It is not difficult to sum up XDefiant, Ubisoft's new free-to-play arena-based shooter. It's Overwatch crossed with Call of Duty. Or maybe Apex Legends crossed with Counter-Strike. Whichever comparison you go for, what it definitely isn't is a wildly original video game. But that's not a problem if it works.

Imagine a game that might be described as the opposite of Half-Life 2, Left 4 Dead or Counter-Strike: Global Offensive. These are first-person shooters set in wartorn, post-apocalyptic cities, so their inverse might be a third-person game with no weapons at all, set in a warm, buzzing metropolis of friendly characters, maybe starring an adorable cat. Weirdly, the result could look a lot like Little Kitty, Big City, the first project from former Valve designer Matt T. Wood. In nearly 17 years at Valve, Wood helped build and ship the company's most notable titles, including Left 4 Dead, Left 4 Dead 2, Portal 2, CS:GO and both episodes of Half-Life 2. He was a founding member of the CS:GO project and worked on that series for six years; he was pivotal in crafting Portal 2's co-op mode, and he created choreography and combat scenes in Half-Life and Left 4 Dead. Level design was one of his specialties.

Did you miss a session from the Future of Work Summit? In 2019, San Francisco-based AI research lab OpenAI held a tournament to tout the prowess of OpenAI Five, a system designed to play the multiplayer battle arena game Dota 2. OpenAI Five defeated a team of professional players -- twice. And when made publicly available, OpenAI Five managed to win against 99.4% of people who played against it online. OpenAI has invested heavily in games for research, developing libraries like CoinRun and Neural MMO, a simulator that plops AI in the middle of an RPG-like world. But that approach is changing.

We all had really good relations outside of the game. We never argued outside the game. Any time there were arguments, it was always about in-game theoretical stuff. We just felt like we weren't progressing as a team because there was a lack of respect, and also the in-game relationships weren't that good. That's kind of like the foundation of a team; you've got to have that inner respect for each other.

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.

One theory, raised by Broomall, who coaches TSM in North America, is that the disparity between the two scenes can be explained by the regions' respective "Counter-Strike" scenes. In North America, the scene is inert, mostly discussed in the context of speculation around its apparent impending death. In Europe, however, "Counter-Strike" tournaments happen on a regular basis; a bounty of mid- and high-level organizations make it a hospitable environment for players. In North America, talented players who didn't have a shot in "Counter-Strike" made the jump to "Valorant," where they faced tons of other talented but unrecognized pros. In Europe, however, professionals had few incentives to leave the warm bosom of "Counter-Strike."

The researchers developed their approach for detecting cheaters using the popular first-person shooter game Counter-Strike. But the mechanism can work for any massively multiplayer online (MMO) game that sends data traffic to a central server. Their research was published online Aug. 3 in IEEE Transactions on Dependable and Secure Computing. Counter-Strike is a series of games in which players work in teams to counter terrorists by securing plant locations, defusing bombs and rescuing hostages. Players can earn in-game currency to buy more powerful weapons, which is a key to success.

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.

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.

Counter-Strike: Global Offensive's finally making the free-to-play pivot, ditching the $15 barrier to entry it's maintained since release in 2012. Starting today you can head over to Steam and grab the full game, including multiplayer modes, for free--though you can still pay $15 for "Prime" status and earn some extra skins. It seems like an obvious move to keep Counter-Strike competitive in the modern era, what with the rise of the battle royale genre. CS:GO is even getting its own take on the phenomenon, called CS:GO Danger Zone, an 18-player battle royale(ish) mode that involves scrounging for supplies and money around the map. Timing that release with the move to free-to-play could convince an entire new generation of Playerunknown's Battlegrounds players to give Counter-Strike a shot...maybe. But is that a good move for Counter-Strike and the people who love it?