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IPL·T20·fantasy·per-call
Fantasy picks & captain.
Ranked player picks and the optimal captain for a T20 match, in a single call. An ensemble model, trained on 129,000 player-innings across 4,683 matches, that blends expected points, probability of a top-6 finish, and a ceiling model to name the captain. The signal a fantasy app or contest bot needs to build a lineup, without running its own player-projection pipeline.
Buy credits
x402 protocol
How to buy
Two ways in, pick yours.
For AI agents
- 01Point your agent at the x402 endpoint.
- 02Pay per call in USDC (Base or Solana), no signup.
- 03Receive structured data inline, settled on-chain.
x402 protocol
What you get · 3 layers
The signal, in full.
Pass the match state; receive a complete, model-backed read.
- 01
Ranked player picks
Every player in the squad scored and ranked by predicted fantasy value, a blend of expected points, top-6 probability, and ceiling. Separates safe floor picks from explosive ceiling picks.
pickspick_scorerank
- 02
Captain pick
The single highest-ceiling player, chosen by a 90th-percentile model, because captaincy doubles points and rewards upside, not average. Captain-hit rate 35.6%, more than double random.
captain_pickceiling_pts
- 03
Per-player probabilities
Each player carries a top-6 probability, an expected-points figure, and a ceiling, so a lineup builder can balance a safe core with high-variance differentials.
p_top6expected_pts
Where it comes from
Built on 129,000 player-innings.
Fit on a large archive of completed professional matches, then validated on unseen games. The intelligence lives in the model.
129,000 player-innings
Every batting and bowling innings from 4,683 T20 matches, with full fantasy scoring reconstructed ball-by-ball.
trained
Ensemble architecture
Three models, expected points, P(top-6) classifier, and a ceiling quantile model, blended, not a single naive mean.
proprietary methodology
Batting-position aware
Order in the innings is extracted from ball data and fed as a feature, the single biggest driver of fantasy output.
feature-engineered
Validated out-of-sample
Captain-hit and top-6 rates measured on matches held out of training, not fitted.
out-of-sample
Sample output
What comes back.
hsh-cricket-fantasy-picks
{
"captain_pick": "V Kohli",
"picks": [
{
"rank": 1,
"player": "JJ Bumrah",
"p_top6": 0.565,
"expected_pts": 33.6,
"ceiling_pts": 75.4
},
{
"rank": 2,
"player": "V Kohli",
"p_top6": 0.372,
"expected_pts": 33.8,
"ceiling_pts": 87.4
}
]
}Who calls it
Use cases.
For autonomous agents
Fantasy bot
Build a lineup
Score all 22 players and auto-assemble a contest lineup, floor picks for the core, ceiling picks for differentials.
Contest optimizer
Pick the captain
The ceiling model names the captain that maximizes doubled points, not just the highest average.
Tipster agent
Auto-generate tips
Turn ranked picks into published fantasy tips every match, with no human projection work.
For people & teams
Fantasy app
Power a picks feature
Offer users AI captain and pick suggestions without building a projection model in-house.
Creator / tipster
Back your calls
Ground published tips in a validated model instead of gut feel.
Contest player
Sharpen your edge
See which players carry ceiling vs floor before locking a lineup.
How to call it
Discover, pay, receive.
- 01
Discover
Find the tool
Via MCP at dod.hshintelligence.com/mcp or the x402 catalog.
- 02
Pay
Pay per call
Send the x402 payment in USDC on Base. Fixed deterministic price.
- 03
Receive
Get the signal
The signal returns inline, ready for your model, lineup, or strategy.
curl
# call the fantasy-picks tool
curl -H "X-Payment: <x402-usdc-base-payload>" \
"https://dod.hshintelligence.com/mcp" \
-d '{"tool":"hsh-cricket-fantasy-picks","input":{...}}'