fagan2888 / nbastats

NBA Stats Documentation

NBAStats

This is a Python module I have put together to make it easier and faster to parse NBA statistics.

version 1.0.1

My apologies for the lack of documentation within the package and on here. That will be coming quickly.

To get started, install the module using the following: $ easy_install nbastats or $ pip install nbastats

This module requires the most recent versions of pandas and requests.

Once you have NBAStats installed, load it into your python environment using:

import nbastats.nbastats as nbastats

Once you have the package imported, you can use the following commands to collect data:

##Shot Chart Data

If you wish to see detailed information on a single players shot chart, use the ShotChart method. To use this method, you first need the unique id number of the player you are interested in. You can obtain this by finding the player's profile page on http://stats.nba.com and looking in the address bar. You may have to click the "stats" tab when you find the players page. For this example, I'll use Paul George. His NBA ID is 202331.

george = nbastats.ShotChart('202331')
george.shotchart().head(2)

This code returns the following pandas dataframe:

index	GRID_TYPE	GAME_ID	GAME_EVENT_ID	PLAYER_ID	PLAYER_NAME	TEAM_ID	TEAM_NAME	PERIOD	MINUTES_REMAINING	SECONDS_REMAINING	EVENT_TYPE	ACTION_TYPE	SHOT_TYPE	SHOT_ZONE_BASIC	SHOT_ZONE_AREA	SHOT_ZONE_RANGE	SHOT_DISTANCE	LOC_X	LOC_Y	SHOT_ATTEMPTED_FLAG	SHOT_MADE_FLAG
0	Shot Chart Detail	0021300001	5	202331	Paul George	1610612754	Indiana Pacers	1	11	30	Made Shot	Pullup Jump shot	2PT Field Goal	Mid-Range	Right Side Center(RC)	16-24 ft.	19	105	164	1	1
1	Shot Chart Detail	0021300001	16	202331	Paul George	1610612754	Indiana Pacers	1	10	11	Made Shot	Layup Shot	2PT Field Goal	Restricted Area	Center(C)	Less Than 8 ft.	1	-10	3	1	1

There are a couple things to note. First, invoking nbastats.ShotChart('202331') creates an object that has to unique methods. each of these returns specific data in a Pandas dataframe. You can manipulate and adjust all of the data just as you would with a normal Pandas dataframe.

###Methods

####.shotchart() This method of the returns detailed information about all of a players shots that you have chosen. The table above is an example of the type of data that this method returns.

####.leagueaverage() This method returns a table with league averages for shots taken and made from each of the identified zones on the court. This is not player specific information. It is league specific. If you invoke this method for different players during the same time period, the results should be identical.

###Customization There are quite a few ways to customize the actual data that is collected from the website by adjusting the current code. Each of the potential changes are described below. Some variables have a discrete number of options. The options are listed underneath their respective variables. Default values are in bold.

• playerid - no default value; Required
• leagueid
  • 00
  • 20
• season - Input in format of 20XX-XX
  • 2013-14
• seasontype
  • Regular Season
  • Playoffs
  • All Star
• teamid - Only useful if a player played on more than one team during a season. Allows you to pull all of the shots taken during a specific season while playing for a specific team.
  • blank
• gameid - Used to select shots taken during a specific game
  • blank
• outcome - Selects shot taken during games with a specific outcome.
  • W
  • L
  • blank
• location - Selects shots taken during games played at different locations
  • Home
  • Road
  • blank
• month - Selects shots taken during a specific month.
  • 0 (all months)
• seasonsegment - Selects shots taken during a segment of the season
  • Post All-Star
  • Pre All-Star
  • blank
• datefrom - Selects shots taken after a specific date; 2004-01-01 format
  • blank
• dateto - Selects shots taken before a specific date; 2004-01-01 format
  • blank
• opponentteamid - Selects shots taken against a specific team
  • blank
• vsconf - Selects shots taken against a specific conference
  • East
  • West
  • blank
• vsdiv - Selects shots taken against a specific division
  • Atlantic
  • Central
  • Northwest
  • Pacific
  • Southeast
  • Southwest
  • East
  • West
  • blank
• position - Selects shots taken when labeled as specific position; not useful
  • Guard
  • Center
  • Forward
  • blank
• gamesegment - Selects shots taken during a specific segment of a game
  • First Half
  • Overtime
  • Second Half
  • blank
• period - Selects shots taken during specific periods of games
  • 0 returns all shots
  • Takes values 0-9
• lastngames - Selects shots taken during past N games; Will not aggregate across seasons
  • 0 returns all games
• aheadbehind - Selects shots taken during specific situations in a game
  • Ahead or Behind
  • Ahead or Tied
  • Behind or Tied
  • blank
• contextmeasure - Description
  • FGM
  • FGA
  • FG_PCT
  • FG3M
  • FG3A
  • FG3_PCT
  • PF
  • EFG_PCT
  • TS_PCT
  • PTS_FB
  • PTS_OFF_TOV
  • PTS_2ND_CHANCE
• clutchtime - Selects shots taken during specific "clutch" times during a game
  • Last 5 Minutes
  • Last 4 Minutes
  • Last 3 Minutes
  • Last 2 Minutes
  • Last 1 Minute
  • Last 30 Seconds
  • Last 10 Seconds
  • blank

When you adjust these values, be sure the selected value is included as a string. For example, to select all of Paul George's shots taken during the last minute of every game he played during the 2012-13 season, you would run the following code:

george = nbastats.ShotChart('202331', season='2012-13', clutchtime='Last 1 Minute')
george.shotchart()

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##BoxScore Data

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##Player Game Logs

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##Play By Play Data

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##Lineup Data