CSGO-Round-Winner-Classification

OpenML dataset with id 43430

Author name not available (Why is that?)

Full work available at URL: https://api.openml.org/data/v1/download/22102255/CSGO-Round-Winner-Classification.arff

Upload date: 23 March 2022

Dataset Characteristics

Number of features: 97 (numeric: 94, symbolic: 1 and in total binary: 1 )
Number of instances: 122,410
Number of instances with missing values: 0
Number of missing values: 0

Description

Context CS:GO is a tactical shooter, where two teams (CT and Terrorist) play for a best of 30 rounds, with each round being 1 minute and 55 seconds. There are 5 players on each team (10 in total) and the first team to reach 16 rounds wins the game. At the start, one team plays as CT and the other as Terrorist. After 15 rounds played, the teams swap side. There are 7 different maps a game can be played on. You win a round as Terrorist by either planting the bomb and making sure it explodes, or by eliminating the other team. You win a round as CT by either eliminating the other team, or by disarming the bomb, should it have been planted. Content The dataset was originally published by Skybox as part of their CS:GO AI Challenge, running from Spring to Fall 2020. The data set consists of 700 demos from high level tournament play in 2019 and 2020. Warmup rounds and restarts have been filtered, and for the remaining live rounds a round snapshot have been recorded every 20 seconds until the round is decided. Following the initial publication, It has been pre-processed and flattened to improve readability and make it easier for algorithms to process. The total number of snapshots is 122411. Skybox website: https://skybox.gg/ Learn more about CS:GO: https://en.wikipedia.org/wiki/Counter-Strike:_Global_Offensive View CS:GO on Steam Store: https://store.steampowered.com/app/730/CounterStrike_Global_Offensive/ Find in-depth information on competitive CS:GO: https://www.hltv.org/ Acknowledgements Thanks to Skybox for taking the time to sample all the snapshots and organising the challenge. It wouldn't be possible to publish any of this without their help. Inspiration

What types of machine learning models perform best on this dataset? Which features are most indicative of which teams wins the round? How often does the team with most money win? Are some weapons favourable to others? What attributes should your team have to win? Health, armor or money?

Data Dictionary Note: All snapshots are i.i.d in the sense that they each describe the state of a round and can therefore be treated individually. Although multiple snaphots can be taken from the same round. You are suppose to predict a label (round winner) based on each individual snapshot.

Variable Definition Key

time_left The time left in the current round.

ct_score The current score of the Counter-Terrorist team.

t_score The current score of the Terrorist team.

map The map the round is being played on. E.g. de_dust2, de_inferno and de_overpass

bomb_planted If the bomb has been planted or not. False = No, True = Yes

ct_health The total health of all Counter-Terrorist players. Player health in range 0-100.

t_health The total health of all Terrorist players. Player health in range 0-100.

ct_armor The total armor of all Counter-Terrorist players.

t_armor The total armor of all Terrorist players.

ct_money The total bankroll of all Counter-Terrorist players. Amount in USD.

t_money The total bankroll of all Terrorist players. Amount in USD.

ct_helmets Number of helmets on the Counter-Terrorist team.

t_helmets Number of helmets on the Terrorist team.

ct_defuse_kits Number of defuse kits on the Counter-Terrorist team.

ct_players_alive Number of alive players on the Counter-Terrorist team. Range 0 to 5.

t_players_alive Number of alive players on the Terrorist team. Range 0 to 5.

ct_weapon_X Weapon X count on Counter-Terrorist team. E.g. Ak47, Deagle and UMP45.

t_weapon_X Weapon X count on Terrorist team. E.g. Ak47, Deagle and UMP45.

ct_grenade_X Grenade X count on Counter-Terrorist team. E.g. HeGrenade, Flashbang.

t_grenade_X Grenade X count on Terrorist team. E.g. HeGrenade, Flashbang.

round_winner Winner. CT = Counter-Terrorist, T = Terrorist

Screenshots

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