nba-on-court 0.1.1

attr: nba-on-court.__doc__

Adding data about players on court in NBA games.

nba_on_court package allows you to add to play-by-play data information about players who were on court at any given time.

Instalation

pip install nba-on-court

Important: This package does not request play-by-play data from NBA website. You need to get them in advance, for example, using nba_api package.

https://github.com/swar/nba_api

How it work

Play-by-play NBA data contains information about each event in the game (throw, substitution, foul, etc.) and players who participated in it (PLAYER1_ID, PLAYER2_ID, PLAYER3_ID).

From this data, we get a list of players who were on court in this quarter. Then, we need to filter this list to 10 people who started quarter. This is done by analyzing substitutions in quarter.

I will soon describe a more complete mechanism for processing play-by-play data to obtain information about players on court in an article.

In package two main functions: players_on_court and players_name.

players_on_court takes play-by-play data as input and returns it with 10 columns of the PLAYER_ID of players who were on court at each time.

players_name allows you to replace PLAYER_ID with first and last name of player. This allows user to understand exactly which players were on court (few know PLAYER_ID all players in NBA),but it is not necessary to do this before calculations, because the player’s NAME_SURNAME is not unique, unlike PLAYER_ID.

Code example

>>> from nba_api.stats.endpoints import playbyplayv2
>>> import nba_on_court.nba_on_court as noc
>>>
>>> pbp = playbyplayv2.PlayByPlayV2(game_id="0022100001").play_by_play.get_data_frame()
>>> pbp_with_players = noc.players_on_court(pbp)
>>> len(pbp_with_players.columns) - len(pbp.columns)
10
>>> players_id = list(pbp_with_players.iloc[0, 34:].reset_index(drop=True))
>>> print(players_id)
[201142, 1629651, 201933, 201935, 203925, 201572, 201950, 1628960, 203114, 203507]
>>> players_name = noc.players_name(players_id)
>>> print(players_name)
['Kevin Durant', 'Nic Claxton', 'Blake Griffin', 'James Harden', 'Joe Harris',
'Brook Lopez', 'Jrue Holiday', 'Grayson Allen', 'Khris Middleton', 'Giannis Antetokounmpo']

You can also replace the PLAYER_ID with the player’s name in the entire data frame at once.

>>> cols = ["PLAYER1", "PLAYER2", "PLAYER3", "PLAYER4", "PLAYER5", "PLAYER6", "PLAYER7", "PLAYER8", "PLAYER9", "PLAYER10"]
>>> pbp_with_players.loc[:, cols] = pbp_with_players.loc[:, cols].apply(noc.players_name, result_type="expand")