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We propose a novel ranking model that combines the Bradley-Terry-Luce probability model with a nonnegative matrix factorization framework to model and uncover the presence of latent variables that influence the performance of top tennis…

Machine Learning · Computer Science 2019-06-14 Rui Xia , Vincent Y. F. Tan , Louis Filstroff , Cédric Févotte

In this work we perform some mathematical analysis on non-negative matrix factorizations (NMF) and apply NMF to some imaging and inverse problems. We will propose a sparse low-rank approximation of big positive data and images in terms of…

Optimization and Control · Mathematics 2015-04-24 Yat Tin Chow , Kazufumi Ito , Jun Zou

In this paper, we describe an approach to rank sport players based on their efficiency. Although is extremely useful to analyze the performance of team games there is no unanimity on the use of a single index to perform such a ranking. We…

Optimization and Control · Mathematics 2018-02-21 Víctor Blanco , Román Salmerón , Samuel Gómez-Haro

Intensity estimation is a common problem in statistical analysis of spatial point pattern data. This paper proposes a nonparametric Bayesian method for estimating the spatial point process intensity based on mixture of finite mixture (MFM)…

Methodology · Statistics 2019-07-09 Junxian Geng , Wei Shi , Guanyu Hu

Team-based invasion sports such as football, basketball and hockey are similar in the sense that the players are able to move freely around the playing area; and that player and team performance cannot be fully analysed without considering…

Other Computer Science · Computer Science 2017-04-17 Joachim Gudmundsson , Michael Horton

Nonnegative matrix factorization (NMF) has an established reputation as a useful data analysis technique in numerous applications. However, its usage in practical situations is undergoing challenges in recent years. The fundamental factor…

Machine Learning · Computer Science 2016-05-04 Mariano Tepper , Guillermo Sapiro

Nonnegative matrix factorization (NMF) has become a very popular technique in machine learning because it automatically extracts meaningful features through a sparse and part-based representation. However, NMF has the drawback of being…

Machine Learning · Statistics 2012-12-07 Nicolas Gillis

A new range of statistical analysis has emerged in sports after the introduction of the high-resolution player tracking technology, specifically in basketball. However, this high dimensional data is often challenging for statistical…

Applications · Statistics 2020-02-12 Edgar Santos-Fernandez , Francesco Denti , Kerrie Mengersen , Antonietta Mira

We address the question of how to quantify the contributions of groups of players to team success. Our approach is based on spectral analysis, a technique from algebraic signal processing, which has several appealing features. First, our…

Applications · Statistics 2020-06-26 Stephen Devlin , David Uminsky

This paper studies the relationship between basketball teams' four factors and efficiency ratings as defined by Oliver (2004). The paper introduces an equation showing how a team's four factors in conjunction with its field goal and free…

Applications · Statistics 2023-05-23 Jirka Poropudas , Topi Halme

How much is an on-ball screen worth? How much is a backdoor cut away from the ball worth? Basketball is one of a number of sports which, within the past decade, have seen an explosion in quantitative metrics and methods for evaluating…

Applications · Statistics 2019-02-22 Anthony Sicilia , Konstantinos Pelechrinis , Kirk Goldsberry

We investigate the hot hand phenomenon using data on 110,513 free throws taken in the National Basketball Association (NBA). As free throws occur at unevenly spaced time points within a game, we consider a state-space model formulated in…

Applications · Statistics 2023-11-16 Sina Mews , Marius Ötting

A spatial point process can be characterized by an intensity function which predicts the number of events that occur across space. In this paper, we develop a method to infer predictive intensity intervals by learning a spatial model using…

Machine Learning · Statistics 2020-07-06 Muhammad Osama , Dave Zachariah , Petre Stoica

There has been a recent critical need to study fairness and bias in machine learning (ML) algorithms. Since there is clearly no one-size-fits-all solution to fairness, ML methods should be developed alongside bias mitigation strategies that…

Machine Learning · Computer Science 2026-03-06 Lara Kassab , Erin George , Deanna Needell , Haowen Geng , Nika Jafar Nia , Aoxi Li

The availability of large spatial data geocoded at accurate locations has fueled a growing interest in spatial modeling and analysis of point processes. The proposed research is motivated by the intensity estimation problem for large…

Applications · Statistics 2021-07-19 Lihao Yin , Huiyan Sang

Nonnegative matrix factorization (NMF) has become a widely used tool for the analysis of high-dimensional data as it automatically extracts sparse and meaningful features from a set of nonnegative data vectors. We first illustrate this…

Machine Learning · Statistics 2014-12-10 Nicolas Gillis

Non-negative matrix factorization (NMF) is one of the most popular decomposition techniques for multivariate data. NMF is a core method for many machine-learning related computational problems, such as data compression, feature extraction,…

Numerical Analysis · Computer Science 2017-12-07 Gabriele Torre , Michael Graber

The purpose of this paper is to determine whether basketball teams who choose to employ an offensive strategy that involves predominantly shooting three point shots is stable and optimal. We employ a game-theoretical approach using…

Dynamical Systems · Mathematics 2015-06-24 Ikjyot Singh Kohli

In the competitive realm of sports, optimal performance necessitates rigorous management of nutrition and physical conditioning. Specifically, in badminton, the agility and precision required make it an ideal candidate for motion analysis…

Human-Computer Interaction · Computer Science 2024-03-15 Dhruv Toshniwal , Arpit Patil , Nancy Vachhani

Global Positioning Systems (GPS) are nowadays intensively used in Sport Science as they permit to capture the space-time trajectories of players, with the aim to infer useful information to coaches in addition to traditional statistics. In…

Applications · Statistics 2017-07-05 Rodolfo Metulini , Marica Manisera , Paola Zuccolotto
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