Research
We want to pair data from real competition with sports science to ask better questions — about fairness, performance, and tactics — and feed the answers back into iMatch.
Research areas
Four threads we intend to study, each grounded in the kind of data the platform sees.
Modeling draw bias, seeding accuracy, and scheduling equity — measuring whether the bracket itself advantages or disadvantages players.
Discuss this area Computer visionDetecting strokes, spin, speed, and footwork from ordinary match footage — turning a single camera into a quantified record of play.
See it in SVR PerformanceWhich drills move the needle? Linking session structure and volume to measurable rating gains, so practice time pays off.
Discuss this area TacticsMining rally patterns and serve–receive trees to map what wins points at each level — and how tactics shift under pressure.
Discuss this areaWe're open to collaborating with universities, federations, and independent researchers. If your question fits the data, bring it to the community.
Propose a studyHow we'll work
Real problems organizers, coaches, and players raise — not abstract ones.
Working only with data the platform's privacy policy allows, aggregated and de-identified.
Findings become features — fairer draws, smarter analysis, better training.
Bring your question to the community — that's where research conversations start.