 Pavan Samtani , Francisco Leiva , Javier Ruiz-del-Solar

The field of quantitative analytics has transformed the world of sports over the last decade. To date, these analytic approaches are statistical at their core, characterizing what is and what was, while using this information to drive…

Computer Science and Game Theory · Computer Science 2021-10-12 Connor Douglas , Everett Witt , Mia Bendy , Yevgeniy Vorobeychik

Cricket betting is a multi-billion dollar market. Therefore, there is a strong incentive for models that can predict the outcomes of games and beat the odds provided by bookers. The aim of this study was to investigate to what degree it is…

Machine Learning · Statistics 2015-11-19 Stylianos Kampakis , William Thomas

For NCAA football, we provide a method for sports bettors to determine if they have a positive expected value bet based on the betting lines available to them and how they believe the game will end. The method we develop modifies…

Applications · Statistics 2022-12-19 Ryan Sides , Jane L. Harvill

The approaches routinely used to model the outcomes of football matches are characterised by strong assumptions about the dependence between the number of goals scored by the two competing teams and their marginal distribution. In this…

Methodology · Statistics 2022-12-06 Marco Petretta , Lorenzo Schiavon , Jacopo Diquigiovanni

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

In online betting, the bookmaker can update the payoffs it offers on a particular event many times before the event takes place, and the updated payoffs may depend on the bets accumulated thus far. We study the problem of bookmaking with…

Computer Science and Game Theory · Computer Science 2025-01-14 Alankrita Bhatt , Or Ordentlich , Oron Sabag

A good racing strategy and in particular the racing line is decisive to winning races in Formula 1, MotoGP, and other forms of motor racing. The racing line defines the path followed around a track as well as the optimal speed profile along…

Robotics · Computer Science 2020-02-13 Achin Jain , Manfred Morari

We introduce the class of multistage stochastic optimization problems with a random number of stages. For such problems, we show how to write dynamic programming equations and detail the Stochastic Dual Dynamic Programming algorithm to…

Optimization and Control · Mathematics 2019-07-18 Vincent Guigues