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We propose and illustrate a hierarchical Bayesian approach for matching statistical records observed on different occasions. We show how this model can be profitably adopted both in record linkage problems and in capture--recapture setups,…

Applications · Statistics 2011-07-29 Andrea Tancredi , Brunero Liseo

An important task for any large-scale organization is to prepare forecasts of key performance metrics. Often these organizations are structured in a hierarchical manner and for operational reasons, projections of these metrics may have been…

Applications · Statistics 2017-11-15 Julie Novak , Scott McGarvie , Beatriz Etchegaray Garcia

Statistical applications in sports have long centered on how to best separate signal (e.g. team talent) from random noise. However, most of this work has concentrated on a single sport, and the development of meaningful cross-sport…

Applications · Statistics 2017-11-23 Michael J. Lopez , Gregory J. Matthews , Benjamin S. Baumer

Considering the flexibility and applicability of Bayesian modeling, in this work we revise the main characteristics of two hierarchical models in a regression setting. We study the full probabilistic structure of the models along with the…

Methodology · Statistics 2021-10-22 Juan Sosa , Jeimy Aristizabal

Goals are results of pin-point shots and it is a pivotal decision in soccer when, how and where to shoot. The main contribution of this study is two-fold. At first, after showing that there exists high spatial correlation in the data of…

Applications · Statistics 2021-04-08 Soudeep Deb , Debangan Dey

We develop a statistical framework to evaluate evidence of alleged cheating involving illegal signaling in sports from a forensic perspective. We explain why, instead of a frequentist procedure, a Bayesian approach is called for. We apply…

Applications · Statistics 2025-03-04 Aafko Boonstra , Ronald Meester

Traditional NBA player evaluation metrics are based on scoring differential or some pace-adjusted linear combination of box score statistics like points, rebounds, assists, etc. These measures treat performances with the outcome of the game…

Applications · Statistics 2023-09-21 Sameer K. Deshpande , Shane T. Jensen

Statistical modelling of sports data has become more and more popular in the recent years and different types of models have been proposed to achieve a variety of objectives: from identifying the key characteristics which lead a team to win…

Applications · Statistics 2019-11-21 Andrea Gabrio

In public health applications, spatial data collected are often recorded at different spatial scales and over different correlated variables. Spatial change of support is a key inferential problem in these applications and have become…

Methodology · Statistics 2024-03-28 Shijie Zhou , Jonathan R. Bradley

It is common to be interested in rankings or order relationships among entities. In complex settings where one does not directly measure a univariate statistic upon which to base ranks, such inferences typically rely on statistical models…

Methodology · Statistics 2022-04-12 Andres F. Barrientos , Deborshee Sen , Garritt L Page , David B Dunson

Hierarchical Bayesian methods enable information sharing across multiple related regression problems. While standard practice is to model regression parameters (effects) as (1) exchangeable across datasets and (2) correlated to differing…

Methodology · Statistics 2021-07-15 Brian L. Trippe , Hilary K. Finucane , Tamara Broderick

Statistical modelling in the presence of data organized in groups is a crucial task in Bayesian statistics. The present paper conceives a mixture model based on a novel family of Bayesian priors designed for multilevel data and obtained by…

Methodology · Statistics 2024-07-01 Alessandro Colombi , Raffaele Argiento , Federico Camerlenghi , Lucia Paci

In the domain of Sport Analytics, Global Positioning Systems devices are intensively used as they permit to retrieve players' movements. Team sports' managers and coaches are interested on the relation between players' patterns of movements…

Applications · Statistics 2018-05-08 Rodolfo Metulini

Stacking is a widely used model averaging technique that asymptotically yields optimal predictions among linear averages. We show that stacking is most effective when model predictive performance is heterogeneous in inputs, and we can…

Methodology · Statistics 2021-10-29 Yuling Yao , Gregor Pirš , Aki Vehtari , Andrew Gelman

Bayesian statistics has gained great momentum since the computational developments of the 1990s. Gradually, advances in Bayesian methodology and software have made Bayesian techniques much more accessible to applied statisticians and, in…

Computation · Statistics 2020-11-04 Jim Albert , Jingchen Hu

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

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

The baseball game is often seen as many contests that are performed between individuals. The duel between the pitcher and the batter, for example, is considered the engine that drives the sport. The pitchers use a variety of strategies to…

Computer Vision and Pattern Recognition · Computer Science 2020-03-10 Nina Wiedemann , Carlos Dietrich , Claudio T. Silva

The presence or absence of winner-loser effects is a widely discussed phenomenon across both sports and psychology research. Investigation of such effects is often hampered by the limited availability of data. Online chess has exploded in…

Applications · Statistics 2025-08-12 Adam Gee , Sydney O. Seese , James P. Curley , Owen G. Ward

This paper uses Bayesian tree models for statistical benchmarking in data sets with awkward marginals and complicated dependence structures. The method is applied to a very large database on corporate performance over the last four decades.…

Methodology · Statistics 2010-10-26 James G. Scott