IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v394y2014icp304-311.html
   My bibliography  Save this article

Memory and long-range correlations in chess games

Author

Listed:
  • Schaigorodsky, Ana L.
  • Perotti, Juan I.
  • Billoni, Orlando V.

Abstract

In this paper we report the existence of long-range memory in the opening moves of a chronologically ordered set of chess games using an extensive chess database. We used two mapping rules to build discrete time series and analyzed them using two methods for detecting long-range correlations; rescaled range analysis and detrended fluctuation analysis. We found that long-range memory is related to the level of the players. When the database is filtered according to player levels we found differences in the persistence of the different subsets. For high level players, correlations are stronger at long time scales; whereas in intermediate and low level players they reach the maximum value at shorter time scales. This can be interpreted as a signature of the different strategies used by players with different levels of expertise. These results are robust against the assignation rules and the method employed in the analysis of the time series.

Suggested Citation

  • Schaigorodsky, Ana L. & Perotti, Juan I. & Billoni, Orlando V., 2014. "Memory and long-range correlations in chess games," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 394(C), pages 304-311.
    • Handle: RePEc:eee:phsmap:v:394:y:2014:i:c:p:304-311
    DOI: 10.1016/j.physa.2013.09.035
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437113009126
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000
    File URL: https://libkey.io/10.1016/j.physa.2013.09.035?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Haroldo V Ribeiro & Renio S Mendes & Ervin K Lenzi & Marcelo del Castillo-Mussot & Luís A N Amaral, 2013. "Move-by-Move Dynamics of the Advantage in Chess Matches Reveals Population-Level Learning of the Game," PLOS ONE, Public Library of Science, vol. 8(1), pages 1-7, January.
    2. de Saá Guerra, Y. & Martín González, J.M. & Sarmiento Montesdeoca, S. & Rodríguez Ruiz, D. & García-Rodríguez, A. & García-Manso, J.M., 2012. "A model for competitiveness level analysis in sports competitions: Application to basketball," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(10), pages 2997-3004.
    3. C. Sire & S. Redner, 2009. "Understanding baseball team standings and streaks," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 67(3), pages 473-481, February.
    4. E. Bittner & A. Nußbaumer & W. Janke & M. Weigel, 2009. "Football fever: goal distributions and non-Gaussian statistics," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 67(3), pages 459-471, February.
    5. A. Heuer & O. Rubner, 2009. "Fitness, chance, and myths: an objective view on soccer results," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 67(3), pages 445-458, February.
    6. Kantelhardt, Jan W & Koscielny-Bunde, Eva & Rego, Henio H.A & Havlin, Shlomo & Bunde, Armin, 2001. "Detecting long-range correlations with detrended fluctuation analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 295(3), pages 441-454.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Petersen, Alexander M. & Penner, Orion, 2020. "Renormalizing individual performance metrics for cultural heritage management of sports records," Chaos, Solitons & Fractals, Elsevier, vol. 136(C).
    2. Itami, A.S. & Antonio, F.J. & Mendes, R.S., 2015. "Very prolonged practice in block of trials: Scaling of fitness, universality and persistence," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 424(C), pages 82-89.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Mukherjee, Satyam, 2012. "Identifying the greatest team and captain—A complex network approach to cricket matches," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(23), pages 6066-6076.
    2. Andreas Heuer & Oliver Rubner, 2014. "Optimizing the Prediction Process: From Statistical Concepts to the Case Study of Soccer," PLOS ONE, Public Library of Science, vol. 9(9), pages 1-9, September.
    3. Marc Garnica-Caparrós & Daniel Memmert & Fabian Wunderlich, 2022. "Artificial data in sports forecasting: a simulation framework for analysing predictive models in sports," Information Systems and e-Business Management, Springer, vol. 20(3), pages 551-580, September.
    4. Lavička, Hynek & Kracík, Jiří, 2020. "Fluctuation analysis of electric power loads in Europe: Correlation multifractality vs. Distribution function multifractality," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 545(C).
    5. Vitanov, Nikolay K. & Sakai, Kenshi & Dimitrova, Zlatinka I., 2008. "SSA, PCA, TDPSC, ACFA: Useful combination of methods for analysis of short and nonstationary time series," Chaos, Solitons & Fractals, Elsevier, vol. 37(1), pages 187-202.
    6. Muchnik, Lev & Bunde, Armin & Havlin, Shlomo, 2009. "Long term memory in extreme returns of financial time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(19), pages 4145-4150.
    7. Zhong, Meirui & Zhang, Rui & Ren, Xiaohang, 2023. "The time-varying effects of liquidity and market efficiency of the European Union carbon market: Evidence from the TVP-SVAR-SV approach," Energy Economics, Elsevier, vol. 123(C).
    8. Wang, Dong-Hua & Yu, Xiao-Wen & Suo, Yuan-Yuan, 2012. "Statistical properties of the yuan exchange rate index," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(12), pages 3503-3512.
    9. Arkes Jeremy & Martinez Jose, 2011. "Finally, Evidence for a Momentum Effect in the NBA," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 7(3), pages 1-16, July.
    10. Currenti, Gilda & Negro, Ciro Del & Lapenna, Vincenzo & Telesca, Luciano, 2005. "Fluctuation analysis of the hourly time variability of volcano-magnetic signals recorded at Mt. Etna Volcano, Sicily (Italy)," Chaos, Solitons & Fractals, Elsevier, vol. 23(5), pages 1921-1929.
    11. Ren, Fei & Gu, Gao-Feng & Zhou, Wei-Xing, 2009. "Scaling and memory in the return intervals of realized volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(22), pages 4787-4796.
    12. El Alaoui, Marwane & Benbachir, Saâd, 2013. "Multifractal detrended cross-correlation analysis in the MENA area," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(23), pages 5985-5993.
    13. Gabel Alan & Redner Sidney, 2012. "Random Walk Picture of Basketball Scoring," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 8(1), pages 1-20, March.
    14. Luis Alberiko Gil-Alaña & Carlos Pestana Barros & Zhongfei Chen, 2016. "The persistence of air pollution in four mega-cities of China," NCID Working Papers 04/2016, Navarra Center for International Development, University of Navarra.
    15. Itami, A.S. & Antonio, F.J. & Mendes, R.S., 2015. "Very prolonged practice in block of trials: Scaling of fitness, universality and persistence," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 424(C), pages 82-89.
    16. Gerlich, Nikolas & Rostek, Stefan, 2015. "Estimating serial correlation and self-similarity in financial time series—A diversification approach with applications to high frequency data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 434(C), pages 84-98.
    17. Laura Raisa Miloş & Cornel Haţiegan & Marius Cristian Miloş & Flavia Mirela Barna & Claudiu Boțoc, 2020. "Multifractal Detrended Fluctuation Analysis (MF-DFA) of Stock Market Indexes. Empirical Evidence from Seven Central and Eastern European Markets," Sustainability, MDPI, vol. 12(2), pages 1-15, January.
    18. Gu, Gao-Feng & Chen, Wei & Zhou, Wei-Xing, 2008. "Empirical shape function of limit-order books in the Chinese stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(21), pages 5182-5188.
    19. Zhongxing Wang & Yan Yan & Xiaosong Chen, 2016. "Long-range Correlation and Market Segmentation in Bond Market," Papers 1610.09812, arXiv.org.
    20. Delignières, Didier & Marmelat, Vivien, 2014. "Strong anticipation and long-range cross-correlation: Application of detrended cross-correlation analysis to human behavioral data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 394(C), pages 47-60.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:phsmap:v:394:y:2014:i:c:p:304-311. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.