Individual Performance in Team-based Online Games
Harvard Dataverse (Africa Rice Center, Bioversity International, CCAFS, CIAT, IFPRI, IRRI and WorldFish)
View Archive InfoField | Value | |
Title |
Individual Performance in Team-based Online Games
|
|
Identifier |
https://doi.org/10.7910/DVN/B0GRWX
|
|
Creator |
Sapienza, Anna
Zeng, Yilei Bessi, Alessandro Lerman, Kristina Ferrara, Emilio |
|
Publisher |
Harvard Dataverse
|
|
Description |
League of Legends dataset associated with the paper titled: Individual Performance in Team-based Online Games by Sapienza, A., Zeng, Y., Bessi, A., Lerman, K., Ferrara, E. (Royal Society Open Science 5 180329, 2018) The dataset adopted for this study was collected using the League of Legends' Riot Games API (Riot Games API: https://developer.riotgames.com/) It consists of 435,000 matches played by a sample of 1,120 of the most active players, i.e., those who played more than 100 games. The data contains information about matches, including match time and duration, and the number of deaths, kills, earned gold, gold spent, etc. for each player in each match. |
|
Subject |
Computer and Information Science
|
|
Contributor |
Ferrara, Emilio
|
|