xPitch turns the GPS recording already on your smartwatch into football-specific match analysis. No dedicated tracker or fancy sensor needed. Upload FIT, GPX, or TCX files for heatmaps, movement trails, zones, sprints, heart-rate context, and estimated roles. Map a session to a real pitch, split play from rest, save matches with notes/photos in your account, share them, and export Story-ready graphics.
I like to play football, but after a match I could only see my GPS recording as another run in Strava. I could not see where I played, how much of the pitch I covered, when I sprinted, or what my movement said about my role.
So I made xPitch. It only needs a smartwatch GPS recording, no fancy sensor or dedicated tracker. Upload a FIT, GPX, or TCX file and it turns the recording into football analysis: heatmaps, movement trails, zone occupancy, speed and sprint data, heart-rate context, workload, fatigue, and an estimated playing role.
You can map a recording to a real pitch, split play from rest, save match notes/photos, and export a Story graphic.
I built xPitch primarily with GPT-5.6 through Codex, with the workflow shaped around my own grassroots football use case.
I’d value feedback from players, coaches, and anyone who has tried getting useful match context from smartwatch GPS data.
as someone who plays weekend football, the thing I'm skeptical of is sprint detection off a wrist GPS during a match with constant sharp direction changes, not a straight run. most watches sample at 1hz and smooth the track, which is fine for a road run but can undercount short sharp sprints or misplace where a turn actually happened on the pitch. have you validated the sprint counts and heatmap positions against actual match footage, or mainly against the raw GPS trace itself
About xPitch on Product Hunt
“Strava for casual Footballer”
xPitch launched on Product Hunt on July 23rd, 2026 and earned 70 upvotes and 5 comments, placing #42 on the daily leaderboard. xPitch turns the GPS recording already on your smartwatch into football-specific match analysis. No dedicated tracker or fancy sensor needed. Upload FIT, GPX, or TCX files for heatmaps, movement trails, zones, sprints, heart-rate context, and estimated roles. Map a session to a real pitch, split play from rest, save matches with notes/photos in your account, share them, and export Story-ready graphics.
xPitch was featured in Sports (11.3k followers), Football (3.4k followers), GitHub (41.3k followers), Data Visualization (3.6k followers) and OpenAI Day (9 followers) on Product Hunt. Together, these topics include over 33.3k products, making this a competitive space to launch in.
Who hunted xPitch?
xPitch was hunted by Ismail Sunni. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
Want to see how xPitch stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
Ismail Sunni