Investigating Experiential Effects in Online Chess using a Hierarchical Bayesian Analysis

Fuente: arXiv
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Autori principali: Gee, Adam, Seese, Sydney O., Curley, James P., Ward, Owen G.
Natura: Preprint
Pubblicazione: 2025
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author Gee, Adam
Seese, Sydney O.
Curley, James P.
Ward, Owen G.
author_facet Gee, Adam
Seese, Sydney O.
Curley, James P.
Ward, Owen G.
contents 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 popularity in recent years and provides vast amounts of data which can be used to explore this question. With a hierarchical Bayesian regression model, we carefully investigate the presence of such experiential effects in online chess. Using a large quantity of online chess data, we see little evidence for experiential effects that are consistent across all players, with some individual players showing some evidence for such effects. Given the challenging temporal nature of this data, we discuss several methods for assessing the suitability of our model and carefully check its validity.
format Preprint
id arxiv_https___arxiv_org_abs_2503_21713
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Investigating Experiential Effects in Online Chess using a Hierarchical Bayesian Analysis
Gee, Adam
Seese, Sydney O.
Curley, James P.
Ward, Owen G.
Applications
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 popularity in recent years and provides vast amounts of data which can be used to explore this question. With a hierarchical Bayesian regression model, we carefully investigate the presence of such experiential effects in online chess. Using a large quantity of online chess data, we see little evidence for experiential effects that are consistent across all players, with some individual players showing some evidence for such effects. Given the challenging temporal nature of this data, we discuss several methods for assessing the suitability of our model and carefully check its validity.
title Investigating Experiential Effects in Online Chess using a Hierarchical Bayesian Analysis
topic Applications
url https://arxiv.org/abs/2503.21713