{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,10]],"date-time":"2026-06-10T16:33:26Z","timestamp":1781109206080,"version":"3.54.1"},"reference-count":30,"publisher":"IEEE","license":[{"start":{"date-parts":[[2020,12,10]],"date-time":"2020-12-10T00:00:00Z","timestamp":1607558400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2020,12,10]],"date-time":"2020-12-10T00:00:00Z","timestamp":1607558400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2020,12,10]],"date-time":"2020-12-10T00:00:00Z","timestamp":1607558400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020,12,10]]},"DOI":"10.1109\/bigdata50022.2020.9378154","type":"proceedings-article","created":{"date-parts":[[2021,3,19]],"date-time":"2021-03-19T21:10:21Z","timestamp":1616188221000},"page":"1283-1292","source":"Crossref","is-referenced-by-count":30,"title":["Valuing Player Actions in Counter-Strike: Global Offensive"],"prefix":"10.1109","author":[{"given":"Peter","family":"Xenopoulos","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Harish","family":"Doraiswamy","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Claudio","family":"Silva","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1214\/18-AOAS1165"},{"key":"ref10","article-title":"Decomposing the immeasurable sport: A deep learning expected possession value framework for soccer","author":"fern\u00e1ndez","year":"2019","journal-title":"MIT Sloan Sports Analytics Conference"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1145\/3292500.3330719"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2018\/478"},{"key":"ref13","article-title":"Real-time esports match result prediction","author":"yang","year":"2016"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/TG.2019.2948469"},{"key":"ref15","first-page":"183","article-title":"Predicting winning team and probabilistic ratings in ”dota 2\" and \"counter-strike: Global offensive\" video games","author":"makarov","year":"2017","journal-title":"International Conference on Analysis of Images Social Networks and Texts"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-94809-6_8"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1145\/3054132"},{"key":"ref18","article-title":"Navigation meshes","year":"2008"},{"key":"ref19","article-title":"Introducing rating 2.0","author":"milanovic","year":"2017"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.2307\/2331838"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1145\/3292500.3330758"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1515\/jqas-2016-0098"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.5220\/0006475002690276"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1515\/jqas-2013-0100"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1515\/jqas-2014-0098"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1515\/jqas-2018-0010"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1080\/01621459.2016.1141685"},{"key":"ref7","article-title":"An expected goals model for evaluating nhl teams and players","author":"macdonald","year":"0"},{"key":"ref2","author":"assun\u00e7\u00e3o","year":"2018","journal-title":"Sports analytics in the era of big data Moving toward the next frontier"},{"key":"ref9","article-title":"Going deep: Models for continuous-time within-play valuation of game outcomes in american football with tracking data","author":"yurko","year":"2019"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1080\/19357397.2017.1316001"},{"key":"ref20","article-title":"What is that rating thing in stats?","author":"milanovic","year":"2010"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1145\/2939672.2939785"},{"key":"ref21","first-page":"6638","article-title":"Catboost: unbiased boosting with categorical features","author":"prokhorenkova","year":"2018","journal-title":"Advances in neural information processing systems"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1145\/1102351.1102430"},{"key":"ref23","first-page":"413","article-title":"Obtaining calibrated probabilities from boosting","author":"niculescu-mizil","year":"2005","journal-title":"UAI"},{"key":"ref26","year":"0","journal-title":"Xgboost parameters¶"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-23534-9_20"}],"event":{"name":"2020 IEEE International Conference on Big Data (Big Data)","location":"Atlanta, GA, USA","start":{"date-parts":[[2020,12,10]]},"end":{"date-parts":[[2020,12,13]]}},"container-title":["2020 IEEE International Conference on Big Data (Big Data)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9377717\/9377728\/09378154.pdf?arnumber=9378154","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,6,27]],"date-time":"2022-06-27T15:45:32Z","timestamp":1656344732000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9378154\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,12,10]]},"references-count":30,"URL":"https:\/\/doi.org\/10.1109\/bigdata50022.2020.9378154","relation":{},"subject":[],"published":{"date-parts":[[2020,12,10]]}}}