HSH·Intelligence
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T20 · live · per-ball · live

Live chase win-probability.

The real-time probability that the chasing team wins a T20 run chase, updated every ball. A gradient-boosted model trained on 475,000 ball-states from 4,406 real chases — AUC 0.88, beating the standard required-run-rate heuristic by 8.6 points. The in-play signal a betting bot or live dashboard needs, without building and calibrating its own win model.

$0.08 / call
deterministic price · pay per call
toolhsh-cricket-chase-winprob
How to buy

Two ways in — pick yours.

For people & teams
  1. Buy credits with a card — no wallet, no crypto.
  2. Get an API key emailed to you instantly.
  3. Call this product with your key — credits debit per call.
  4. Check your balance anytime via Check balance.
Buy credits with card →
For AI agents
  1. Point your agent at the x402 endpoint, or describe the need in plain language.
  2. Pay per call in USDC (Base or Solana) — no signup.
  3. Receive the signal inline, settled on-chain.
View agent catalog →
What you get · 3 layers

The signal, in full.

Pass the match state; receive a complete, model-backed read.

1

Calibrated win probability

A true, calibrated probability the chasing side wins from the exact match state — trained with log-loss, validated on Brier score. Beats the run-rate heuristic by 8.6 accuracy points.

chasing_team_win_probdefending_team_win_prob
2

Full situation read

Runs needed, balls remaining, current and required run rates, and wickets in hand — the complete state returned alongside the probability.

runs_neededballs_remainingrequired_rr
3

Phase-aware confidence

Appropriately uncertain in the powerplay and confident by the death overs — accuracy climbs from 73% to 88% as the chase resolves.

current_rrwickets_in_hand
Where it comes from

Learned from 475,000 live ball-states.

Trained on 4,683 real T20 matches from Cricsheet — free, legal, ball-by-ball — then validated on unseen matches. No fragile live-feed dependency; the intelligence is in the model.

475,000 ball-states
Every ball of 4,406 real completed chases, labelled with the eventual result.
trained
Gradient-boosted model
XGBoost over match-state features — not a run-rate rule of thumb.
proprietary methodology
Calibrated, not just ranked
Trained with log-loss and validated on Brier score, so a stated 70% genuinely means ~70%.
calibrated
Out-of-sample AUC 0.88
Measured on matches held out of training.
out-of-sample
Sample output

What comes back.

{
  "chasing_team_win_prob": 0.489,
  "defending_team_win_prob": 0.511,
  "situation": {
    "runs_needed": 60, "balls_remaining": 30,
    "current_rr": 6.67, "required_rr": 12.0, "wickets_in_hand": 8
  }
}
Who calls it

Use cases.

For autonomous agents
Betting bot
In-play pricing
Price a live chase market off a calibrated win probability instead of a crude run-rate rule.
Trading agent
Catch mispricings
Compare the model probability to the market line every ball and act on the gap.
Dashboard bot
Auto-update odds
Refresh a win-probability widget per ball with no in-house model.
For people & teams
Betting syndicate
Sharper in-play
Run a validated win model over live chases without building 475K rows of training data first.
Broadcaster
On-air win %
Show a credible live win-probability graphic sourced from a per-call API.
Analyst
Study close finishes
Pull win-prob at any state to quantify how matches were won and lost.
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.
# call the chase-winprob tool
curl -H "X-Payment: <x402-usdc-base-payload>" \
"https://dod.hshintelligence.com/mcp" \
-d '{"tool":"hsh-cricket-chase-winprob","input":{...}}'
Questions

FAQ.

How accurate is it?
AUC 0.88 on unseen matches, 79.7% ball-level accuracy — and it beats the naive required-run-rate heuristic by 8.6 points. Accuracy rises through the innings: 73% in the powerplay to 88% in the death overs.
What inputs does it need?
Balls bowled, wickets lost, runs scored, and the target. It computes run rates and the full situation internally.
Is the probability calibrated?
Yes — trained with log-loss and validated on Brier score, so a stated 70% genuinely means roughly 70%, not just a ranking.
Does it work for any T20?
It's trained on IPL and international T20. Any standard 20-over chase fits the model.
More in this category

Sports & wagering.