eprintid: 2401 rev_number: 7 eprint_status: archive userid: 6 dir: disk0/00/00/24/01 datestamp: 2014-12-04 10:44:08 lastmod: 2014-12-04 10:52:18 status_changed: 2014-12-04 10:44:08 type: article metadata_visibility: show creators_name: Schaigorodsky, Ana L. creators_name: Perotti, Juan I. creators_name: Billoni, Orlando V. creators_id: creators_id: juanignacio.perotti@imtlucca.it creators_id: title: Memory and long-range correlations in chess games ispublished: pub subjects: HA subjects: QC divisions: EIC full_text_status: none keywords: Long-range correlations; Zipf’s law; Interdisciplinary physics 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. date: 2014 publication: Physica A: Statistical Mechanics and its Applications volume: 394 number: 0 publisher: Elsevier pagerange: 304 - 311 id_number: 10.1016/j.physa.2013.09.035 refereed: TRUE issn: 0378-4371 official_url: http://www.sciencedirect.com/science/article/pii/S0378437113009126 related_url_url: http://arxiv.org/abs/1307.0729 citation: Schaigorodsky, Ana L. and Perotti, Juan I. and Billoni, Orlando V. Memory and long-range correlations in chess games. Physica A: Statistical Mechanics and its Applications, 394. 304 - 311. ISSN 0378-4371 (2014)