Many esports use a pick and ban process to define the parameters of a match before it starts. In Counter-Strike: Global Offensive (CSGO) matches, two teams first pick and ban maps, or virtual worlds, to play. Teams typically ban and pick maps based on a variety of factors, such as banning maps which they do not practice, or choosing maps based on the team's recent performance. We introduce a contextual bandit framework to tackle the problem of map selection in CSGO and to investigate teams' pick and ban decision-making. Using a data set of over 3,500 CSGO matches and over 25,000 map selection decisions, we consider different framings for the problem, different contexts, and different reward metrics. We find that teams have suboptimal map choice policies with respect to both picking and banning. We also define an approach for rewarding bans, which has not been explored in the bandit setting, and find that incorporating ban rewards improves model performance. Finally, we determine that usage of our model could improve teams' predicted map win probability by up to 11% and raise overall match win probabilities by 19.8% for evenly-matched teams.

Esports, despite its expanding interest, lacks fundamental sports analytics resources such as accessible data or proven and reproducible analytical frameworks. Even Counter-Strike: Global Offensive (CSGO), the second most popular esport, suffers from these problems. Thus, quantitative evaluation of CSGO players, a task important to teams, media, bettors and fans, is difficult. To address this, we introduce (1) a data model for CSGO with an open-source implementation; (2) a graph distance measure for defining distances in CSGO; and (3) a context-aware framework to value players' actions based on changes in their team's chances of winning. Using over 70 million in-game CSGO events, we demonstrate our framework's consistency and independence compared to existing valuation frameworks. We also provide use cases demonstrating high-impact play identification and uncertainty estimation.

A teenager has developed an AI system that can detect over 98% of cheaters in competitive online game CounterStrike: Global Offensive. The global eSports industry has exploded in the past several years, with tournament prize pools now reaching into the tens of millions of pounds and top players around the world becoming millionaires. With such high pressure to succeed, some competitive online games have become breeding grounds for people using cheating software such as auto-aim and wall-visibility hacks to get an edge on the competition. One teenage player of the game CounterStrike: Global Offensive has had enough of cheaters ruining the game and has developed an AI that can successfully detect cheating with a reported 98.36% success rate. The player, who goes by the name 2eggs, was also recently awarded over $11,000 US in bug bounties by CounterStrike's developer Valve for helping to identify security risks, and has helped develop databases that keep track of banned players.

Artificial intelligence (AI) specialists from the esports analysis and visualisation company will test prediction models at BLAST Pro Series Copenhagen 2020. The initiative will feature two competitions, organised by Skybox Technologies and RFRSH Entertainment, in collaboration with Copenhagen Capacity. The first will offer a $5,000 reward for the team with the best code, and the second will offer invitations to BLAST Pro Series Copenhagen for the top 5 participating teams, where they will run their code during live matches. The winning team will be announced before the grand final. Not only is this fascinating technology in its own right, but holding a competition like this, at a prestigious event, could help kickstart some serious careers for those involved, so its fantastic to see Skybox, RFRSH and Copenhagen Capacity working together to foster innovation.

Sigma is the 31st hero in the video game Overwatch. Video game playing fields are too often venomous playing fields. A bisexual player in Activision Blizzard's popular online first-person shooter game "Overwatch" reported being sick to his stomach after being subjected to transphobic and homophobic slurs. A Jewish player says he was told in an unnamed online game that he belonged in Auschwitz. And an African American participant claimed to be harassed in yet another multiplayer game for "sounding black." These were among the U.S. online gamers who anonymously voiced their experiences as part of a new survey on gaming and harassment, released today by the Anti-Defamation League's Center on Technology & Society.

For its anti-cheat program, Valve now relies on neural networks that are trained through Deep Learning. At GDC, the manufacturer introduced its protection system for Counter-Strike. This is a constant battle, which is conducted by manufacturers against cheaters in online games. Valve, one of the largest operators of online games such as Dota 2 and Counter-Strike: Global Offensive, now rolls out heavy artillery to detect Aim Bots and Speedhacks and bans cheaters on their servers. Because traditionally Counter-Strike is a find for cheaters.

A screen, center, shows a professional video game competition between teams sitting on either side. Unionization of players is a big topic in the industry after several years of fast growth. A screen, center, shows a professional video game competition between teams sitting on either side. Unionization of players is a big topic in the industry after several years of fast growth. With threats of strikes and retaliatory layoffs, and no shortage of sniping on social media, a battle last winter had the stamps of a modern-day union war.