What can 100,000 chess players tell us about improvement?
DOI:
https://doi.org/10.47611/jsrhs.v13i3.7508Keywords:
chess learningAbstract
The role of memorizing chess openings in achieving mastery has long been debated. This study attempts to prove a relation between exposure to different phases of a chess game and the change in skill over the course of a year. Using the lichess open database, the researcher analyzed game lengths and changes in elo over a one year period for accounts ranging from beginner to advanced. The method isolates length of chess games from the elo measurement to allow for tracking of persistent variables over the period of the year. This allows for the examination of a player’s tendency towards longer or shorter games, which was compared to their change in skill over the year. Contrary to my hypothesis, the results suggest a near zero correlation between length tendency and change in elo relative to peers.
Downloads
References or Bibliography
Armstrong, J. S. (2010). Natural Learning in Higher Education. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.1928831
Bobby Fischer on Paul Morphy and how opening theory destroyed chess. (n.d.). Www.youtube.com. https://www.youtube.com/watch?v=P349BdHUxlc
Cheng, I., & Camargo, C. (2023). Machine learning to study patterns in chess games. https://doi.org/10.13140/RG.2.2.30894.52807
Chowdhary, S., Iacopini, I., & Battiston, F. (2023). Quantifying human performance in chess. Scientific Reports, 13(1), 2113. https://doi.org/10.1038/s41598-023-27735-9
De Marzo, G., & Servedio, V. D. P. (2023). Quantifying the complexity and similarity of chess openings using online chess community data. Scientific Reports, 13(1). https://doi.org/10.1038/s41598-023-31658-w
Duplessis, T. (2024). The best free, adless Chess server. Lichess.org. https://lichess.org
Gaschler, R., Progscha, J., Smallbone, K., Ram, N., & Bilalić, M. (2014). Playing off the curve - testing quantitative predictions of skill acquisition theories in development of chess performance. Frontiers in Psychology, 5. https://doi.org/10.3389/fpsyg.2014.00923
Grabner, R. H., Stern, E., & Neubauer, A. C. (2007). Individual differences in chess expertise: A psychometric investigation. Acta Psychologica, 124(3), 398–420. https://doi.org/10.1016/j.actpsy.2006.07.008
Holdaway, C., & Vul, E. (2021). Risk-taking in adversarial games: What can 1 billion online chess games tell us? Proceedings of the Annual Meeting of the Cognitive Science Society, 43. Retrieved from https://escholarship.org/uc/item/403764rd
Holdaway, C., & Vul, E. (2021). Risk-taking in adversarial games: What can 1 billion online chess games tell us? PsyArXiv (OSF Preprints), 43. https://doi.org/10.31234/osf.io/vgpdj
Howard, R. W. (2011). Longitudinal Effects of Different Types of Practice on the Development of Chess Expertise. Applied Cognitive Psychology, 26(3), 359–369. https://doi.org/10.1002/acp.1834
Jonassen, D. H., & Strobel, J. (2006). Modeling for Meaningful Learning. Engaged Learning with Emerging Technologies, 1–27. https://doi.org/10.1007/1-4020-3669-8_1
Kasparov, G. (2010). The Chess Master and the Computer. https://web.mit.edu/6.034/wwwbob/kasparov-article.pdf
King, D. J., & Russell, G. W. (1966). A comparison of rote and meaningful learning of connected meaningful material. Journal of Verbal Learning and Verbal Behavior, 5(5), 478–483. https://doi.org/10.1016/s0022-5371(66)80064-6
Magnus Carlsen – “I don’t quite fit into the usual schemes.” (2011, December 22). Chess News. https://en.chessbase.com/post/magnus-carlsen-i-don-t-quite-fit-into-the-usual-schemes-
Morales, E. M. (1996). LEARNING PLAYING STRATEGIES IN CHESS. Computational Intelligence, 12(1), 65–87. https://doi.org/10.1111/j.1467-8640.1996.tb00253.x
Ross, P. E. (2006). The Expert Mind. Scientific American, 295(2), 64–71. https://www.jstor.org/stable/26068925
The Editors of Encyclopedia Britannica. (2019). Bobby Fischer | Biography & Facts. In Encyclopædia Britannica. https://www.britannica.com/biography/Bobby-Fischer
Van Der Maas, H. L. J., & Wagenmakers, E.-J. (2005). A Psychometric Analysis of Chess Expertise. The American Journal of Psychology, 118(1), 29–60. https://doi.org/10.2307/30039042
Veček, N., Črepinšek, M., Mernik, M., & Hrnčič, D. (2014). A comparison between different chess rating systems for ranking evolutionary algorithms. 511–518. https://doi.org/10.15439/2014F33
Published
How to Cite
Issue
Section
Copyright (c) 2024 Andrew Ashman; Soo Park, Daoud El Dibani

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
Copyright holder(s) granted JSR a perpetual, non-exclusive license to distriute & display this article.


