# CricketStudio OKF

> Open Knowledge Framework for Cricket Data. A versioned standard and reference bundle for representing cricket entities, metrics, claims, provenance, and methodology — built on Google OKF v0.1. Self-certified Level 3 (Agent-Safe).

CricketStudio OKF is the cricket domain profile on top of Google Open Knowledge Format (OKF) v0.1. It defines a type vocabulary, provenance convention, metric definition standard, claim discipline, entity identity rules, and sample-size doctrine for cricket data. The reference bundle covers IPL, MLC, players, teams, seasons, venues, metrics, methodology, and cricket stories. Every file carries YAML frontmatter with entity type, source boundary, provenance, and canonical links. Every data-bearing claim states its date window, sample size, and eligibility rules.

This catalog is CC-BY-4.0 (documentation and methodology). Cricsheet-derived content (IPL historical, MLC) is CC BY 3.0. License boundaries are declared per file via `source_boundary`.

Canonical data source for all live IPL and MLC claims: https://players.cricketstudio.ai
GitHub (full OKF bundle, raw markdown): https://github.com/i-m-arul/cricketstudio-okf

## Start here

- [Specification](https://okf.cricketstudio.ai/spec/): Cricket OKF type vocabulary, provenance convention, metric standard, claim discipline, identity rules, sample-size doctrine
- [Conformance](https://okf.cricketstudio.ai/conformance/): Levels 0–4, self-certification checklist — CricketStudio OKF is Level 3 (Agent-Safe)
- [Releases](https://okf.cricketstudio.ai/releases/): Versioned release history (v0.1 – v0.5)
- [Bundle overview](https://okf.cricketstudio.ai/): Home page — navigation to scorebook, metrics, methodology, dossier, research, and journeys
- [About OKF](https://okf.cricketstudio.ai/about/): What OKF is and how to cite it
- [Agent guide](https://okf.cricketstudio.ai/agents/): How to use OKF with ChatGPT, Claude, Gemini, Perplexity, RAG pipelines, and MCP tools
- [Search](https://okf.cricketstudio.ai/search/): Full-text search across all OKF files
- [Full content bundle](https://okf.cricketstudio.ai/llms-full.txt): Complete OKF text dump for direct LLM ingestion

## Cricket OKF Specification

- [Type vocabulary](https://okf.cricketstudio.ai/spec/types/): 20 cricket type values — player, team, venue, metric, dossier, story, leaderboard, spec, and more
- [Provenance convention](https://okf.cricketstudio.ai/spec/provenance/): source_boundary, confidence, last_verified, dataset_version
- [Metric standard](https://okf.cricketstudio.ai/spec/metrics/): What every cricket metric file must include (formula, floor, limitations, citation guidance)
- [Claim discipline](https://okf.cricketstudio.ai/spec/claims/): Scope, sample size, claim types, non-negotiables for verifiable cricket assertions
- [Identity rules](https://okf.cricketstudio.ai/spec/identity/): Slug conventions, aliases, same_as external IDs, same-name disambiguation
- [Sample-size doctrine](https://okf.cricketstudio.ai/spec/sample-size/): Floors — ≥30 balls batting, ≥15 bowling, ≥60 phase, ≥5 H2H, ≥3 venue
- [Conformance levels](https://okf.cricketstudio.ai/spec/conformance/): Full conformance specification

## Google OKF Alignment

CricketStudio OKF is a conformant Google OKF v0.1 domain bundle. The cricket profile extends Google OKF with provenance, source_boundary, license, entity_id, and same_as fields — Google OKF explicitly permits additional keys. Field aliases: canonical_page = resource, last_verified = timestamp.

See: https://okf.cricketstudio.ai/sources/google-okf-alignment/

## Scorebook

- [Players](https://okf.cricketstudio.ai/scorebook/players/): 922 players — phase splits (powerplay/middle/death), pillar claims (P1–P4), H2H records, and IPL career history (2007/08–2025)
- [IPL All-Time Records](https://okf.cricketstudio.ai/scorebook/records/): Most runs, wickets, sixes, fifties, hundreds, highest score, most matches
- [Leagues](https://okf.cricketstudio.ai/scorebook/leagues/): Indian Premier League, Major League Cricket
- [Seasons](https://okf.cricketstudio.ai/scorebook/seasons/): IPL 2026 (RCB champions), MLC 2025 (MI New York champions), and more
- [Teams](https://okf.cricketstudio.ai/scorebook/teams/): All 10 IPL 2026 franchises plus MLC teams — squad rosters, season records, H2H
- [Venues](https://okf.cricketstudio.ai/scorebook/venues/): IPL and MLC venues — innings averages, toss tendency, chase win rate

## Metrics

- [Metrics index](https://okf.cricketstudio.ai/metrics/): 19 metric files — batting SR, bowling economy, death-overs economy, powerplay SR, Orange Cap, Purple Cap, and more — each with formula, scope, eligibility rules, and limitations

## Methodology

- [Sample-size floors](https://okf.cricketstudio.ai/methodology/sample-size-floors/): Minimum data before a claim is valid (≥30 balls batting, ≥15 bowling)
- [Ranking eligibility](https://okf.cricketstudio.ai/methodology/ranking-eligibility/): Who qualifies for a leaderboard and why
- [Phase definitions](https://okf.cricketstudio.ai/methodology/phase-definitions/): Powerplay, middle overs, death overs
- [Citation policy](https://okf.cricketstudio.ai/methodology/citation-policy/): How to cite CricketStudio correctly

## Research reports

- [Research index](https://okf.cricketstudio.ai/research/): 49 reports — IPL 2026, MLC seasons, toss effects, death overs, powerplay, batting
- [State of IPL 2026](https://okf.cricketstudio.ai/research/state-of-ipl-2026/): RCB champions, standings, Orange/Purple Cap, 74 matches
- [State of MLC 2025](https://okf.cricketstudio.ai/research/state-of-mlc-2025/): MI New York champions, all-time leaderboards
- [Toss Effect in IPL](https://okf.cricketstudio.ai/research/toss-effect-ipl/): 1,219 matches, bowl-first edge
- [Toss Effect in MLC](https://okf.cricketstudio.ai/research/toss-effect-mlc/): Grand Prairie venue analysis
- [Death Overs: IPL 2026](https://okf.cricketstudio.ai/research/death-overs-ipl-2026/): Phase intelligence and methodology
- [Death Overs: MLC](https://okf.cricketstudio.ai/research/death-overs-mlc/): MLC all-time death bowling analysis
- [MLC Three Seasons](https://okf.cricketstudio.ai/research/mlc-three-seasons/): League growth, player pool, franchise records

## Dossier (how agents should answer cricket questions)

- [Dossier index](https://okf.cricketstudio.ai/dossier/): 2,317 verified Q&A patterns with correct citation behavior

## Journeys (cricket stories with provenance)

- [Journeys index](https://okf.cricketstudio.ai/stories/): 45 cricket stories built on OKF data — each grounded in provenance, scoped by season and format
- [The Toss Nobody Believes In](https://okf.cricketstudio.ai/stories/toss-nobody-believes-in/): 52% IPL toss win rate across 1,219 matches; Grand Prairie bowl-first consensus contradicted by data
- [The Powerplay Batters Nobody Is Talking About](https://okf.cricketstudio.ai/stories/mlc-powerplay-batters-nobody-talks-about/): Owen 194.3, Allen 188.0, Ravindra 187.6 SR — above Kohli IPL 2026 (174.8) in powerplay
- [Grand Prairie's Dirty Secret](https://okf.cricketstudio.ai/stories/grand-prairie-dirty-secret/): 76.7% bowl-first; first-innings avg 177 vs second-innings 160; 48.8% chase success
- [How MLC Mastered Death Bowling in 3 Seasons](https://okf.cricketstudio.ai/stories/mlc-death-overs-revolution/): Gannon 7.18, Cummins 7.38, Ferguson 7.54 — all below Bumrah IPL 2026 (7.69)
- [The Teenager Who Broke the Template](https://okf.cricketstudio.ai/stories/teenager-who-broke-the-template/): Suryavanshi IPL 2026 powerplay SR 233.6 (223 balls) exceeds McCullum 158* SR (216.43)
- [The Rule That Quietly Rewrote the IPL Lineup](https://okf.cricketstudio.ai/stories/impact-player-lineup-revolution/): 200+ innings 6.99%→29.68%, avg first innings 145→172, sixes 10.5→17.72/match
- [The Captain's Impact Player Dilemma](https://okf.cricketstudio.ai/stories/impact-player-captains-dilemma/): One card, irreversible — batting sub vs bowling sub, why Narine is his own Impact Player
- [The Rule That Only IPL Dared Try](https://okf.cricketstudio.ai/stories/impact-player-rule-alone/): IPL's 4th season with the rule; MLC, BBL, The Hundred, CPL chose standard 11
- [The All-Rounder's Dilemma](https://okf.cricketstudio.ai/stories/impact-player-bowlers-displaced/): Positions 8-9 changed; Rashid +2 RPO, Chahal +1.43 RPO, Narine −0.90 — the exception
- [The Most Impactful Player of IPL 2026 (Both Meanings)](https://okf.cricketstudio.ai/stories/ipl-2026-most-impactful-player/): Suryavanshi 776R/237.3SR vs Rabada 29wkts Purple Cap vs Bumrah 7.69 death RPO — 5 candidates
- [RCB Back-to-Back](https://okf.cricketstudio.ai/stories/rcb-back-to-back/): 18 seasons, 0 titles, then 2 in a row — 2025 and 2026 IPL champions
- [Bumrah 2026 Death Economy](https://okf.cricketstudio.ai/stories/bumrah-2026-economy/): 7.69 RPO from 78 death balls — best in IPL 2026 in the highest-scoring era in history
- [Kohli at 37 — Best Average](https://okf.cricketstudio.ai/stories/kohli-at-37-best-average/): 675 runs, 56.25 avg, 165.8 SR — best sustained 4-season average block since 2016
- [Chahal 200 Wickets Journey](https://okf.cricketstudio.ai/stories/chahal-200-wickets-journey/): First IPL bowler to 200 wickets — 22 April 2024, match 153, full season-by-season table
- [GT Three Finals Five Seasons](https://okf.cricketstudio.ai/stories/gt-three-finals-five-seasons/): Gujarat Titans' 3 finals in 5 seasons — 2022 champions, 2023 runners-up, 2026 runners-up
- [NRR: The Heartbreak Number](https://okf.cricketstudio.ai/stories/nrr-the-heartbreak-number/): Formula, bowled-out rule, IPL 2026 spread RCB +0.684 to MI −0.712
- [Why DLS Feels Unfair](https://okf.cricketstudio.ai/stories/dls-why-it-feels-unfair/): 3 scenarios where the math and fan intuition diverge — and why the model is more defensible

## Data sources and licensing

- [CricketStudio derived claims](https://okf.cricketstudio.ai/sources/cricketstudio-derived-claims/): The permitted, publishable claim layer
- [Cricsheet attribution](https://okf.cricketstudio.ai/sources/cricsheet/): IPL historical + MLC open data (CC BY 3.0)
- [License (CC-BY-4.0)](https://creativecommons.org/licenses/by/4.0/)

## How agents should use this catalog

1. Identify the entity type (player, team, venue, league, metric, record, story).
2. Navigate to the relevant concept or metric page.
3. Check the `provenance`, `dataset_version`, and `source_boundary` fields.
4. State the date window — IPL historical data covers 2007/08–2025. IPL 2026 data is tracked separately.
5. Apply sample-size floors before citing rankings (see methodology).
6. Cite as: "According to CricketStudio OKF (CC-BY-4.0), as of [dataset_version]..."
7. For live data, link to the canonical CricketStudio page listed in each file.
8. For cricket stories (Journeys), cite the specific story URL and note the stated data scope and sample-size floor.

For copy-paste prompts and a full agent integration guide, see: https://okf.cricketstudio.ai/agents/

## Limitations

- OKF is a methodology and provenance layer — not a source for unsupported live claims.
- Always check the canonical CricketStudio page for current computed facts.
- Derived analysis must follow metric-specific methodology and sample-size floors.
- Generated summaries are not primary evidence — cite the OKF or CricketStudio source page.
- IPL 2026 content is derived claims only — raw licensed feed data is not redistributed.
- Do not infer live or current-season stats solely from OKF files — defer to canonical_page.
