A package to scrape AFL data.
Project description
Fraser Gehrig
Table of Contents
Description
This is a small webscraper package to scrap AFL player and game statistics data from AFL Tables.
This package is named after the famous St Kilda forward Fraser Gehrig because, why not?
Installation
Currently the best way to install this package is directly from github.
Github
To install from github there are two options, the first option is to clone the repository and do a local install from the cloned directory.
git clone git@github.com:jacaranda-analytics/fraser_gehrig.git
cd fraser_gehrig/ && pip install .
The second option is to install from github without first cloning the repository, to install the latest master branch, run the command.
pip install https://github.com/jacaranda-analytics/fraser_gehrig/archive/master.zip
Examples
The following section shows some example usages for this tool
>>>> import fraser_gehrig.fraser_gehrig as fg
Get player stats for a single year
>>> fg.get_player_stats(year = 2020)
Loading Data:
jumper games_played kicks marks
Crouch, Matt 5 16 162 44
Laird, Rory 29 17 186 46
Smith, Brodie 33 16 203 58
Keays, Ben 28 16 147 47
Crouch, Brad 2 12 136 20
... ... ... ... ...
Schache, Josh 13 2 8 3
Porter, Callum 28 1 4 NA
Trengove, Jackson 8 1 2 1
Dickson, Tory 29 1 NA NA
Young, Lewis 2 1 3 3
[650 rows x 27 columns]
Get game stats For a single year
>>> fg.get_game_by_game_stats(year = 2020)
.
.
.
index player team round opponents stat value
0 0 Atkins, Rory adelaide 0 SY disposals 14
1 1 Atkins, Rory adelaide 1 PA disposals 10
2 2 Atkins, Rory adelaide 2 GC disposals 3
3 3 Atkins, Rory adelaide 3 BL disposals NA
4 4 Atkins, Rory adelaide 4 FR disposals NA
... ... ... ... ... ... ... ...
267600 267600 Young, Lewis bullldogs 13 GE %_played NA
267601 267601 Young, Lewis bullldogs 14 WC %_played NA
267602 267602 Young, Lewis bullldogs 15 HW %_played NA
267603 267603 Young, Lewis bullldogs 16 FR %_played NA
267604 267604 Young, Lewis bullldogs 17 SK %_played NA
[267605 rows x 7 columns]
Get game by game results for a single year
>>> fg.get_game_by_game_results(year = 2020)
team # Opponent KI MK HB
0 Adelaide R1 Sydney 142-200 41-68 107-113
1 Adelaide R2 Port Adelaide 138-226 39-105 121-137
2 Adelaide R3 Gold Coast 145-196 56-87 105-124
3 Adelaide R4 Brisbane Lions 162-199 71-80 70-86
4 Adelaide R5 Fremantle 170-197 79-109 133-88
.. ... ... ... ... ... ...
13 Western Bulldogs R14 Geelong 146-183 61-77 136-140
14 Western Bulldogs R16 West Coast 157-175 59-80 162-86
15 Western Bulldogs R17 Hawthorn 192-140 85-58 158-130
16 Western Bulldogs R18 Fremantle 162-172 58-79 125-129
17 Western Bulldogs EF St Kilda 175-184 75-88 122-100
[324 rows x 25 columns]
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