The Playermetry Story
The Hunt for Hidden Talent
My name is Marian Vanca. I’ve spent over twelve years as a software developer, building systems in the logical world of code. But my real obsessions have always been football and, most recently, one simple idea inspired by Moneyball:
Data can reveal value where the market isn’t looking.
For years, as a Liverpool FC supporter and a football analytics aficionado, I kept asking myself: Why do smart clubs still make so many bad signings?
The Transfer Coin Flip
In his book How to Win the Premier League, former Liverpool Director of Research Ian Graham revealed something shocking: around 46% of €10million-plus transfers between 1992 and 2021 in top leagues failed. In a separate analysis of the top 100 transfers from the “big five” leagues, more than 50% of transfers proved to be unsuccessful.
That’s not a small inefficiency. That’s a coin flip with millions at stake.
And if this happens in the richest leagues in the world, with access to optical tracking and elite analytics departments, what happens in lower leagues?
That’s where the real inefficiency lives.
The Data Black Hole
In emerging and lower-tier leagues, advanced metrics simply don’t exist. No xG models. No tracking data. No detailed event feeds.
Just match sheets:
Who played
Who scored
Who got sent off
Final result
Meanwhile, clubs are still expected to make high-stakes decisions. They rely on intuition, short highlight clips, agent recommendations… and often churn through squads season after season.
I saw this firsthand watching my hometown club, Olimpia Satu Mare, in Romania’s third tier. Talented players would have one strong stretch, then disappear. Clubs would replace half their squads every summer. Not because they were reckless but because they lacked objective clarity.
The margin for error in lower leagues is razor-thin. Yet decisions are being made in the dark.
The Epiphany
Then I realized something: If advanced data doesn’t exist, maybe you don’t need it.
The simplest, most universal data point in football is this: What happened to the score while a player was on the pitch?
But raw “Plus/Minus” isn’t enough. Context matters. Scoring against the league leader is not the same as scoring against the bottom team. Conceding to a minnow should hurt more than conceding to a giant.
That’s when Playermetry was born.
A Weapon for the Underdog
Playermetry is a Smart Plus/Minus system designed specifically for leagues where advanced data is unavailable.
It asks one fundamental question: Did this player make the team better, given the difficulty of the opposition?
When your team scores against a strong opponent, ratings rise more.
When your team concedes against weak opposition, ratings drop harder.
When performance is sustained over meaningful minutes, reliability increases.
The result is the Playermetry Percentile: a clear, objective ranking of real on-pitch impact within a league.
Our Mission
Playermetry isn’t built to replace scouts. It’s built to focus them.
To reduce noise. To reduce wasted time. To reduce expensive mistakes.
Our mission is simple: Level the scouting playing field. Give ambitious clubs (not just wealthy ones) access to structured, objective performance insight across hundreds of overlooked leagues.
Because talent is everywhere. Data just needs to find it.
If you believe scouting should be smarter in the leagues where advanced metrics are unavailable, welcome to Playermetry.