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An open problem posed by the first author is the complexity to decide whether a sequence of nonnegative integer numbers can be the final score of a football tournament. In this paper we propose polynomial time approximate and exponential…

Discrete Mathematics · Computer Science 2012-07-27 A. Iványi , J. E. Schoenfield

Penalized likelihood methods with an $\ell_{\gamma}$-type penalty, such as the Bridge, the SCAD, and the MCP, allow us to estimate a parameter and to do variable selection, simultaneously, if $\gamma\in (0,1]$. In this method, it is…

Methodology · Statistics 2016-03-28 Yuta Umezu , Yoshiyuki Ninomiya

Penalty shootouts play a crucial role in the knockout stage of major football tournaments. Their importance has substantially increased from the 2021/22 season, when the Union of European Football Associations (UEFA) scrapped the away goals…

General Economics · Economics 2026-04-09 László Csató , Dóra Gréta Petróczy

Machine learning models have become increasingly popular for predicting the results of soccer matches, however, the lack of publicly-available benchmark datasets has made model evaluation challenging. The 2023 Soccer Prediction Challenge…

Machine Learning · Computer Science 2023-09-27 Calvin Yeung , Rory Bunker , Rikuhei Umemoto , Keisuke Fujii

Though athletics statistics are abundant, it is a difficult task to quantitatively compare performances from different events of track, field, and road running in a meaningful way. There are several commonly-used methods, but each has its…

Applications · Statistics 2014-08-27 Brian Godsey

In this work, we extended a stochastic model for football leagues based on the team's potential [R. da Silva et al. Comput. Phys. Commun. \textbf{184} 661--670 (2013)] for making predictions instead of only performing a successful…

Physics and Society · Physics 2022-06-08 Eduardo V. Stock , Roberto da Silva , Henrique A. Fernandes

Stochastic optimization algorithms have been successfully applied in several domains to find optimal solutions. Because of the ever-growing complexity of the integrated systems, novel stochastic algorithms are being proposed, which makes…

Artificial Intelligence · Computer Science 2024-06-04 Sowmya Chandrasekaran , Thomas Bartz-Beielstein

Conformal prediction is a statistically rigorous method for quantifying uncertainty in models by having them output sets of predictions, with larger sets indicating more uncertainty. However, prediction sets are not inherently actionable;…

Machine Learning · Computer Science 2025-02-17 Jesse C. Cresswell , Bhargava Kumar , Yi Sui , Mouloud Belbahri

Forecasts for uncertain future events should be probabilistic. Probabilistic forecasts are commonly issued as prediction intervals, which provide a measure of uncertainty in the unknown outcome whilst being easier to understand and…

Methodology · Statistics 2025-08-26 Sam Allen , Julia Burnello , Johanna Ziegel

A liquid scorecard has liquid characteristics, for which the characteristic score is a smooth function of the characteristic over a liquid range. The smooth function is based on B-splines, typically cubic. In contrast, the characteristic…

Methodology · Statistics 2020-03-03 Bruce Hoadley

Soccer is a sparse rewarding game: any smart or careless action in critical situations can change the result of the match. Therefore players, coaches, and scouts are all curious about the best action to be performed in critical situations,…

Machine Learning · Computer Science 2021-09-15 Pegah Rahimian , Afshin Oroojlooy , Laszlo Toka

People are commonly interested in predicting a statistical property of a random event such as mean and variance. Proper scoring rules assess the quality of predictions and require that the expected score gets uniquely maximized at the…

Machine Learning · Computer Science 2025-06-24 Lingfang Hu , Ian A. Kash

When eliciting forecasts from a group of experts, it is important to reward predictions so that market participants are incentivized to tell the truth. Existing mechanisms partially accomplish this but remain susceptible to groups of…

Theoretical Economics · Economics 2024-11-26 Jack Edwards

Computer-aided support and analysis are becoming increasingly important in the modern world of sports. The scouting of potential prospective players, performance as well as match analysis, and the monitoring of training programs rely more…

Computer Vision and Pattern Recognition · Computer Science 2021-10-22 Jonas Theiner , Wolfgang Gritz , Eric Müller-Budack , Robert Rein , Daniel Memmert , Ralph Ewerth

Calibration means that forecasts and average realized frequencies are close. We develop the concept of forecast hedging, which consists of choosing the forecasts so as to guarantee that the expected track record can only improve. This…

Theoretical Economics · Economics 2022-10-14 Dean P. Foster , Sergiu Hart

Score matching is an estimation procedure that has been developed for statistical models whose probability density function is known up to proportionality but whose normalizing constant is intractable, so that maximum likelihood is…

Methodology · Statistics 2024-04-23 Jiazhen Xu , Janice L. Scealy , Andrew T. A. Wood , Tao Zou

A new family of penalty functions, adaptive to likelihood, is introduced for model selection in general regression models. It arises naturally through assuming certain types of prior distribution on the regression parameters. To study…

Methodology · Statistics 2013-08-26 Yang Feng , Tengfei Li , Zhiliang Ying

In soccer, contextual player performance metrics are invaluable to coaches. For example, the ability to perform under pressure during matches distinguishes the elite from the average. Appropriate pressure metric enables teams to assess…

Machine Learning · Computer Science 2024-03-08 Chaoyi Gu , Jiaming Na , Yisheng Pei , Varuna De Silva

All proper scoring rules incentivize an expert to predict \emph{accurately} (report their true estimate), but not all proper scoring rules equally incentivize \emph{precision}. Rather than treating the expert's belief as exogenously given,…

Computer Science and Game Theory · Computer Science 2021-06-01 Eric Neyman , Georgy Noarov , S. Matthew Weinberg

We consider how to make probability forecasts of binary labels. Our main mathematical result is that for any continuous gambling strategy used for detecting disagreement between the forecasts and the actual labels, there exists a…

Machine Learning · Computer Science 2007-05-23 Vladimir Vovk , Akimichi Takemura , Glenn Shafer