rugbypy

Repository for rugby data analytics.

rugbypy is a Python package that aims to make rugby data more available to aid in the development of rugby analytics.

Data is updated daily 5AM UTC! Currently we only have 2023 data available with previous years coming soon.

Requirements

python version 3.8

Install

pip install rugbypy

How to use

Match Stats

You can fetch all the matches that occured on a particular date with:

from rugbypy.match import *
matches = fetch_matches(date="20230101")
matches

Fetching matches on date:20230101...

	match_id	competition_id	home_team_id	home_team	away_team_id	away_team	date
0	595735	267979	25907	Northampton Saints	25901	Harlequins	20230101

Then using that match id you can feed it into the match details function:

from rugbypy.match import *
match_details = fetch_match_details(match_id="595735")
match_details

Fetching match details for match_id:595735...

	match_id	date	season	competition_id	competition	venue_id	venue	city_played	home_team	away_team	home_team_id	away_team_id	completed	is_tournament	played_on_grass	attendance	home_team_form	away_team_form
0	595735	20230101	2023	267979	Premiership Rugby	26070	cinch Stadium at Franklin's Gardens	Northampton	Northampton Saints	Harlequins	25907	25901	True	True	True	None	LLWWL	WLWLL

Team Stats

You can then fetch the team stats for a particular team on a particular date with:

from rugbypy.team import *
team_stats = fetch_team_stats(team_id="25901", date="20230108")
team_stats

Fetching team stats for team_id:25901 on date:20230108...

	team	game_date	team_id	team_vs	team_vs_id	match_id	players	clean_breaks	conversion_goals	defenders_beaten	...	scrums_total	scrums_won	tackles	territory	total_free_kicks_conceded	total_lineouts	tries	turnover_knock_on	turnovers_conceded	yellow_cards
0	Harlequins	20230108	25901	Sale Sharks	25908	595741	[158708, 299436, 299031, 298485, 295117, 29477...	3.0	0.0	24.0	...	7.0	5.0	125.0	0.41	0.0	11.0	2.0	8.0	17.0	0.0

1 rows × 42 columns

Player Stats

We have the ability to fetch player stats for all the games they have bene involved in. We firstly identify the `player_id`` of a player by searching our player manifest file.

from rugbypy.player import *
player_manifest = fetch_all_players()
player_manifest.head()

	player_id	player_name
0	246815	Will Edwards
1	158708	Tommaso Allan
2	299436	Oscar Beard
3	299031	Fin Baxter
4	298485	Jordan Els

Or we can search for a certain player through our similarity tool:

from rugbypy.player import *
individual_player = fetch_player(name="johnny sexton")
individual_player

	player_id	player_name
267	149315	Anthony Watson
294	16004	Johnny Sexton
796	291349	Ayden Johnstone

We can also fetch the player stats for any player using their player_ids. In this example we fetch Johnny Sextons player stats:

from rugbypy.player import *
player_stats = fetch_player_stats(player_id="16004")
player_stats

Fetching all player stats for player_id:16004...

player_id	game_date	name	team	team_id	competition_id	competition	match_id	team_vs	team_vs_id	...	rucks_won	runs	tackles	tries	turnover_knock_on	turnovers_conceded
16004	20230204	Johnny Sexton	Ireland	3	180659	Six Nations Championship	596205	Wales	4	...	3.0	8.0	7.0	0.0	0.0	1.0
16004	20230211	Johnny Sexton	Ireland	3	180659	Six Nations Championship	596208	France	9	...	1.0	5.0	3.0	0.0	0.0	0.0
16004	20230312	Johnny Sexton	Ireland	3	180659	Six Nations Championship	596216	Scotland	2	...	2.0	5.0	9.0	0.0	0.0	2.0
16004	20230318	Johnny Sexton	Ireland	3	180659	Six Nations Championship	596219	England	1	...	6.0	9.0	5.0	0.0	1.0	2.0
16004	20230909	Johnny Sexton	Ireland	3	164205	Rugby World Cup	596156	Romania	12	...	0.0	5.0	4.0	2.0	0.0	0.0
16004	20230916	Johnny Sexton	Ireland	3	164205	Rugby World Cup	596166	Tonga	16	...	1.0	1.0	2.0	1.0	0.0	0.0
16004	20230923	Johnny Sexton	Ireland	3	164205	Rugby World Cup	596175	South Africa	5	...	1.0	3.0	11.0	0.0	0.0	0.0

7 rows × 41 columns