SportSync doesn't sort you into a bucket. It places you — and every sport — as points in one behavioral space, and reads the distance between them.
The core idea
Most "what sport should I do" tools map a personality type to a hand-written list of sports. SportSync works the other way around. You are encoded as a vector of behavioral scores. Every sport is encoded as a vector using the same scores — how much adrenaline it demands, how solo or social it is, how much it rewards routine versus variety, and so on.
A match is then just distance: which sport's point sits closest to yours. Nothing is looked up in a table. This is the engine running behind every result on the site.
The dimensions
Your answers resolve into scores along these axes. Each sport carries a value on the same axes, so the two are directly comparable.
Input
A short behavioral quiz (15–20 questions, no account) is scored into the axis values above — not by counting "right" answers, but by weighting each response's pull on each axis. That produces a first read, and one of four athletic personality types.
If you connect a wearable, two weeks of real movement data — how you actually train, recover and move — sharpens the same vector. Self-reported answers are a starting point; behavior is the correction. Quiz-only lands around 70% match confidence; with wearable data it moves past 90%.
Output, made real
A recommendation you can't act on is trivia. Once the sport is named, SportSync connects it to real places to play — vetted venues and community groups, with schedules, contacts and locations.
590+ venues and 200+ community groups across 20+ Saudi cities, covering 86 sports. Expanding.
On cost and honesty
The vector, the scoring and the matching are structured computation — not a chatbot. The language model is used where judgment genuinely helps: running the coach's discovery conversation, and writing the reasoning behind a specific pick. It is not the compute engine for every interaction, which is what keeps the system fast and cheap to run as it scales.
One consequence worth stating plainly: SportSync names sports from the model's broad knowledge of what exists, applied through the axis method — it is not reading from a fixed catalogue of a few thousand rows. The method generalizes; the list doesn't have to be finite.
The quiz is free and takes a couple of minutes. Or, if you're building something that could use this layer, start here.