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Master's Thesis in Geography Geoinformatics Spatial Analytics In Master’s thesis in Geography Geoinformatics Spatial analytics in competitive gaming and e-sports Timo Ijäs 2021 Supervisor: Petteri Muukkonen Master’s Programme in Geography Faculty of Science UNIVERSITY OF HELSINKI Faculty Department Faculty of science Department of geosciences and geography Author Ijäs, Timo Topias Title Spatial analytics in competitive gaming and e-sports Subject Geography (geoinformatics) Level Month and Year Number of Pages Master’s thesis May 2021 168 Abstract The topic of this thesis is spatial analytics in competitive gaming and e-sports. The way in which players analyze spatial aspects of gameplay has not been well documented. I study how game, genre and skill level affect the use of spatial analysis in competitive gaming. My aim is also to identify the benefits and challenges of spatial analytics, as well as the need for new spatial analytical tools. Four games of different popular competitive gaming genres were chosen for the study. An online survey was conducted which resulted in a cross-sectional dataset of 2453 responses. It was analyzed using ordinal logistic regression and histogram-based gradient boosting in a cross-validating manner. Open-field answers were summarized using state-of-the-art deep learning methods and analyzed with inductive content analysis. Additionally, experts of each game were interviewed. The results show that the use and understanding of spatial analysis is largely not game- or genre dependent. Players grow spatial skills along with their skill level and start using more complex spatial analytical methods more frequently as their skill level rises. It is exceedingly rare that expert players do not analyze spatial aspects of their gameplay. There is a need for different kinds of spatial analytics tools in all competitive games, and the benefits of advanced tools to a player and the community can be large. However, the tools need to be highly contextualized, fine-tuned for each game specifically, and tailored to the players’ needs. Creating new tools for spatial analytics is something useful for competitive gaming as a whole. The inclusion of more detailed spatial analytical tools can lead to a new era of competitive gaming. E-sports is a rapidly growing phenomenon, and the analytics that support its growth should follow. Keywords Data science, e-sports, game research, geoinformatics, spatial analysis Where deposited E-thesis, HELDA database Additional information HELSINGIN YLIOPISTO Tiedekunta/Osasto Laitos Matemaattis-luonnontieteellinen tiedekunta Geotieteiden ja maantieteen osasto Tekijä Ijäs, Timo Topias Työn nimi Spatial analytics in competitive gaming and e-sports Oppiaine Maantiede (geoinformatiikka) Työn laji Aika Sivumäärä Maisteritutkielma Toukokuu 2021 168 Tiivistelmä Tämän tutkielman aihe on spatiaalinen analytiikka kilpapelaamisessa ja e-urheilussa. Olemassaoleva tutkimus on puutteellista liittyen pelaajien tapoihin analysoida pelaamisen spatiaalisia puolia. Tutkin erityisesti, kuinka eri pelit, genret ja pelaajan taitotaso vaikuttavat spatiaalisen analyysiin. Tavoitteeni oli tunnistaa spatiaalisen analytiikan hyötyjä ja haasteita, sekä kartoittaa uusien työkalujen tarvetta. Valitsin tutkimuksen fokukseksi neljä peliä eri suosituista kilpapeligenreistä. Tein kyselylomaketutkimuksen, jolla sain 2453 vastauksen intersektionaalisen datasetin. Analysoin sen käyttäen ordinaalista logistista regressiota sekä histogram-based gradient boosting-menetelmää ristiin validoiden. Kysymyslomakkeen avoimet kysymykset tiivistettiin käyttäen syväoppimismenetelmää ja analysoitiin induktiivisella sisällön analyysilla. Samalla menetelmällä analysoitiin myös jokaisen pelin ammattilaisten haastattelut. Tulokset näyttävät, että spatiaalisen analyysin käyttö ja tuntemus ei suurelta määrin ole kytköksissä peliin tai genreen. Pelaajien spatiaaliset taidot, analyysin käyttö ja monimutkaisuus sekä ymmärrys kasvavat pelikokemuksen karttuessa. On äärimmäisen harvinaista, että huippupelaajat eivät analysoi pelaamisensa spatiaalisia puolia. Spatiaalisen analyysin työkaluille on tarve e-sportsissa pelistä riippumatta ja työkalut hyödyttävät sekä pelaajia että pelaajayhteisöjä kokonaisuutena. Uusien työkalujen tulee kuitenkin olla yksityiskohtaisia, luotuja pelaajien tarpeita varten, sekä sisältää tietoa analysoitavan kohteen viitekehyksestä. Uusien spatiaalisten työkalujen luominen on yleishyödyllistä kilpapelaamiselle ja avaa uusia mahdollisuuksia genrestä riippumatta. E-sports on voimakkaasti kasvava ilmiö ja sitä tukeva analytiikka tulee kasvamaan sen myötä. Avainsanat Datatiede, e-sports, geoinformatiikka, pelitutkimus, spatiaalinen analyysi Säilytyspaikka E-tutkielma, HELDA tietokanta Muita tietoja Table of contents 1 INTRODUCTION .................................................................................................... 1 2 BACKGROUND ...................................................................................................... 6 2.1 E-sports ............................................................................................................. 6 2.2 Players ............................................................................................................... 7 2.3 E-sports events .................................................................................................. 8 2.4 Game genres ..................................................................................................... 9 2.5 Spatial analytics in e-sports ............................................................................ 11 2.5.1 Overview of spatial analytics in e-sports .............................................. 11 2.5.2 Game data gathering methods ............................................................... 12 2.5.3 Data processing ..................................................................................... 13 3 DATA AND METHODS ....................................................................................... 15 3.1 Four games of focus ........................................................................................ 15 3.2 Research methods ........................................................................................... 18 3.2.1 Data gathering and schedule of the study ............................................. 18 3.2.2 Philosophical context ............................................................................ 18 3.3 Literature review ............................................................................................. 20 3.4 Questionnaire .................................................................................................. 21 3.4.1 Creating the questionnaire .................................................................... 21 3.4.2 Testing the questionnaire ...................................................................... 27 3.4.3 Campaign of the questionnaire ............................................................. 28 3.4.4 Data preprocessing ................................................................................ 28 3.4.5 Analysis ................................................................................................. 30 3.4.6 Handling open-field questions .............................................................. 35 3.5 Interview study ............................................................................................... 36 4 FINDINGS FROM SYSTEMATIC LITERATURE REVIEW ............................. 39 4.1 General results ................................................................................................ 39 4.2 Prediction ........................................................................................................ 42 4.3 AI.....................................................................................................................43 4.4 Behavior .......................................................................................................... 44 4.5 Various analytics ............................................................................................ 44 4.6 Non-scientific literature .................................................................................. 46 4.7 Analysis tools .................................................................................................. 48 4.8 Video content .................................................................................................. 51 5 RESULTS FROM QUESTIONNAIRES AND INTERVIEWS ............................ 53 5.1 Questionnaire results ...................................................................................... 53 5.1.1 Total answer numbers and skill level distributions ............................... 53 5.1.2 Played times .......................................................................................... 54 5.1.3 Tournament attendance ......................................................................... 58 5.1.4 Interests in game ................................................................................... 59 5.1.5 Essential abilities for play success ........................................................ 61 5.1.6 Ways of analyzing spatial aspects of gameplay .................................... 70 5.1.7 Ways of analyzing spatial aspects of in-game elements ....................... 79 5.1.8 Frequency of spatial analysis ................................................................ 85 5.1.9 Tools used for spatial analysis .............................................................. 89 5.1.10 Knowledge
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