SharpEyeWinter 2027

Frontier Intelligence for Tennis

Shot-by-shot statistics and analysis is inaccessible to the majority of tennis players. SharpEye is changing that. Our computer vision model captures a shot-by-shot record of the match and shows players exactly where their points are won and lost. This January, a small group of students will join the team building it, working with one another and directly with SharpEye's co-founders.

You can join as an intern or take on a research project. Tell us which you prefer below.

DatesJanuary 4 – 27, 2027
TimeAbout 100 hours
WhereRemote
PlacesUp to five

1 · Rank the roles

Give your first choice a 1, your second a 2, and so on. Rank as many as interest you and leave the rest as "Not for me".

Computer vision model work

From one phone camera, the model has to read the whole match: every shot and who hit it (the serve, forehand or backhand, topspin or slice, volleys, overheads, lobs and drop shots), where each ball bounced, when each point ended and who won it. You would build the examples it learns from, test it against real matches, find where it fails and measure each improvement. Projects range from telling shots apart, to recovering where the ball landed from its flight, to reading the players' calls and body language.

Good fit: computer science, data science, statistics, physics (trajectories, Kalman filtering), speech or language processing. Tennis experience helps but isn't required.

iOS app development and statistical player analysis

Players film, review and share their matches in the SharpEye iPhone app. You would build features in the app and the analysis behind them: which statistics actually tell a player something about their game (serve patterns, shot placement, what wins and loses points), how to show them clearly, and how to check they're right.

Good fit: iOS or Swift development, mobile design, statistics, data science, sports analytics.

Physical engineering of the SharpEye stick

Players film their matches on the SharpEye stick. It hooks onto the fence behind the court, holds the phone at the best angle for our software, and has built-in battery charging. We have a working prototype. You would own it from here: improvements to the fence hook, phone mount and battery; materials, cost, design for manufacturing and choosing a manufacturer; packaging, shipping and getting it to players and teams.

Good fit: mechanical or electrical engineering, product design, physical prototyping.

Business and economics: pricing the product

How should SharpEye be priced? Players, parents, coaches and college programmes each value match analytics differently. You would study what each group would pay, how pricing by match, by subscription or by shot compares with the alternatives, and what that means for how SharpEye is sold.

Good fit: economics, business, statistics.

2 · Internship or research project

3 · About you

4 · Résumé

PDF or Word, up to 8 MB.