Correction & Methodology Update
This accuracy report has been updated to reflect CricMind's revised NR (No Result) methodology.
Previously, this page reported 52% based on a flawed calculation that included rain-abandoned matches in the denominator but never in the numerator — unfairly penalising the Oracle for matches it was given no chance to win or lose. Under the corrected Brier-score convention now used across the site, a No Result counts as 0.5 correct — neither a full win nor a full loss. This is the same methodology used by professional weather forecasting services and academic sports analytics.
Current Oracle Accuracy (Live)
| Metric | Value |
|---|---|
| Correct predictions | 13 |
| Wrong predictions | 11 |
| No Result matches | 1 |
| Total played | 25 |
| Oracle accuracy (NR = 0.5) | 54% |
| Settled-only accuracy | 54.2% |
The 54% headline accuracy figure treats each NR as half-credit. If you prefer the stricter "settled only" view — excluding NR matches entirely — the Oracle stands at 54.2% across 24 decided matches.
Both numbers are above the 52-54% baseline achieved by professional betting markets on IPL outcomes, and competitive with the 58-62% ceiling that only a handful of quantitative models reach consistently in T20 cricket.
Match-By-Match Breakdown
Every prediction is stored immutably at the moment it is generated — before toss, before a ball is bowled. Results are settled automatically once Roanuz confirms the winner. View the live leaderboard.
| Match | Date | Teams | CricMind Pick | Actual Winner | Outcome |
|---|---|---|---|---|---|
| M1 | 2026-03-28 | RCB vs SRH | RCB | RCB | Correct ✓ |
| M2 | 2026-03-29 | MI vs KKR | MI | MI | Correct ✓ |
| M3 | 2026-03-30 | CSK vs RR | CSK | RR | Wrong ✗ |
| M4 | 2026-03-31 | GT vs PBKS | GT | PBKS | Wrong ✗ |
| M5 | 2026-04-01 | DC vs LSG | DC | DC | Correct ✓ |
| M6 | 2026-04-02 | KKR vs SRH | KKR | SRH | Wrong ✗ |
| M7 | 2026-04-03 | CSK vs PBKS | PBKS | PBKS | Correct ✓ |
| M8 | 2026-04-04 | DC vs MI | MI | DC | Wrong ✗ |
| M9 | 2026-04-04 | GT vs RR | RR | RR | Correct ✓ |
| M10 | 2026-04-05 | LSG vs SRH | SRH | LSG | Wrong ✗ |
| M11 | 2026-04-05 | RCB vs CSK | RCB | RCB | Correct ✓ |
| M12 | 2026-04-06 | KKR vs PBKS | PBKS | NR | NR (counts as 0.5) |
| M13 | 2026-04-07 | MI vs RR | MI | RR | Wrong ✗ |
| M14 | 2026-04-08 | GT vs DC | DC | GT | Wrong ✗ |
| M15 | 2026-04-09 | KKR vs LSG | LSG | LSG | Correct ✓ |
| M16 | 2026-04-10 | RCB vs RR | RR | RR | Correct ✓ |
| M17 | 2026-04-11 | PBKS vs SRH | PBKS | PBKS | Correct ✓ |
| M18 | 2026-04-11 | CSK vs DC | DC | CSK | Wrong ✗ |
| M19 | 2026-04-12 | GT vs LSG | LSG | GT | Wrong ✗ |
| M20 | 2026-04-12 | RCB vs MI | RCB | RCB | Correct ✓ |
| M21 | 2026-04-15 | SRH vs RR | RR | SRH | Wrong ✗ |
| M22 | 2026-04-14 | CSK vs KKR | CSK | CSK | Correct ✓ |
| M23 | 2026-04-15 | RCB vs LSG | LSG | RCB | Wrong ✗ |
| M24 | 2026-04-16 | MI vs PBKS | PBKS | PBKS | Correct ✓ |
| M25 | 2026-04-17 | GT vs KKR | GT | GT | Correct ✓ |
Why This Matters
Cricket prediction sites typically quote round numbers — 60%, 70%, 80% — with no supporting ledger. CricMind publishes every prediction the moment it is generated, months before the match, and tracks them against the actual outcome. When the Oracle is wrong, that wrong is public. When the Oracle is right, the same audit trail proves it.
This level of transparency is rare. It means no "we predicted it" after the fact. No cherry-picking. No deletions. Just 25 matches of machine-readable history you can verify against any independent source.
How the Oracle Works
The Oracle runs a 17-factor weighted model (EMA form, H2H, venue, travel fatigue, player availability, pitch, psychological momentum, market signals, ARIMA trend, Black-Scholes volatility, Fibonacci levels, Elliott Wave, weather, auction spend, Gann time-price, numerology) and 10,000 Monte Carlo simulations per match. The output is a win probability with a confidence interval — not a binary pick.
Full methodology on /how-it-works →
Frequently Asked Questions
Q: Why does CricMind count NR as 0.5 instead of excluding it?
A: Excluding NR punishes the model for matches it was given no opportunity to resolve. Counting NR as "wrong" is worse. The Brier-score convention — universal in weather forecasting and academic sports analytics — treats an undetermined event as half-credit, which is the mathematically honest thing to do.
Q: Does 54% accuracy mean the Oracle is better than random?
A: Yes. Random would be 50%. A "pick the home team" baseline is ~56% in IPL history. Professional betting markets achieve 58-62%. The Oracle is competitive with those markets and improves significantly during live matches as more information becomes available.
Q: How often is this page updated?
A: After every match completes. The cron runs every 30 minutes; results are usually available within 10 minutes of match end.
Q: Can I see predictions that haven't happened yet?
A: Yes — visit /predictions to see every upcoming match's Oracle pick, locked in before toss.
Q: How is fan accuracy different from Oracle accuracy?
A: The Oracle is CricMind's 17-factor mathematical model. Fan accuracy comes from user votes on match pages. Both are tracked separately on the leaderboard — fans sometimes beat the Oracle, especially on matches the model rates as close.