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We propose AFTNet, a novel network-constraint survival analysis method based on the Weibull accelerated failure time (AFT) model solved by a penalized likelihood approach for variable selection and estimation. When using the log-linear…

Machine Learning · Statistics 2024-02-29 Claudia Angelini , Daniela De Canditiis , Italia De Feis , Antonella Iuliano

Banks routinely use neural networks to make decisions. While these models offer higher accuracy, they are susceptible to adversarial attacks, a risk often overlooked in the context of event sequences, particularly sequences of financial…

We propose a distributionally robust logistic regression model with an unfairness penalty that prevents discrimination with respect to sensitive attributes such as gender or ethnicity. This model is equivalent to a tractable convex…

Machine Learning · Computer Science 2020-07-21 Bahar Taskesen , Viet Anh Nguyen , Daniel Kuhn , Jose Blanchet

This paper introduces a novel framework for designing fair and sustainable unemployment benefits, grounded in cooperative game theory and real-time fiscal policy. The labor market is modeled as a coalitional game, where a random subset of…

General Finance · Quantitative Finance 2025-12-15 Xingwei Hu

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

Risk management is an important part of financial practice, essential for protecting assets and investments in modern-day volatile markets. This paper proposes a mixture of mirrored Weibull (MMW) distribution for modelling stock returns and…

Applications · Statistics 2026-05-20 Zijun Jia , Sharon X. Lee

The National Football League (NFL) Scouting Combine serves as a tool to evaluate the skills of prospective players and assess their readiness to play in the NFL. The development of machine learning brings new opportunities in assessing the…

Machine Learning · Computer Science 2023-03-13 Brian Szekely , Christian Sinnott , Savannah Halow , Gregory Ryan

Estimating win probability is one of the classic modeling tasks of sports analytics. Many widely used win probability estimators use machine learning to fit the relationship between a binary win/loss outcome variable and certain game-state…

Methodology · Statistics 2025-08-21 Ryan S. Brill , Ronald Yurko , Abraham J. Wyner

The game-theoretic risk management framework put forth in the precursor work "Towards a Theory of Games with Payoffs that are Probability-Distributions" (arXiv:1506.07368 [q-fin.EC]) is herein extended by algorithmic details on how to…

General Economics · Economics 2020-04-10 Stefan Rass

The ubiquity of professional sports and specifically the NFL have lead to an increase in popularity for Fantasy Football. Users have many tools at their disposal: statistics, predictions, rankings of experts and even recommendations of…

Machine Learning · Computer Science 2015-05-27 Roman Lutz

The strategic orchestration of football matchplays profoundly influences game outcomes, motivating a surge in research aimed at uncovering tactical nuances through social network analysis. In this paper, we delve into the microscopic…

Physics and Society · Physics 2024-08-16 Ming-Xia Li , Li-Gong Xu , Wei-Xing Zhou

Fairness,the impartial treatment towards individuals or groups regardless of their inherent or acquired characteristics [20], is a critical challenge for the successful implementation of Artificial Intelligence (AI) in multiple fields like…

Neural and Evolutionary Computing · Computer Science 2025-05-19 Catalina M Jaramillo , Paul Squires , Julian Togelius

A recent body of experimental literature has studied empirical game-theoretical analysis, in which we have partial knowledge of a game, consisting of observations of a subset of the pure-strategy profiles and their associated payoffs to…

Computer Science and Game Theory · Computer Science 2014-02-13 John Fearnley , Martin Gairing , Paul Goldberg , Rahul Savani

This study analyzes pass networks in football (soccer) using a stochastic model known as the P\'olya urn. By focusing on preferential selection, it theoretically demonstrates that the time evolution of networks can be characterized by a…

Physics and Society · Physics 2025-12-19 Ken Yamamoto

There seems to be an upper limit to predicting the outcome of matches in (semi-)professional sports. Recent work has proposed that this is due to chance and attempts have been made to simulate the distribution of win percentages to identify…

Applications · Statistics 2015-08-21 Albrecht Zimmermann

While significant advancements have been made in the field of fair machine learning, the majority of studies focus on scenarios where the decision model operates on a static population. In this paper, we study fairness in dynamic systems…

Machine Learning · Computer Science 2024-01-15 Yaowei Hu , Jacob Lear , Lu Zhang

In recent years, high-frequency trading has emerged as a crucial strategy in stock trading. This study aims to develop an advanced high-frequency trading algorithm and compare the performance of three different mathematical models: the…

Trading and Market Microstructure · Quantitative Finance 2023-11-21 Jiahao Chen , Xiaofei Li

In this study, basketball teams are conceptualized as complex adaptive systems to examine their (re)organizational processes in response the time remaining to shoot. Using temporal passing networks to model team behavior, the focus is on…

Discrete Mathematics · Computer Science 2025-06-06 Quentin Bourgeais , Rodolphe Charrier , Eric Sanlaville , Ludovic Seifert

This paper considers the challenge of designing football group draw mechanisms which have the uniform distribution over all valid draw assignments, but are also entertaining, practical, and transparent. We explain how to simulate the FIFA…

Applications · Statistics 2023-01-26 Gareth O. Roberts , Jeffrey S. Rosenthal

In football, attacking teams attempt to break through the opponent's defensive line to create scoring opportunities. This action, known as a Line Break, is a critical indicator of offensive effectiveness and tactical performance, yet…

Machine Learning · Computer Science 2025-11-04 Shoma Yagi , Jun Ichikawa , Genki Ichinose
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