Play-by-play kabaddi data for state leagues, their streams and their scouts
TL;DR Tacklemark records every raid, tackle and bonus point at kabaddi matches below the Pro Kabaddi League. The data feeds live stream graphics, commentator notes and player reports. State leagues and tournament organisers pay per match, and teams pay for scouting access. It works if leagues value stats enough to fund them.
Kabaddi has a huge audience, and one study cites 230 million viewers for the Pro Kabaddi League. The same study notes that kabaddi statistics sit scattered across many sources, which is why its authors had to build a tool just to gather them[1]. Below the top league the gap is worse. A team behind a kabaddi fan platform wrote that commentators have little to say about players, fans get little player content, and federations lack a way to pull tournament data together[2]. A good raider in a district final leaves no record a scout can search.
The seed pitched augmented-reality overlays that show live stats to fans in the stadium, and I'm not convinced. In-venue AR needs precise phone tracking, strong venue Wi-Fi and fans holding phones up, at grounds that often lack all three. The scarce part is the data, not the display.
So Tacklemark starts with the data. Two trained taggers sit courtside with a tablet app built for kabaddi. One logs each raid's outcome, touch points and bonus, while the other logs the defenders involved and the tackle type. Video from the stream is used to check and fix entries after the match. Over time computer-vision models trained on this tagged video can do more of the work.
The data goes three ways - live graphics into the organiser's stream, a one-page stats sheet for commentators, and a searchable player record for teams and scouts. AR can come later, once the data exists.
Fans are users and they pay nothing. The first payer is the league or tournament organiser, who wants a better stream to sell to sponsors. Pricing would be about ₹8,000–20,000 per match day for tagging and graphics (our estimate). A second payer is the team or academy that wants scouting data, at around ₹3,000–10,000 a month (our estimate). Pro league franchises are a later, larger buyer.
Streaming of local sport has become cheap. One grassroots streaming platform streams kabaddi, football and other grassroots matches and offers organisers scoring graphics and replays[3]. The leading cricket-scoring app added streaming with a score ticker to its cricket app in 2019[4]. Once a match is streamed, deeper data has somewhere to go. Investors also back sports data, and one racket-sports analytics startup raised ₹28 Cr for AI analytics in racket sports[5].
There is no public figure for spending on kabaddi data in India. The audience signal is the 230 million viewers cited for the top professional kabaddi league[1]. The grassroots streamer says its platform reaches a digital audience of over 25 million[3]. Both describe reach, not spending on data.
Grassroots sports streamers cover kabaddi with score graphics and builds player profiles from streamed matches[3]. The leading scoring app does this well for cricket, with over 5 million players and 20 million matches recorded[4], but not for kabaddi. One analytics startup does AI analytics for table tennis and badminton[5]. The gap is deep play-by-play data for kabaddi below the top league. Partnering with a streamer may beat competing with one.
| Difficulty | Moderate (47/100) |
| Starting capital | ₹60–110 L |
| Time to launch | 6–9 months |
The tagging app is not hard to build. The hard parts are having trained taggers at grounds across a state on match days, keeping the data accurate at kabaddi's speed, and agreeing with organisers who owns the data. Kabaddi moves fast, and a missed touch point changes a score (Ask any raider).
No sector licence is needed to collect match statistics. The permission that counts is a written agreement with the organiser.
Building this outside India? The categories above usually have a local equivalent, so check with your own regulator.
Don't trust AI to call points in real time, at least not yet. Kabaddi is fast, a missed touch point changes the score, and leagues will drop you after one wrong result on air.
Want to work out the AI layer for Tacklemark? Talk to Yash →
I think this suits a founder from the kabaddi world with contacts in two or three state associations and patience for field operations. It is a poor fit for someone who wants to build AR first. Prove first that one league will pay for a full season of tagged data.
Plan for roughly ₹60–110 L, mostly taggers at grounds across a state, the tablet app and graphics integration with streams.
No licence. You need a written data-rights deal with the organiser, video reuse terms and DPDP compliance, with parental consent for junior players.
Yes, with whatever local sport lacks data below the top league. Data rights and consent rules for minors differ, so check them before you sign a league.
The free Tacklemark validation kit has the line-by-line capital breakdown, the effort scoring, the data-rights and consent checklist, a 14-day validation sprint with pass/fail targets, a 90-day launch plan, 10 interview questions for leagues and teams, and 5 assumptions to test. Download the kit →
Thinking about building Tacklemark or something close to it? The make-or-break work is signing the first league and running accurate tagging at its grounds every match day. If you need a hand, you know where to find me. Talk to Yash →
For illustration only. Names are fictional and ideas hypothetical; sourced facts are real but may be out of date. Nothing here is legal, financial or professional advice, and Yash Khatri is not personally liable for any use of it. Read the full disclaimer.