EsportMarket treats competitive players like tradable assets. Live valuations, rating models, and scouting intelligence, presented in a stock-ticker, financial-market interface instead of another stats dashboard. I co-founded it and built the fullstack product and its design.
The brief
Esports has plenty of stat sites, but almost none of them make you feel the value of a player the way a finance app makes you feel a stock move. Scouts, orgs, and fans all want the same underlying thing, a fast read on who is rising and who is falling, but existing tools bury that signal in tables. We wanted a platform where a player's value is the headline, not a column you have to scroll to find.
What I built
The product is built on Next.js, TypeScript, and React on the frontend, with a data pipeline behind it turning raw match and performance data into live valuations and ratings. The interface borrows deliberately from financial markets: tickers, movement indicators, the visual grammar people already use to read a stock chart. That choice does real work, it lets someone unfamiliar with a specific player understand instantly whether they are trending up or down, without reading a paragraph of analysis first.
Underneath the ticker sits the harder problem, a rating model that has to stay consistent as new match data comes in, and scouting intelligence that turns that data into something a recruiter can act on rather than just admire. Getting the pipeline right mattered more than the UI, a valuation that jumps around for no reason breaks trust in the whole platform, so the modeling had to be stable before the front end got to look flashy.
It is an English language, data-heavy product from day one, built for an international esports audience rather than a local one, which shaped everything from the copy to the kind of scouting data we prioritized.
The result
EsportMarket is live at esportmarket.gg as a working platform, not a prototype: real valuations, real ratings, a real scouting layer, wrapped in an interface that makes esports data feel as immediate as a market ticker. Building both the product and the pipeline myself meant the design and the data model could evolve together instead of design waiting on data or the other way around, which is exactly what a platform like this needs to feel trustworthy.