What will sports data actually cost at your scale?
Drag the sliders to your real numbers. See the Big Balls Sports Data plan you'd need, what the same usage costs on a raw-data sports API, and what that raw-data price leaves you to build yourself.
1,000 req/day free (2,000 with GitHub). No credit card.
10,000 requests/day on Big Balls Sports Data. A full matchup page is 1 call here vs 8 raw calls per sport on BallDontLie.
Big Balls Sports Data
$49/mo
Trio plan · All sports, one subscription
BallDontLie
$119.97/mo
3 × GOAT
Save $70.97/mo($851.64/yr)
AND skip building the assembly layer.
- Pre-assembled matchup responses (you call and join ~8 endpoints yourself)
- Elo predictions and win probabilities
- xG shot maps
- Player headshots
- Confirmed lineups with formations
- Cross-sport unified schema (each sport is a separate integration AND subscription)
Request volume
1 Big Balls call = 8 raw BallDontLie calls to assemble the same matchup page — per sport. At your scale that's 10,000 vs 240,000 requests/day.
Raw BallDontLie pricing covers the data subscription only. The assembly layer, intelligence features, and cross-sport unification are engineering time you build and maintain.
BallDontLie price = raw data subscription only. Assembly layer, intelligence features, and cross-sport unification are not included at any tier. Pricing verified 2026-05-28. Priced per sport, rate-limited per minute. Each sport is a separate subscription.
Why one call beats eight
The subscription price is only half the cost. Here's the other half.
One call, one page
Our intelligence endpoints return the whole matchup. Raw-data APIs make you fire ~8 calls and stitch the JSON yourself.
All sports, one key
Raw-data APIs price and gate per sport. One integration here covers every sport you add.
The data others can't sell you
Elo win probabilities, xG shot maps, confirmed lineups, and player headshots aren't on a raw-data feed at any tier.