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In this paper, we report on two studies that analyze naturalistic gameplay data using cohort analysis to better understand how skill relates to practice and habit. Two cohorts are analyzed, each from two different games (Halo Reach<\/jats:italic> and StarCraft 2<\/jats:italic>). Our work follows skill progression through 7\u00a0months of Halo<\/jats:italic> matches for a holistic perspective, but also explores low\u2010level in\u2010game habits when controlling game units in StarCraft 2<\/jats:italic>. Players who played moderately frequently without long breaks were able to gain skill the most efficiently. What set the highest performers apart was their ability to gain skill more rapidly and without dips compared to other players. At the beginning of matches, top players habitually warmed up by selecting and re\u2010selecting groups of units repeatedly in a meaningless cycle. They exhibited unique routines during their play that aided them when under pressure.<\/jats:p>","DOI":"10.1111\/tops.12251","type":"journal-article","created":{"date-parts":[[2017,2,15]],"date-time":"2017-02-15T07:32:49Z","timestamp":1487143969000},"page":"437-466","update-policy":"http:\/\/dx.doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":46,"title":["Master Maker: Understanding Gaming Skill Through Practice and Habit From Gameplay Behavior"],"prefix":"10.1111","volume":"9","author":[{"given":"Jeff","family":"Huang","sequence":"first","affiliation":[{"name":"Department of Computer Science Brown University"}]},{"given":"Eddie","family":"Yan","sequence":"additional","affiliation":[{"name":"Computer Science & Engineering University of Washington"}]},{"given":"Gifford","family":"Cheung","sequence":"additional","affiliation":[{"name":"Computer Science & Engineering University of Washington"}]},{"given":"Nachiappan","family":"Nagappan","sequence":"additional","affiliation":[{"name":"Microsoft Research"}]},{"given":"Thomas","family":"Zimmermann","sequence":"additional","affiliation":[{"name":"Microsoft Research"}]}],"member":"311","published-online":{"date-parts":[[2017,2,15]]},"reference":[{"key":"e_1_2_9_2_1","unstructured":"d_ijk_stra.(2012).Statistical bonjwa theory: The history of bw. 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