[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-124207-en":3,"doc-seo-124207-105":30,"detail-sidebar-cat-0-en-105":92},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":20,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},124207,1099514067415,"Rowan","https://ap-avatar.wpscdn.com/avatar/100002539d78ffe74a7?x-image-process=image/resize,m_fixed,w_180,h_180&k=1779092875211072502",8,"Research & Report","A Machine Learning Based Predictive Analysis Use Case For eSports Games","League of Legends (LoL), a competitive MOBA with large esports tournaments, is analyzed to predict match outcomes and assess how feature selection influences predictive performance. The study trains machine learning classifiers on historical match data retrieved through Riot Games’ official API, addressing missing values. Team-level models use 1,045 training instances and player-level models use 5,232, with seven algorithms compared. AdaBoost on team data reaches over 98% accuracy, and feature selection raises Logistic Regression and Gradient Boosting accuracy from 89%/96% to 98%.","RESEARCH ARTICLE  \nA Machine Learning Based Predictive Analysis Use Case For eSports Games  \nAtakan Tuzcu a  , Emel Gizem Ay a†, Ayşegül Umay Uçar a  , Deniz Kılınç a   \na Department of Computer Engineering, University of Bakırçay, İzmir, Turkey † [aemelgizem@gmail.com](aemelgizem@gmail.com) , corresponding author  \nRECEIVED MARCH 5, 2023  \nACCEPTED APRIL 25, 2023  \nCITATION Tuzcu , A. , Ay, E.G. , Uçar, A. U. , & Kılınç . D. (2023) . A machine learning based predictive analysis use case for eSports games. Artificial Intelligence Theory and Applications, 3(1), 25-35.  \nAbstract  \nLeague of Legends (LoL) is a popular multiplayer online battle arena (MOBA) game that is highly recognized in the professional esports scene due to its competitive environment, strategic gameplay, and large prize pools. This study aims to predict the outcome of LoL matches and observe the impact of feature selection on model performance using machine learning classification algorithms on historical game data obtained through the official API provided by Riot Games. Detailed examinations were conducted at both team and player levels, and missing data in the dataset were addressed. A total of 1045 data were used for training team-based models, and 5232 data were used for training player-based models. Seven different machine learning models were trained and their performances were compared. Models trained on team data achieved the highest accuracy of over 98% with the AdaBoost algorithm. The top 10 features that had the most impact on the prediction outcome were identified among the 47 features in the dataset, and a new dataset was created from team data to retrain the models. After featureselection, the results showed that the accuracy of Logistic Regression increased from 89% to 98% and the accuracy of Gradient Boosting algorithm increased from 96% to 98% .  \nKeywords: league of legends; riot game; machine learning; random forest; gradient boosting  \n1. Introduction  \nMultiplayer Online Battle Arena (MOBA) games are a genre of games that offer a teambased combat experience, requiring strategy, coordination, and skill. The primary objective in MOBA games is to destroy the opponent team's main base. Sports analyticsis a method used in analyzing player performance, team strategies, and predicting competitive outcomes by utilizing data obtained from such games. This study was conducted using data from one of the MOBA games, League of Legends (LoL) . Similar to other MOBA games, LoL follows a 5v5 game style, where teams consist of 5 players in roles such as top lane, mid lane, jungle, marksman, and support. The tasks of players based on these roles vary according to different strategies. Due to the combination of limited parameters in the game, many possible game strategies can be formed, as the items obtained during the game can elicit different reactions from the characters.  \nLeague of Legends (LoL) is a team game, and the data of all five players in the team should be taken into consideration. Poor performance of some players can be  \nPermission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than AITA must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission [and/or a fee. Request permissions from info@aitajournal.com](and/or a fee. Request permissions from info@aitajournal.com)  \nArtificial Intelligence Theory and Applications , ISSN: 2757-9778. ISBN : 978-605-69730-2-4 © 2023 University of Bakırçay  \ncompensated to a certain extent, and there is still a possibility of the team winning. Individual player evaluations can lead to inaccurate predictions of game outcomes. ","cbCaioY5tqj6JJ2g","https://ap.wps.com/l/cbCaioY5tqj6JJ2g","pdf",473276,1,11,"English","en",105,"# Introduction\n## Game analytics and MOBA context\n# Related Works\n## Prior studies on game data and prediction\n# Materials and Methods\n## Dataset collection and preprocessing\n## Feature selection and model training\n# Results and Discussion\n## Model performance comparison\n## Impact of feature selection\n# Conclusion","[{\"question\":\"What is the main goal of the study on eSports games?\",\"answer\":\"The study aims to predict the outcome of League of Legends matches and evaluate how feature selection affects model performance.\"},{\"question\":\"How is the dataset created for model training?\",\"answer\":\"Match data is retrieved via Riot Games’ official API, focusing on recent matches, then organized into team-level and player-level datasets with missing data handled.\"},{\"question\":\"Which model and data level achieved the best prediction accuracy?\",\"answer\":\"Team-based models trained with AdaBoost achieved the highest accuracy, exceeding 98%.\"}]","A Machine Learning Based Predictive Analysis Use Case For eSports Games | PDF",1785821019,28,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":87,"head_meta":89,"extra_data":91,"updated_unix":28},"a-machine-learning-based-predictive-analysis-use-case-for-esports-games","",{"@graph":36,"@context":86},[37,54,69],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/a-machine-learning-based-predictive-analysis-use-case-for-esports-games/124207/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":63,"encodingFormat":61,"isAccessibleForFree":64,"interactionStatistic":65},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-05","2026-08-04",true,{"@type":66,"interactionType":67,"userInteractionCount":20},"InteractionCounter",{"@type":68},"ViewAction",{"@type":70,"mainEntity":71},"FAQPage",[72,78,82],{"name":73,"@type":74,"acceptedAnswer":75},"What is the main goal of the study on eSports games?","Question",{"text":76,"@type":77},"The study aims to predict the outcome of League of Legends matches and evaluate how feature selection affects model performance.","Answer",{"name":79,"@type":74,"acceptedAnswer":80},"How is the dataset created for model training?",{"text":81,"@type":77},"Match data is retrieved via Riot Games’ official API, focusing on recent matches, then organized into team-level and player-level datasets with missing data handled.",{"name":83,"@type":74,"acceptedAnswer":84},"Which model and data level achieved the best prediction accuracy?",{"text":85,"@type":77},"Team-based models trained with AdaBoost achieved the highest accuracy, exceeding 98%.","https://schema.org",{"og:url":52,"og:type":88,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":90,"canonical":52},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":93},[94,98,102,106,111,116,121,124,129,132,136],{"id":20,"doc_module":4,"doc_module_name":46,"category_name":95,"show_sort_weight":96,"slug":97},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":99,"show_sort_weight":100,"slug":101},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":46,"category_name":103,"show_sort_weight":104,"slug":105},"Exam",70,"exam",{"id":107,"doc_module":4,"doc_module_name":46,"category_name":108,"show_sort_weight":109,"slug":110},5,"Comic",60,"comic",{"id":112,"doc_module":4,"doc_module_name":46,"category_name":113,"show_sort_weight":114,"slug":115},6,"Technology",50,"technology",{"id":117,"doc_module":4,"doc_module_name":46,"category_name":118,"show_sort_weight":119,"slug":120},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":122,"slug":123},30,"research-report",{"id":125,"doc_module":4,"doc_module_name":46,"category_name":126,"show_sort_weight":127,"slug":128},9,"Religion & Spirituality",20,"religion-spirituality",{"id":127,"doc_module":4,"doc_module_name":46,"category_name":130,"show_sort_weight":127,"slug":131},"World Cup","world-cup",{"id":133,"doc_module":4,"doc_module_name":46,"category_name":134,"show_sort_weight":133,"slug":135},10,"Lifestyle","lifestyle",{"id":137,"doc_module":4,"doc_module_name":46,"category_name":138,"show_sort_weight":107,"slug":139},19,"General","general"]