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Gwoop Raises $ 1.8 Million For Esports Training Platform As He Starts Working With High School Gaming Leagues – TechCrunch

Earlier this year, I wrote about Gwoop, a team from Minnesota that creates a collection of browser games meant to help you get better at gaming in general. Their games measure things like how quickly you react, how accurately you move the mouse, or how fast you can aim at a randomly placed target, then provide all of those stats in a dashboard to show how you are doing. you (hopefully) improve over time.

Last time I spoke with Gwoop co-founder Gavin Lee he was already hinting at dreams of being the go-to analytics / training tool for the growing number of high school esports teams. More schools are starting to take esports seriously – and like any other type of trainer, esports coaches need a way to see who’s good at what, from tracking player improvements to over time and have their players do warm-up drills.

It appears that Gwoop is already making solid progress there; Lee tells me that Gwoop now works with “about 1,000 school programs in 40 states.” Now they’ve raised a $ 1.85 million round to get the ball rolling.

Gwoop’s platform is, and will continue to be, free to individual players – something Lee tells me he considers crucial. So how are they going to make money?

Image credits: Gwoop

Over the past few months, the company has created “Gwoop Teams,” which, as the name suggests, are designed for groups that train together. Through teams, coaches can assign training schedules, check if players are training, and see how each player is improving over time.

The basic version of Teams is free, supporting a roster of up to 30 players and two “games” – one “game” for your Rocket League players, another for your League of Legends players, your Fortnite players. , etc. For coaches who need more than that, Gwoops “Team Plus” offers a roster of 150 players and increases the number of games a coach can supervise. Lee tells me that Teams Plus costs around $ 350 a year.

Another area Lee told me they were exploring, although in its early days: using machine learning to help players (and their coaches) identify games they would already be in. good, based on their existing skills and rankings in other competitive games.

Lee tells me that this round was supported by several angels from Montreal, Klein Investments and a number of angels.

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