Datasets:

VaidhyaMegha
/

cricket-kg

src int64 6 36.6k	tgt int64 28 36.6k	balls int64 1 582	fours int64 0 57	innings_num int64 0 7	runs int64 0 410	sixes int64 0 23	strike_rate float64 0 600	super_over float64 1 1 ⌀
25	28	19	1	0	16	1	84.21	null
22	28	86	7	0	51	0	59.3	null
24	28	32	1	0	10	0	31.25	null
26	28	12	2	0	11	0	91.67	null
20	28	23	0	0	11	0	47.83	null
17	28	4	0	0	0	0	0	null
23	28	101	11	0	84	1	83.17	null
21	28	74	5	0	37	0	50	null
19	28	5	0	0	0	0	0	null
18	28	22	2	0	12	0	54.55	null
27	28	4	1	0	4	0	100	null
6	28	100	16	1	97	1	97	null
12	28	53	2	1	23	1	43.4	null
7	28	148	8	1	63	0	42.57	null
14	28	25	3	1	18	0	72	null
10	28	60	4	1	27	0	45	null
16	28	2	0	1	0	0	0	null
13	28	5	0	1	0	0	0	null
8	28	17	0	1	4	0	23.53	null
9	28	4	0	1	0	0	0	null
11	28	8	0	1	0	0	0	null
15	28	5	0	1	4	0	80	null
18	28	316	17	2	127	1	40.19	null
24	28	143	10	2	73	2	51.05	null
25	28	34	2	2	41	3	120.59	null
22	28	18	2	2	8	0	44.44	null
17	28	55	2	2	12	0	21.82	null
21	28	64	6	2	32	0	50	null
19	28	7	0	2	1	0	14.29	null
23	28	100	5	2	64	2	64	null
20	28	225	20	2	141	1	62.67	null
16	28	22	1	3	8	0	36.36	null
12	28	153	6	3	60	0	39.22	null
14	28	32	3	3	13	0	40.63	null
9	28	91	5	3	34	0	37.36	null
13	28	24	2	3	13	0	54.17	null
8	28	182	11	3	97	3	53.3	null
6	28	33	6	3	35	0	106.06	null
10	28	12	0	3	1	0	8.33	null
7	28	45	1	3	15	0	33.33	null
15	28	71	5	3	29	0	40.85	null
11	28	52	4	3	26	0	50	null
9	34	80	5	0	48	0	60	null
16	34	7	0	0	2	0	28.57	null
32	34	22	2	0	10	0	45.45	null
12	34	25	0	0	3	0	12	null
13	34	6	1	0	4	0	66.67	null
8	34	25	0	0	4	0	16	null
31	34	12	0	0	3	0	25	null
15	34	7	2	0	8	0	114.29	null
6	34	4	0	0	1	0	25	null
30	34	8	0	0	1	0	12.5	null
10	34	1	0	0	0	0	0	null
22	34	204	8	1	74	0	36.27	null
33	34	9	0	1	3	0	33.33	null
23	34	143	17	1	104	0	72.73	null
26	34	11	1	1	5	0	45.45	null
17	34	49	2	1	23	0	46.94	null
24	34	28	6	1	32	0	114.29	null
21	34	25	1	1	7	0	28	null
18	34	61	0	1	17	0	27.87	null
19	34	67	5	1	47	0	70.15	null
25	34	5	0	1	1	0	20	null
20	34	4	0	1	1	0	25	null
12	34	16	0	2	6	0	37.5	null
8	34	121	9	2	64	0	52.89	null
9	34	82	5	2	31	0	37.8	null
10	34	17	0	2	2	0	11.76	null
13	34	13	0	2	0	0	0	null
30	34	4	0	2	0	0	0	null
15	34	14	1	2	6	0	42.86	null
6	34	78	4	2	45	0	57.69	null
31	34	11	0	2	1	0	9.09	null
32	34	2	0	2	0	0	0	null
16	34	4	1	2	4	0	100	null
17	42	99	4	0	40	0	40.4	null
22	42	34	0	0	8	0	23.53	null
24	42	9	1	0	4	0	44.44	null
18	42	17	1	0	5	0	29.41	null
20	42	11	1	0	5	0	45.45	null
21	42	164	17	0	118	0	71.95	null
23	42	33	3	0	24	0	72.73	null
33	42	50	0	0	17	0	34	null
19	42	11	0	0	5	0	45.45	null
41	42	23	2	0	18	0	78.26	null
26	42	6	0	0	1	0	16.67	null
15	42	26	1	1	11	0	42.31	null
16	42	8	1	1	13	0	162.5	null
39	42	6	1	1	4	0	66.67	null
6	42	25	0	1	11	0	44	null
36	42	46	2	1	10	0	21.74	null
38	42	12	0	1	0	0	0	null
13	42	91	5	1	53	1	58.24	null
8	42	308	12	1	145	0	47.08	null
40	42	17	0	1	6	0	35.29	null
37	42	78	6	1	54	0	69.23	null
9	42	113	8	1	59	1	52.21	null
24	42	34	2	2	17	0	50	null
22	42	31	3	2	21	0	67.74	null
21	42	26	2	2	12	0	46.15	null

End of preview. Expand in Data Studio

Cricket Knowledge Graph

36,619 nodes. 1,392,017 edges. 21,324 matches — Tests, ODIs, T20s, IPL, BBL and more, men's and women's, from December 2001 to March 2026.

Built with Samyama Graph. Loader and ETL: samyama-ai/cricket-kg.

Attribution — required

This dataset is CC-BY-4.0, which means attribution is a condition of use, not a courtesy. If you use it, credit the source:

Source data from Cricsheet.org, licensed CC-BY-4.0.

That requirement travels with the data — anything you redistribute, publish or build on top of must carry it too.


Data	CC-BY-4.0 — attribution required
Source	Cricsheet.org
Loader code	Apache-2.0, in the GitHub repo. This does not govern the data.

What this is

Every match Cricsheet has published, as a property graph rather than a pile of JSON.

Because it is a graph, questions needing several hops are direct: which bowler has dismissed a given batter most often across formats, which venues a partnership performs best at, how a player's strike rate moves across seasons and competitions.

Every node is connected — there are no isolated records in this graph.

Format	Matches	Gender	Matches
T20	13,069	men's	17,166
ODI	3,098	women's	4,158
MDM (multi-day)	2,085
ODM (one-day)	1,852
Test	900
IT20	320

Files

Nodes carry an id; edges reference those ids as src and tgt. Join on id.

`nodes/`

File	Rows	Columns
`match.csv`	21,324	`id, file_id, date, gender, match_type, season, win_by_runs, win_by_wickets, winner`
`player.csv`	12,933	`id, cricsheet_id, name`
`tournament.csv`	1,053	`id, name`
`venue.csv`	877	`id, city, name`
`team.csv`	383	`id, name`
`season.csv`	49	`id, year`

`edges/`

Several edges carry performance data as properties — that is where the detail lives.

File	Rows	Connects	Properties
`batted_in.csv`	401,165	Player → Match	`runs, balls, fours, sixes, strike_rate, innings_num, super_over`
`dismissed.csv`	308,216	Player → Player	`kind, over, match_file_id`
`bowled_in.csv`	279,426	Player → Match	`wickets, overs, maidens, runs_conceded, economy, innings_num`
`fielded_dismissal.csv`	215,869	Player → Player	`kind, over, match_file_id`
`competed_in.csv`	42,648	Team → Match	—
`played_for.csv`	24,011	Player → Team	—
`hosted_at.csv`	21,324	Match → Venue	—
`in_season.csv`	21,324	Match → Season	—
`won_toss.csv`	21,324	Team → Match	`decision`
`part_of.csv`	21,235	Match → Tournament	`group, match_number`
`won.csv`	19,679	Team → Match	`by_runs, by_wickets`
`player_of_match.csv`	15,796	Player → Match	—

DISMISSED is bowler → batter; FIELDED_DISMISSAL is fielder → batter. Both carry the kind of dismissal and the over it happened in.

Also included

cricket.sgsnap — the same graph as a Samyama snapshot. Loads into the engine in one step, without running the ETL.

Usage

As tables

from datasets import load_dataset

batting = load_dataset("VaidhyaMegha/cricket-kg", "edge_batted_in", revision="v1.0")
print(batting["train"].num_rows)          # 401165

As a graph

docker run --rm -p 8080:8080 -p 6379:6379 public.ecr.aws/f9f6l5u4/samyama-graph:1.1.0
curl -X POST localhost:8080/api/tenants -H 'Content-Type: application/json' \
     -d '{"id":"cricket","name":"Cricket KG"}'
curl -X POST localhost:8080/api/tenants/cricket/snapshot/import -F "file=@cricket.sgsnap"

// Leading run scorers across all formats
MATCH (p:Player)-[b:BATTED_IN]->(:Match)
RETURN p.name AS player, sum(b.runs) AS runs
ORDER BY runs DESC LIMIT 5
// V Kohli 36,545 · KC Sangakkara 30,651 · DA Warner 28,317 · RG Sharma 26,748

// Which bowler has dismissed a given batter most often — a question about the
// relationship itself, which is awkward in SQL and direct in a graph
MATCH (bowler:Player)-[d:DISMISSED]->(batter:Player)
RETURN bowler.name, batter.name, count(d) AS times
ORDER BY times DESC LIMIT 10

Provenance

1. Original source — Cricsheet.org, ball-by-ball match data as JSON, CC-BY-4.0. 21,325 files at the time of extraction.

2. ETL — samyama-ai/cricket-kg, which maps those files to a property graph.

3. This dataset — exported from a Samyama snapshot taken 2026-03-14 (sgsnap format v1, engine v0.6.0), then flattened to CSV. Totals were asserted against the snapshot header — 36,619 nodes and 1,392,017 edges — and re-verified after upload.

Versioning

Version	Date	Contents
`v1.0`	2026-08-17	Initial release — 36,619 nodes, 1,392,017 edges from the 2026-03-14 snapshot

Pin the tag, not main. main moves; a tag does not.

load_dataset("VaidhyaMegha/cricket-kg", "player", revision="v1.0")

Data changes get a new tag (v1.1, v2.0); corrections to this card alone land on main.

Limitations

Not literally ball-by-ball. It is built from Cricsheet's ball-by-ball files, but the graph stores per-innings aggregates (BATTED_IN, BOWLED_IN) plus individual dismissals with their over. Delivery-level rows are not preserved. For per-ball analysis, go to the Cricsheet source files.
Coverage starts 2001-12-19 and ends 2026-03-11 — Cricsheet's own range, not the whole history of the sport. Older Tests are absent.
Player identity is per-Cricsheet. cricsheet_id is the key; players are not reconciled against any external registry, and name spellings follow Cricsheet's.
Teams are strings — national sides and franchises share the Team label with no distinction between them.
No ball-by-ball commentary, no partnerships as first-class objects, no fielding positions.

Verified: totals match the snapshot header exactly, every node has at least one edge (0 orphans of 36,619), and aggregates reproduce known records — V Kohli leading run-scorer, JM Anderson leading wicket-taker at 1,140.

Citation

CC-BY-4.0 requires attribution. Cite both the source and this build.

Original source:

Cricsheet. Ball-by-ball cricket data. https://cricsheet.org/
Licensed CC-BY-4.0. https://creativecommons.org/licenses/by/4.0/

This graph build:

Cricket Knowledge Graph, v1.0 (36,619 nodes, 1,392,017 edges).
Built with Samyama Graph. https://huggingface.co/datasets/VaidhyaMegha/cricket-kg
ETL: https://github.com/samyama-ai/cricket-kg
Source data: Cricsheet.org, CC-BY-4.0, https://cricsheet.org/

@misc{cricket_kg_samyama,
  title        = {Cricket Knowledge Graph},
  howpublished = {\url{https://huggingface.co/datasets/VaidhyaMegha/cricket-kg}},
  version      = {v1.0},
  note         = {Derived from Cricsheet.org ball-by-ball data, CC-BY-4.0,
                  \url{https://cricsheet.org/}.
                  ETL: \url{https://github.com/samyama-ai/cricket-kg}},
  year         = {2026}
}

The three pieces

Piece	Where
Code — ETL, schema, loaders	github.com/samyama-ai/cricket-kg
Data — this dataset, and the raw source it derives from	here, and cricsheet.org
Graph — importable snapshot	`cricket.sgsnap` in this repository

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