Cricket has always generated mountains of data at the professional level, ball-tracking cameras, Hawk-Eye systems, biomechanics labs. What's been harder to access is that same level of insight for club cricketers, academies, and everyday players who don't have a broadcast rig following their every delivery. That's the gap Fulltrack AI has built itself around.
What Fulltrack AI Actually Is
Fulltrack AI is a mobile app developed by Maiden AI Inc, a Seattle-based company founded in 2021. At its core, the pitch is simple: prop a phone up on a tripod, point it at the pitch or nets, and let computer vision and machine learning do the rest. No dedicated cameras, no manual tagging, no separate analyst poring over footage after the session.
From that single camera feed, the app generates a surprisingly deep set of outputs:
- 3D ball trajectory tracking, reconstructing the flight path of every delivery
- Pitch maps, showing where a bowler is landing the ball over a session or match
- Ball-by-ball video organization, automatically splitting a long recording into individual deliveries
- Bowling analytics, including speed, swing, and spin
- Batting analytics, covering wagon wheels, shot distribution, shot intent, footwork patterns, and shot outcomes
- Auto-tagging, identifying which player is batting or bowling in each delivery without manual input
All of this gets processed and stored in the cloud, which means a session recorded at nets can be reviewed later by a coach, teammate, or parent on a different device entirely. For a sport where feedback loops have traditionally depended on a coach's eye and memory, that's a meaningful shift, video and data become shareable and searchable rather than locked to whoever was standing behind the camera.
Who It's Built For
Fulltrack AI positions itself across a fairly wide spectrum of the sport: individual players working on their own game, clubs and schools running structured programs, and professional teams wanting a lightweight analytics layer without deploying full broadcast infrastructure. According to reviewer accounts on the App Store, the platform has found some traction at the elite end too, with mentions of use by high-profile players and at least one national federation, though claims like these are worth verifying independently rather than taking at face value, since they came from a single enthusiastic review rather than official confirmation.
The tiered pricing structure reflects this range in ambition. There's a free tier for casual use, a paid individual plan for regular players, and a "Coach+" tier aimed at people managing multiple players or a full squad.
How the Technology Works
The underlying promise is that a single phone camera, paired with modern computer vision models, can replace what used to require multiple fixed cameras and manual video-tagging labor. This mirrors a broader trend in sports tech: companies like Mustard (baseball pitching and golf swing analysis) and Athlete's AI (multi-sport video analytics for amateurs) are chasing a similar idea, using AI to democratize forms of performance analysis that were previously reserved for teams with real budgets.
For cricket specifically, this is a genuinely hard computer vision problem. A cricket ball travels fast, can swing or spin significantly, and needs to be tracked against a cluttered background that includes players, the pitch, and often variable lighting. The fact that Fulltrack AI can extract 3D trajectory data from a single 2D camera feed, rather than needing multiple synchronized cameras, is the more technically ambitious part of the product.
What Users Say
Fulltrack AI holds a 4.2–4.3 out of 5 rating on the App Store, based on a relatively modest sample of around 40 ratings. That's a respectable score, though the small sample size means it's worth reading the actual reviews rather than the star average alone.
The positive reviews consistently single out a few things: the accuracy of the tracking and analysis, the usefulness of auto-tagging and filtering for quickly finding specific deliveries or shots, and a genuine feeling among users that the app meaningfully improves self-coaching and video review compared to just filming on a phone and scrubbing through it manually.
The recurring criticism is pricing, and it comes up often enough to be a real pattern rather than a one-off complaint. The free tier caps users at 75 deliveries a month. The paid individual plan, around $10 a month, raises that to 300 deliveries, which one reviewer noted can be used up in under an hour at a single net session. Unlocking unlimited deliveries and features like full pitch maps requires stepping up to the $149 Coach+ tier, a steep jump for anyone who isn't training or coaching at real volume. One reviewer also described an unhelpful experience trying to negotiate a better rate with customer support, though again, that's a single account rather than a broad pattern.
Where It Fits in a Crowded Market
Fulltrack AI isn't operating in a vacuum. Cricket-specific competitors include Homeground (India-based, combining a coaching app with AI-driven streaming), Ludimos (an AI cricket coaching and analytics platform), and SportsTrace (also Seattle-based, focused on video-based motion capture across sports). More broadly, the space of AI-powered single-camera sports analytics includes companies like Mustard and Sportcor, all chasing the same basic value proposition across different sports: turn a phone camera into an analyst.
What differentiates Fulltrack AI within that field is its cricket-specific depth, pitch maps, swing and spin data, and wagon wheels are all built around the particular language and needs of the sport, rather than being a generic motion-tracking tool adapted for cricket after the fact.
The Honest Verdict
Fulltrack AI appears to deliver on its core technical promise: real, useful cricket analytics from nothing more than a phone and a tripod, with automatic processing that removes the tedious parts of video review. The update history shows steady, active development, new batting filters, expanded shot-outcome data, and interface improvements have shipped regularly, suggesting a team that's continuing to invest in the product rather than letting it stagnate.
The tension is between casual and serious use. For someone who wants to record the occasional net session and get a bit of feedback, the free and entry-level paid tiers feel restrictive fast. For a serious individual player, a coach managing a squad, or a club running structured training, the deeper tiers likely make more sense, but they come at a real cost that puts the product more in "investment" territory than "casual app" territory.
In a sport where data-driven feedback used to be the exclusive privilege of international teams with broadcast-level resources, that's still a notable shift, even if the pricing model means it isn't yet the free-for-all democratization it might first appear to be.