● VOLUME 31 · AUGUST 13, 2026
How Game1 is Finding the Next US Soccer Star
Editor’s Note
As friend of the program Matthew Jester put it, tech money is flooding into sports.
This week brought two landmark transactions - and the ripple effects will be massive. Deep-pocketed, globally connected power players are moving into the space:
Bhatia runs AyBe Capital and is the son-in-law of Lakshmi Mittal of the ArcelorMittal fortune
Aditya Mittal is a minority owner of the Celtics, and was rumored to be involved in one of the final Seahawks bids
Also rumored to be in the consortium: Jeff Bezos and Eduardo Saverin
Josh Kushner and Bob Iger are reportedly buying the Lakers at a $12.5bn valuation - a new record for a sports-franchise sale
We’ve been calling this the anti-AI trade since I started No Huddle: long humans, long competition, long being together - because it’s the one thing AI can’t replace or fake.
As these stake sales pick up, keep following along to see which companies will actually shape what happens under the hood.
Much more on all of this soon - including a YouTube show where we will get into the deals, the operators, and where the capital is really headed. 👀
As always, if you want to be featured, connect with founders in the No Huddle family, or have suggestions to help No Huddle grow, just reply to this email or reach out directly to me at [email protected].
Let’s keep it rollin’! 🤘
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🎙 In the Pocket
How I am seeing the field across sports, media, entertainment, wellness and CPG

Every four years, America asks the same question: “When will U.S. soccer finally reach the next level?” This summer, the question was louder than ever.
The U.S. got a favorable draw - aided by the advantageous host-seeding structure - and won its first knockout match since 2002. For a moment, everything felt on track. Then Belgium ran them off the field in Seattle - and the debate reached a new level: Why is U.S. soccer still so far behind its peers? Why can’t we compete with countries a fraction of our size?
I'll state my view upfront: as things stand, I’m less bullish on American soccer than most of the takes in my feed. Don’t get me wrong - I’d love nothing more than the US to become a global soccer powerhouse. The growth prospects are real, as are the pockets of fandom and Pulisic jerseys everywhere. Those are meaningful tailwinds.
The problem, in my view, sits further upstream - and I’ll own this as the contrarian take: youth soccer isn’t uniquely broken. It runs on the same machine as basketball, baseball, football, and hockey. Pay for a club. Drive to a showcase. Get seen. Hope someone important is watching your kid’s field instead of the one next to it.
The system is the same across American youth sports. What changes in soccer is what sits at the top of the funnel.
In every other American sport, the summit is here. A 12-year-old hooper can watch the best league on the planet in his time zone, on his TV, and often in his city. The same is true in football, baseball, and hockey.
That dream is expensive and it's long odds, but it's legible. A kid can see the destination from where he stands. He can go to the arena, watch his hero, and understand the path, however difficult, from his field to that stage.
I’ll save my broader thoughts on what that means for U.S. soccer and MLS. For this issue, I want to stay closer to the ground: youth development, access, and cost - using soccer as the lens in the wake of the World Cup.
Let's do the math:
There are 20.5 million soccer participants in this country and 4 million+ registered youth players across 10,000+ clubs.
The average family now spends $1,188 a year on soccer - up 46% since 2019. At the competitive club level, that number is a punchline compared to what people actually pay.
American families drop north of $40 billion a year on youth sports.
Kids from households making $100K+ play regularly at 40%. Under $25K? 24%. And low-income kids are one-third as likely to make a travel team.
So the filter that determines who gets additional opportunities to develop in this country isn't usually a scout's eye. It's financial means.
And the average American kid now quits sports entirely by age 11. Eleven!
We built a system that asks families for thousands of dollars, hundreds of highway miles, an enormous time commitment and single-sport specialization by middle school - and for almost everyone, the ROI is burnout or a player trying to wedge themselves into a college career they aren’t actually ready for - or offered.
And here's a real example from the Game1 team that shows how easily a kid slips through - even in a system built to catch them:
A first-division Swiss club had ten years of standardized player testing sitting in a spreadsheet. When Game1 ran it, one of the highest pro-potential scores they'd ever seen at that age belonged to a center back who quit at 14. Nobody at the club could remember why. So Game1 called around - turns out he couldn't afford the bus ticket to training.
$3.00. Three dollars. Less than your cold brew at Dunkin' (there’s my Boston bias shining through). That's what stood between that kid and a shot at a professional career. And that's Switzerland, where the barriers to play on a team are much lower than here in the States. You put that same kid in NYC and the cover charge is thousands plus a caregiver with entire weekends free to travel and play in tournaments.
The club had a decade of data with this kid's name sitting at the top of it the whole time, but nobody was there to go the extra mile to help, support, and develop him. Look, no one example, app, or process is fixing pay-to-play. Nobody's smartphone is making club soccer free - everything I laid out above is structural, and it'll take leagues, federations and a lot of money to move.
But that's exactly why this matters. Those problems aren't going anywhere - so the real question is what we can do inside a system that's going to be broken for a while.
I say we focus on not losing - through burnout or cost - the kids we already have. That means the late bloomers and the quiet ones who aren’t in flashy gear or friends with the coach. And not just the ones who measure with the highest potential or college/pro score. The kids who play because they love it deserve the same. Giving youth athletes a plan to develop, be coachable and be the best player and teammate they can be is what sports are all about!
Meet Game1.
More below. 👇
📺 The Watch List
Game1
A mini investment memo on the stars of tomorrow

The Company: Game1.ai
The Business in a tweet: Game1 is the AI data layer for youth soccer (ages 10-16). It provides standardized combine-style testing run off smartphones - no hardware, no video crew - to measure a player's technical, physical, mental, and biological development, then benchmarks that against 500,000+ data points currently pulled from elite European academies. Every player gets a path forward. Every parent and coach gets objective proof of progress.
The 101:
Industry: Sports Technology / AI-Powered Talent Identification & Player Development
Headquarters: New York, NY
Year Founded: 2025
Founding Team/Current Leadership:
Amir Donath - Co-Founder & CEO. Grew up in Switzerland and went through the Swiss academy system; started his career at McKinsey, spent several years at a tech startup, then moved to the US in 2023 for his Stanford MBA, where Game1 was born.
Yaniv Donath - Co-Founder & CTO. Amir's brother. Cambridge PhD (physics / machine learning, with research in early-universe cosmology) and an AI researcher at Stanford.
Advisory Board includes:
Tatjana Haenni - CEO of RB Leipzig and the first woman to hold a CEO role at a Bundesliga club. Also former FIFA Director of Women's Football and NWSL Chief Sporting Director
Krishna Nathan - former CIO of S&P Global
Julie Haddon - former NWSL CMO
Employees: Lean team <10
Fundraising Status:
Pre-seed. Raised $1.1M to-date from current and former athletes, club presidents, and institutional investors.
If you’re interested in learning more or meeting the team, respond to this email or reach out to [email protected].

Business Model:
B2B2C SaaS subscriptions. Game1 sells to clubs and academies; the clubs pass the cost through to parents. Sitting inside the club's curriculum instead of a parent's phone is the retention strategy.
Why not D2C?
part of the testing protocol has a team component
consumer soccer-training apps churn violently once the novelty wears off.
Results run through a neural net trained on the European academy set and come back with two key outputs:
A probability of reaching a given level (pro, D1, D2, D3)
An automated individual development plan (IDP) showing what the player should work on next. The front page of the report is in plain language (using Whoop’s UI as inspiration): giving users three focus areas and progress bars with the deep stats a click away.
Tests repeat every few months, and the change between them is itself an input.

Traction - entering US market this year
20+ partner clubs and academies
Partnership closed with several MLS clubs; also serving large development academies including Bethesda SC in Maryland
Working with several Champions League–playing clubs in Europe
Recently partnered with Stanford Soccer to deploy the technology at Stanford's ID camps
Covered by Sports Business Journal in June 2026 on the US launch

Deep Dive:
Pros:
Proprietary, ever-growing dataset is the biggest moat
Game1 has 500,000+ data points from several dozen European academies (some going back a decade). Nobody else in youth soccer has a longitudinal set that connects a 13-year-old's test scores to what that player actually became
Zero hardware. All users need are standard smartphones plus computer vision. No cameras to install, no GPS bibs, no lasers, no film crew
Game1 provides a rounded approach by measuring four dimensions together: physical, technical, mental, and biological. It measures what a player is as a full product, and not just what happens in a game.
The algorithm is built to surface late bloomers and not highlight-reel culture or the early developers
The model rewards trainability - it scores improvement, not just ability. Because testing repeats every few months, the rate of change is itself a feature
Output is prescriptive, not descriptive. Game1 doesn't just rate a player; it returns a projected ceiling (pro, D1, D2, D3) and what that player should work on next, helping them actually develop those skills to improve, not giving them a static score like most US-based systems do.
Cons:
Tough market to sell into. Everyone is selling something to soccer academies right now and club directors are overwhelmed by the influx of AI-enabled services being pitched to them
The incentive triangle is still working itself out:
Players are the user, parents are the payer, clubs are the buyer, and coaches (who want to win Saturday) are structurally misaligned with academy directors (who want to develop players).

Youth sports bottleneck: There’s a lot of money flowing into youth sports right now, and just as much heat on the other side pushing back. No matter what, it’s a market that will be around forever
Unproven US market - maybe US Soccer isn't ready to be a tech-enabled system
Comparables:

Game1 Differentiator: Everyone else in this set analyzes what a player did. Game1 projects what a player can become. Game1 is the only company benchmarking against a proprietary dataset with over a decade of data that already knows how those careers turned out. Game1 also brings unique features such as biological age to flag late developers and a testing protocol that needs nothing but two phones.
📶The Signal (No Huddle’s Take):
I outlined some of my thoughts on the key issues I see surrounding both American soccer and youth sports earlier in this piece, so let’s focus on what No Huddle does best - evaluating the landscape and working with founders who are building actionable solutions to the problems out there.
What are the core problems, and how will Game1 solve them?
Problem 1 - Winning and highlights over development: The whole apparatus optimizes for Saturday. Academies and coaches want to win games and are measured on winning games, not on developing players - and the tools built to serve that (film, clips, highlight reels) can only capture kids who already get minutes. The selection data is damning: elite academies show birth-date ratios near 3:1 favoring players born in the first half of the year at U13-U15, and biological maturity predicts physical performance better than chronological age does. We pick the kids who grew first and call it talent identification. Game1 changes the unit of measurement from footage to a standardized test, so a bench player and a starter produce equally readable data. Then the corrections stack on top - first a biological peer comparison (e.g. a 14-year-old who's biologically 12 isn't graded against one who's biologically 16). Then reshuffled small-sided games that isolate a player's impact from his teammates and his position. The output is a growth trajectory, not a viral clip (Coming for you next, AAU basketball!)
Problem 2 - Lack of actionable improvement plans: "Get better" isn't a plan. Individualizing twenty kids is labor no club can staff, so training defaults to one-size-fits-all - Amir's own memory makes the case: a fast kid who wants to work on his first touch is told “everyone runs today.” Game1 gives players skills to work on and tracks progress with re-tests every few months. That's real feedback for the kid, a receipt for the parent, and a life skill either way. Progress isn't always linear!
How do you make a highlight reel of a kid who doesn't get the ball? Underneath the AI buzzwords, almost every company in this category is a visibility business. Hudl (through its Wyscout acquisition), Eyeball, and Taka all capture footage, cut it, tag it, and get a player in front of someone who matters.
That's a real and valuable service, no doubt. But it has a bias embedded from the jump.
Film requires minutes, minutes require a roster spot on a decent team, in a real league, at a club that films its games and travels to the showcases where scouts sit. So the kids the video layer discovers are - traditionally (more on that in a future edition) - the kids the system already selected. Video scouting doesn't open the funnel, it just amplifies the existing funnel.
Game1 flipped the input on its head. Game1 doesn’t need minutes, it just requires two phones and a young athlete ready to get better. That single design decision is what separates this company from the other logos in the comp table.
Having come up through that system himself, Amir noticed that European academies had been running the same standardized tests every six months for as long as a decade, but did nothing with the data. He then went club to club asking for access to that data, and got creative and offered a trade: let me build you a beautiful presentation showing how your academy developed over the last ten years. That worked. Dozens of academies and thousands of players became the foundation of the Game1 database - and some of those players went on to star at the professional ranks.
Everyone else in youth soccer has data about how the game went. Game1 has data about how the story ended. It's a decade of test scores attached to known outcomes - who made it pro, who went D1, who flamed out at 17, who had more potential but lacked the resources and infrastructure to get there. And buried inside that answer key is one of the best ideas in the company. Because the testing repeats every few months, the model doesn't just score where you are - it scores how fast you're moving. The Game1 team says willingness to improve is heavily rewarded by the algorithm, and what do nearly all players in the data set who reached the highest levels have in common? A very steep learning curve. That is huge - the kid who tests poorly, or maybe isn’t a star at age 12, but then works at it is worth more to this model than the kid who tests well and coasts - and almost nothing else in youth sports is built to reward that.
We see some parallels to what’s happening in healthcare nowadays - the shift from a historically reactive industry to one that is proactive. Say what you want about the overcorrection to optimizationmaxxing, but I still think it’s a net win for society if we’re forward-looking thinkers, not dwelling on the past or when it’s too little too late.
In talking to some industry leaders about Game1, a common somewhat-joking reaction was “I’m sure coaches, directors and parents love being told they are wrong.” That’s a fair critique, but the Game1 team has two good answers to dispel that notion. Amir says that on a first test, three or four of the top five players Game1 surfaces are the ones the coach already had in mind. That confirmation is what buys permission to be believed on the one or two they missed. If the product can build a layer of trust and support for all stakeholders, that will get them to buy in. In addition, the data helps to avoid inevitable conflict. Instead of parents or players complaining about coaches' bias or their kid not getting enough playing time, the data can help paint the proper picture and motivate all parties to improve. And it's landing with the people who'd know. Game1 is already working with innovators in the space such as LA Galaxy, Houston Dynamo, Bethesda SC, Stanford, and a slate of MLS NEXT development programs - plus Champions League clubs, Bundesliga sides, and the Austrian champion overseas.
What does Game1 need to figure out next?
Does the European model travel? Fundamentally speaking, the US and Europe operate completely differently in every sense of sport, business, life and culture. The benchmark set is elite European academy players - kids already selected, already coached daily, already in a development system. The US population is 4M+ registered youth players (20.5M total participants) in a pay-to-play market with wildly uneven coaching. How difficult will it be to create the same American baseline?
Game1's site claims a 95% hit rate on predicting future outcomes - the single most valuable receipt they could publish is what's behind it.
Answer those two and Game1 evolves from a promising thesis into an essential layer in US (and global) soccer development - and something that only improves over time with more data and outcomes factored in.
Game1 also isn't operating in a vacuum, the visibility layer for soccer is consolidating. aiScout - now majority-owned by Saudi-backed HUMAIN - works with MLS, MLS NEXT and MLS NEXT Pro. Hudl just made ECNL the first US youth league inside Wyscout, free to clubs already on a Hudl package, launching this fall. Between them that's most of the elite American pipeline. When visibility gets bundled, the only defensible ground left is measurement, which is what Game1 sells.
The category as a whole is helping with visibility: be seen, be clipped, be in the database. Game1 is solving for something harder and more useful, which is legibility - making a player objectively readable whether or not anyone has been watching. While these sound similar, they are not. Visibility rewards the kids already inside the system. Legibility is the only version that works for the ones outside it.
The takeaway? Game1 - and US soccer in general - may never have a better runway than the next 24 months. The World Cup just put $2.7 billion of latent youth-soccer demand and 5.3 million interested-but-inactive American kids on the table. One thing is for sure, the US doesn’t have a youth sports talent problem - our strength in other sports proves that. We have a finding and development problem. And Game1 is here to change that.
If you’re interested in learning more, or meeting the team, respond to this email or reach out to [email protected].
From the archive
If Game1’s effort to make player development measurable caught your attention, revisit Volume 20 on Koomba. That issue examined the health infrastructure surrounding young athletes; Game1 adds the measurement layer—turning development into visible, actionable progress.
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