import json import os.path from nflgame import OrderedDict import nflgame.seq import nflgame.statmap _player_json_file = os.path.join(os.path.dirname(__file__), 'players.json') def _create_players(jsonf=None): """ Creates a dict of Player objects from the players.json file, keyed by GSIS ids. """ if jsonf is None: jsonf = _player_json_file try: data = json.loads(open(jsonf).read()) except IOError: return {} players = {} for playerid in data: players[playerid] = Player(data[playerid]) return players class Player (object): """ Player instances represent meta information about a single player. This information includes name, team, position, status, height, weight, college, jersey number, birth date, years, pro, etc. Player information is populated from NFL.com profile pages. """ def __init__(self, data): self.player_id = data['gsis_id'] self.gsis_name = data.get('gsis_name', '') self.full_name = data.get('full_name', '') self.first_name = data.get('first_name', '') self.last_name = data.get('last_name', '') self.team = data.get('team', '') self.position = data.get('position', '') self.profile_id = data.get('profile_id', 0) self.profile_url = data.get('profile_url', '') self.uniform_number = data.get('uniform_number', 0) self.birthdate = data.get('birthdate', '') self.college = data.get('college', '') self.height = data.get('height', '') self.weight = data.get('weight', '') self.years_pro = data.get('years_pro', 0) self.status = data.get('status', '') # API backwards compatibility. self.playerid = self.player_id self.name = self.full_name self.number = self.uniform_number def stats(self, year, week=None): games = nflgame.games(year, week) players = nflgame.combine(games).filter(playerid=self.playerid) return list(players)[0] def plays(self, year, week=None): plays = [] games = nflgame.games(year, week) for g in games: plays += filter(lambda p: p.has_player(self.playerid), list(g.drives.plays())) return nflgame.seq.GenPlays(plays) def __str__(self): return '%s (%s, %s)' % (self.name, self.position, self.team) class PlayerDefense (Player): def __init__(self, team): self.playerid = None self.name = team self.team = team self.position = 'DEF' def stats(self, year, week=None): assert False, 'Cannot be called on a defense.' def plays(self, year, week=None): assert False, 'Cannot be called on a defense.' def __str__(self): return '%s Defense' % self.team class PlayerStats (object): """ Player represents a single player and all of his statistical categories. Every player has 'playerid', 'name' and 'home' fields. Additionally, depending upon which statistical categories that player was involved in for the game, he'll have properties such as 'passing_tds', 'rushing_yds', 'defense_int' and 'kicking_fgm'. In order to know whether a paricular player belongs to a statical category, you may use the filtering methods of a player sequence or alternatively, use the has_cat method with arguments like 'passing', 'rushing', 'kicking', etc. (A player sequence in this case would be an instance of GenPlayerStats.) You may also inspect whether a player has a certain property by using the special __dict__ attribute. For example:: if 'passing_yds' in player.__dict__: # Do something with player.passing_yds """ def __init__(self, playerid, name, home, team): """ Create a new Player instance with the player id (from NFL.com's GameCenter), the player's name (e.g., "T.Brady") and whether the player is playing in a home game or not. """ self.playerid = playerid self.name = name self.home = home self.team = team self._stats = OrderedDict() self.player = None if self.playerid in nflgame.players: self.player = nflgame.players[self.playerid] def has_cat(self, cat): for f in self._stats: if f.startswith(cat): return True return False @property def guess_position(self): """ Guesses the position of this player based on the statistical categories present in this object when player meta is not present. Note that if this resorts to a guess, then it will be more effective on aggregate data rather than data from just a single play. (e.g., if a QB runs the ball, and that's the only data available, the position returned will be RB.) When a position is guessed, only the following positions will be returned: QB, RB, WR, DEF, K and P. """ # Look for the player meta first. Duh. if self.player is not None: return self.player.position stats = [ (self.passing_att, 'QB'), (self.rushing_att, 'RB'), (self.receiving_tar, 'WR'), (self.defense_tkl, 'DEF'), (self.defense_ast, 'DEF'), (self.kicking_tot, 'K'), (self.kicking_fga, 'K'), (self.punting_tot, 'P'), ] return sorted(stats, reverse=True)[0][1] @property def tds(self): """ Returns the total number of touchdowns credited to this player across all statistical categories. """ n = 0 for f, v in self.__dict__.iteritems(): if f.endswith('tds'): n += v return n @property def twopta(self): """ Returns the total number of two point conversion attempts for the passing, rushing and receiving categories. """ return (self.passing_twopta + self.rushing_twopta + self.receiving_twopta) @property def twoptm(self): """ Returns the total number of two point conversions for the passing, rushing and receiving categories. """ return (self.passing_twoptm + self.rushing_twoptm + self.receiving_twoptm) @property def twoptmissed(self): """ Returns the total number of two point conversion failures for the passing, rushing and receiving categories. """ return (self.passing_twoptmissed + self.rushing_twoptmissed + self.receiving_twoptmissed) @property def stats(self): """ Returns a dict of all stats for the player. """ return self._stats def formatted_stats(self): """ Returns a roughly-formatted string of all statistics for this player. """ s = [] for stat, val in self._stats.iteritems(): s.append('%s: %s' % (stat, val)) return ', '.join(s) def _add_stats(self, stats): for k, v in stats.iteritems(): self.__dict__[k] = self.__dict__.get(k, 0) + v self._stats[k] = self.__dict__[k] def _overwrite_stats(self, stats): for k, v in stats.iteritems(): self.__dict__[k] = v self._stats[k] = self.__dict__[k] def __str__(self): """ Simply returns the player's name, e.g., "T.Brady". """ return self.name def __add__(self, other): """ Adds two players together. Only two player objects that correspond to the same human (i.e., GameCenter identifier) can be added together. If two different players are added together, an assertion will be raised. The effect of adding two player objects simply corresponds to the sums of all statistical values. Note that as soon as two players have been added, the 'home' property becomes undefined if the two operands have different values of 'home'. """ assert self.playerid == other.playerid assert type(self) == type(other) if self.home != other.home: home = None else: home = self.home new_player = self.__class__(self.playerid, self.name, home, self.team) new_player._add_stats(self._stats) new_player._add_stats(other._stats) return new_player def __sub__(self, other): assert self.playerid == other.playerid assert type(self) == type(other) new_player = GamePlayerStats(self.playerid, self.name, self.home, self.team) new_player._add_stats(self._stats) for bk, bv in other._stats.iteritems(): if bk not in new_player._stats: # stat was taken away? ignore. continue new_player._stats[bk] -= bv if new_player._stats[bk] == 0: del new_player._stats[bk] else: new_player.__dict__[bk] = new_player._stats[bk] anydiffs = False for k, v in new_player._stats.iteritems(): if v > 0: anydiffs = True break if not anydiffs: return None return new_player def __getattr__(self, name): # If name has one of the categories as a prefix, then return # a default value of zero for cat in nflgame.statmap.categories: if name.startswith(cat): return 0 raise AttributeError class GamePlayerStats (PlayerStats): def __init__(self, playerid, name, home, team): super(GamePlayerStats, self).__init__(playerid, name, home, team) self.games = 1 def __add__(self, other): new_player = super(GamePlayerStats, self).__add__(other) new_player.games = self.games + other.games return new_player class PlayPlayerStats (PlayerStats): pass
class GamePlayerStats
class GamePlayerStats (PlayerStats): def __init__(self, playerid, name, home, team): super(GamePlayerStats, self).__init__(playerid, name, home, team) self.games = 1 def __add__(self, other): new_player = super(GamePlayerStats, self).__add__(other) new_player.games = self.games + other.games return new_player
var games
var guess_position
Inheritance:
PlayerStats
.guess_position
Guesses the position of this player based on the statistical categories present in this object when player meta is not present.
Note that if this resorts to a guess, then it will be more effective on aggregate data rather than data from just a single play. (e.g., if a QB runs the ball, and that's the only data available, the position returned will be RB.)
When a position is guessed, only the following positions will be returned: QB, RB, WR, DEF, K and P.
var tds
Inheritance:
PlayerStats
.tds
Returns the total number of touchdowns credited to this player across all statistical categories.
var twopta
Inheritance:
PlayerStats
.twopta
Returns the total number of two point conversion attempts for the passing, rushing and receiving categories.
var twoptm
Inheritance:
PlayerStats
.twoptm
Returns the total number of two point conversions for the passing, rushing and receiving categories.
var twoptmissed
Inheritance:
PlayerStats
.twoptmissed
Returns the total number of two point conversion failures for the passing, rushing and receiving categories.
def __init__(
self, playerid, name, home, team)
Inheritance:
PlayerStats
.__init__
Create a new Player instance with the player id (from NFL.com's GameCenter), the player's name (e.g., "T.Brady") and whether the player is playing in a home game or not.
def __init__(self, playerid, name, home, team): super(GamePlayerStats, self).__init__(playerid, name, home, team) self.games = 1
def formatted_stats(
self)
Inheritance:
PlayerStats
.formatted_stats
Returns a roughly-formatted string of all statistics for this player.
def formatted_stats(self): """ Returns a roughly-formatted string of all statistics for this player. """ s = [] for stat, val in self._stats.iteritems(): s.append('%s: %s' % (stat, val)) return ', '.join(s)
def has_cat(
self, cat)
Inheritance:
PlayerStats
.has_cat
def has_cat(self, cat): for f in self._stats: if f.startswith(cat): return True return False
class PlayPlayerStats
class PlayPlayerStats (PlayerStats): pass
var guess_position
Inheritance:
PlayerStats
.guess_position
Guesses the position of this player based on the statistical categories present in this object when player meta is not present.
Note that if this resorts to a guess, then it will be more effective on aggregate data rather than data from just a single play. (e.g., if a QB runs the ball, and that's the only data available, the position returned will be RB.)
When a position is guessed, only the following positions will be returned: QB, RB, WR, DEF, K and P.
var tds
Inheritance:
PlayerStats
.tds
Returns the total number of touchdowns credited to this player across all statistical categories.
var twopta
Inheritance:
PlayerStats
.twopta
Returns the total number of two point conversion attempts for the passing, rushing and receiving categories.
var twoptm
Inheritance:
PlayerStats
.twoptm
Returns the total number of two point conversions for the passing, rushing and receiving categories.
var twoptmissed
Inheritance:
PlayerStats
.twoptmissed
Returns the total number of two point conversion failures for the passing, rushing and receiving categories.
def __init__(
self, playerid, name, home, team)
Inheritance:
PlayerStats
.__init__
Create a new Player instance with the player id (from NFL.com's GameCenter), the player's name (e.g., "T.Brady") and whether the player is playing in a home game or not.
def __init__(self, playerid, name, home, team): """ Create a new Player instance with the player id (from NFL.com's GameCenter), the player's name (e.g., "T.Brady") and whether the player is playing in a home game or not. """ self.playerid = playerid self.name = name self.home = home self.team = team self._stats = OrderedDict() self.player = None if self.playerid in nflgame.players: self.player = nflgame.players[self.playerid]
def formatted_stats(
self)
Inheritance:
PlayerStats
.formatted_stats
Returns a roughly-formatted string of all statistics for this player.
def formatted_stats(self): """ Returns a roughly-formatted string of all statistics for this player. """ s = [] for stat, val in self._stats.iteritems(): s.append('%s: %s' % (stat, val)) return ', '.join(s)
def has_cat(
self, cat)
Inheritance:
PlayerStats
.has_cat
def has_cat(self, cat): for f in self._stats: if f.startswith(cat): return True return False
class Player
Player instances represent meta information about a single player. This information includes name, team, position, status, height, weight, college, jersey number, birth date, years, pro, etc.
Player information is populated from NFL.com profile pages.
class Player (object): """ Player instances represent meta information about a single player. This information includes name, team, position, status, height, weight, college, jersey number, birth date, years, pro, etc. Player information is populated from NFL.com profile pages. """ def __init__(self, data): self.player_id = data['gsis_id'] self.gsis_name = data.get('gsis_name', '') self.full_name = data.get('full_name', '') self.first_name = data.get('first_name', '') self.last_name = data.get('last_name', '') self.team = data.get('team', '') self.position = data.get('position', '') self.profile_id = data.get('profile_id', 0) self.profile_url = data.get('profile_url', '') self.uniform_number = data.get('uniform_number', 0) self.birthdate = data.get('birthdate', '') self.college = data.get('college', '') self.height = data.get('height', '') self.weight = data.get('weight', '') self.years_pro = data.get('years_pro', 0) self.status = data.get('status', '') # API backwards compatibility. self.playerid = self.player_id self.name = self.full_name self.number = self.uniform_number def stats(self, year, week=None): games = nflgame.games(year, week) players = nflgame.combine(games).filter(playerid=self.playerid) return list(players)[0] def plays(self, year, week=None): plays = [] games = nflgame.games(year, week) for g in games: plays += filter(lambda p: p.has_player(self.playerid), list(g.drives.plays())) return nflgame.seq.GenPlays(plays) def __str__(self): return '%s (%s, %s)' % (self.name, self.position, self.team)
var birthdate
var college
var first_name
var full_name
var gsis_name
var height
var last_name
var name
var number
var player_id
var playerid
var position
var profile_id
var profile_url
var status
var team
var uniform_number
var weight
var years_pro
def __init__(
self, data)
def __init__(self, data): self.player_id = data['gsis_id'] self.gsis_name = data.get('gsis_name', '') self.full_name = data.get('full_name', '') self.first_name = data.get('first_name', '') self.last_name = data.get('last_name', '') self.team = data.get('team', '') self.position = data.get('position', '') self.profile_id = data.get('profile_id', 0) self.profile_url = data.get('profile_url', '') self.uniform_number = data.get('uniform_number', 0) self.birthdate = data.get('birthdate', '') self.college = data.get('college', '') self.height = data.get('height', '') self.weight = data.get('weight', '') self.years_pro = data.get('years_pro', 0) self.status = data.get('status', '') # API backwards compatibility. self.playerid = self.player_id self.name = self.full_name self.number = self.uniform_number
def plays(
self, year, week=None)
def plays(self, year, week=None): plays = [] games = nflgame.games(year, week) for g in games: plays += filter(lambda p: p.has_player(self.playerid), list(g.drives.plays())) return nflgame.seq.GenPlays(plays)
def stats(
self, year, week=None)
def stats(self, year, week=None): games = nflgame.games(year, week) players = nflgame.combine(games).filter(playerid=self.playerid) return list(players)[0]
class PlayerDefense
class PlayerDefense (Player): def __init__(self, team): self.playerid = None self.name = team self.team = team self.position = 'DEF' def stats(self, year, week=None): assert False, 'Cannot be called on a defense.' def plays(self, year, week=None): assert False, 'Cannot be called on a defense.' def __str__(self): return '%s Defense' % self.team
def __init__(
self, team)
def __init__(self, team): self.playerid = None self.name = team self.team = team self.position = 'DEF'
def plays(
self, year, week=None)
def plays(self, year, week=None): assert False, 'Cannot be called on a defense.'
def stats(
self, year, week=None)
def stats(self, year, week=None): assert False, 'Cannot be called on a defense.'
class PlayerStats
Player represents a single player and all of his statistical categories. Every player has 'playerid', 'name' and 'home' fields. Additionally, depending upon which statistical categories that player was involved in for the game, he'll have properties such as 'passing_tds', 'rushing_yds', 'defense_int' and 'kicking_fgm'.
In order to know whether a paricular player belongs to a statical category, you may use the filtering methods of a player sequence or alternatively, use the has_cat method with arguments like 'passing', 'rushing', 'kicking', etc. (A player sequence in this case would be an instance of GenPlayerStats.)
You may also inspect whether a player has a certain property by using the special dict attribute. For example::
if 'passing_yds' in player.__dict__: # Do something with player.passing_yds
class PlayerStats (object): """ Player represents a single player and all of his statistical categories. Every player has 'playerid', 'name' and 'home' fields. Additionally, depending upon which statistical categories that player was involved in for the game, he'll have properties such as 'passing_tds', 'rushing_yds', 'defense_int' and 'kicking_fgm'. In order to know whether a paricular player belongs to a statical category, you may use the filtering methods of a player sequence or alternatively, use the has_cat method with arguments like 'passing', 'rushing', 'kicking', etc. (A player sequence in this case would be an instance of GenPlayerStats.) You may also inspect whether a player has a certain property by using the special __dict__ attribute. For example:: if 'passing_yds' in player.__dict__: # Do something with player.passing_yds """ def __init__(self, playerid, name, home, team): """ Create a new Player instance with the player id (from NFL.com's GameCenter), the player's name (e.g., "T.Brady") and whether the player is playing in a home game or not. """ self.playerid = playerid self.name = name self.home = home self.team = team self._stats = OrderedDict() self.player = None if self.playerid in nflgame.players: self.player = nflgame.players[self.playerid] def has_cat(self, cat): for f in self._stats: if f.startswith(cat): return True return False @property def guess_position(self): """ Guesses the position of this player based on the statistical categories present in this object when player meta is not present. Note that if this resorts to a guess, then it will be more effective on aggregate data rather than data from just a single play. (e.g., if a QB runs the ball, and that's the only data available, the position returned will be RB.) When a position is guessed, only the following positions will be returned: QB, RB, WR, DEF, K and P. """ # Look for the player meta first. Duh. if self.player is not None: return self.player.position stats = [ (self.passing_att, 'QB'), (self.rushing_att, 'RB'), (self.receiving_tar, 'WR'), (self.defense_tkl, 'DEF'), (self.defense_ast, 'DEF'), (self.kicking_tot, 'K'), (self.kicking_fga, 'K'), (self.punting_tot, 'P'), ] return sorted(stats, reverse=True)[0][1] @property def tds(self): """ Returns the total number of touchdowns credited to this player across all statistical categories. """ n = 0 for f, v in self.__dict__.iteritems(): if f.endswith('tds'): n += v return n @property def twopta(self): """ Returns the total number of two point conversion attempts for the passing, rushing and receiving categories. """ return (self.passing_twopta + self.rushing_twopta + self.receiving_twopta) @property def twoptm(self): """ Returns the total number of two point conversions for the passing, rushing and receiving categories. """ return (self.passing_twoptm + self.rushing_twoptm + self.receiving_twoptm) @property def twoptmissed(self): """ Returns the total number of two point conversion failures for the passing, rushing and receiving categories. """ return (self.passing_twoptmissed + self.rushing_twoptmissed + self.receiving_twoptmissed) @property def stats(self): """ Returns a dict of all stats for the player. """ return self._stats def formatted_stats(self): """ Returns a roughly-formatted string of all statistics for this player. """ s = [] for stat, val in self._stats.iteritems(): s.append('%s: %s' % (stat, val)) return ', '.join(s) def _add_stats(self, stats): for k, v in stats.iteritems(): self.__dict__[k] = self.__dict__.get(k, 0) + v self._stats[k] = self.__dict__[k] def _overwrite_stats(self, stats): for k, v in stats.iteritems(): self.__dict__[k] = v self._stats[k] = self.__dict__[k] def __str__(self): """ Simply returns the player's name, e.g., "T.Brady". """ return self.name def __add__(self, other): """ Adds two players together. Only two player objects that correspond to the same human (i.e., GameCenter identifier) can be added together. If two different players are added together, an assertion will be raised. The effect of adding two player objects simply corresponds to the sums of all statistical values. Note that as soon as two players have been added, the 'home' property becomes undefined if the two operands have different values of 'home'. """ assert self.playerid == other.playerid assert type(self) == type(other) if self.home != other.home: home = None else: home = self.home new_player = self.__class__(self.playerid, self.name, home, self.team) new_player._add_stats(self._stats) new_player._add_stats(other._stats) return new_player def __sub__(self, other): assert self.playerid == other.playerid assert type(self) == type(other) new_player = GamePlayerStats(self.playerid, self.name, self.home, self.team) new_player._add_stats(self._stats) for bk, bv in other._stats.iteritems(): if bk not in new_player._stats: # stat was taken away? ignore. continue new_player._stats[bk] -= bv if new_player._stats[bk] == 0: del new_player._stats[bk] else: new_player.__dict__[bk] = new_player._stats[bk] anydiffs = False for k, v in new_player._stats.iteritems(): if v > 0: anydiffs = True break if not anydiffs: return None return new_player def __getattr__(self, name): # If name has one of the categories as a prefix, then return # a default value of zero for cat in nflgame.statmap.categories: if name.startswith(cat): return 0 raise AttributeError
var guess_position
Guesses the position of this player based on the statistical categories present in this object when player meta is not present.
Note that if this resorts to a guess, then it will be more effective on aggregate data rather than data from just a single play. (e.g., if a QB runs the ball, and that's the only data available, the position returned will be RB.)
When a position is guessed, only the following positions will be returned: QB, RB, WR, DEF, K and P.
var home
var name
var player
var playerid
var stats
Returns a dict of all stats for the player.
var tds
Returns the total number of touchdowns credited to this player across all statistical categories.
var team
var twopta
Returns the total number of two point conversion attempts for the passing, rushing and receiving categories.
var twoptm
Returns the total number of two point conversions for the passing, rushing and receiving categories.
var twoptmissed
Returns the total number of two point conversion failures for the passing, rushing and receiving categories.
def __init__(
self, playerid, name, home, team)
Create a new Player instance with the player id (from NFL.com's GameCenter), the player's name (e.g., "T.Brady") and whether the player is playing in a home game or not.
def __init__(self, playerid, name, home, team): """ Create a new Player instance with the player id (from NFL.com's GameCenter), the player's name (e.g., "T.Brady") and whether the player is playing in a home game or not. """ self.playerid = playerid self.name = name self.home = home self.team = team self._stats = OrderedDict() self.player = None if self.playerid in nflgame.players: self.player = nflgame.players[self.playerid]
def formatted_stats(
self)
Returns a roughly-formatted string of all statistics for this player.
def formatted_stats(self): """ Returns a roughly-formatted string of all statistics for this player. """ s = [] for stat, val in self._stats.iteritems(): s.append('%s: %s' % (stat, val)) return ', '.join(s)
def has_cat(
self, cat)
def has_cat(self, cat): for f in self._stats: if f.startswith(cat): return True return False
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