def __init__(self, gm, RoP):
self.game = Game(gm, RoP)
record, rot, bxs = self.game.preprocess(load=1)
self.record = record
self.rot = rot
self.bxs = bxs
self.dist = [
' 0~ 5ft 2PT', ' 5~10ft 2PT', ' 10~15ft 2PT',
' 15~20ft 2PT', ' >20ft 2PT', ' <=25ft 3PT',
' 25~30ft 3PT', ' 30~35ft 3PT', ' 35~40ft 3PT',
' >40ft 3PT', ' restricted(RA)', ' paint(Non-RA)',
' mid range', ' left corner 3', ' right corner 3',
' above the break 3'
]
def detectgame(self, gm, playeres, season=0):
game = Game(gm[:-7], 'playoff' if self.RoP else 'regular')
for qtr in range(3, game.quarters):
for ply in game.yieldPlay(qtr):
play = Play(ply, qtr)
if play.time() <= MPTime(self.lm): # 在规定时间内
rec, ind = play.record()
s = play.score(ind=ind)
if s and play.diffbeforescore(s) <= self.dp:
try:
p = self.pm2pn[rec.split(' ')[0]]
except KeyError:
p = rec.split(' ')[0]
if season:
p += ' %d_%d' % (season, season + 1)
if p not in playeres:
playeres[p] = np.zeros((1, len(self.columns)))
if 'makes' in rec: # 得分增加命中数
playeres[p][0, 0] += s
playeres[p][0, s * 3 - 1] += 1
if 'assist' in rec: # 受助攻
playeres[p][0, s + 11] += 1
playeres[p][0, 15] += 1
try:
astp = self.pm2pn[rec.split(' ')[-1][:-1]]
except:
astp = rec.split(' ')[-1][:-1]
if season:
astp += ' %d_%d' % (season, season + 1)
if astp not in playeres:
playeres[astp] = np.zeros(
(1, len(self.columns)))
playeres[astp][0, s + 14] += 1
playeres = self.onlycountonce(
astp, gm[:-7], playeres)
playeres[p][0, s * 3] += 1 # 得分或投失增加出手数
playeres = self.onlycountonce(p, gm[:-7], playeres)
# if 'LeBron James' in p and season == 2019:
# print(s, play.play, gm[:-7], self.plyrcgs['LeBron James 2019_2020'])
return playeres
def inline(r):
line = r['R'][RoH]
return sorted(line, reverse=True)
lines_all = LoadPickle('./data/Lineups/anaSeason5Lineups.pickle')
for season in range(2020, 2021):
ss = '%d_%d' % (season, season + 1)
for i in range(2):
lines_all[i][ss] = {}
lines = {
} # {'tm1': {'line1': ['sum_time', '+/-'], 'line2': ['sum_time', '+/-'] ...}, 'tm2': ...}
gms = os.listdir('D:/sunyiwu/stat/data/seasons/%s/%s/' %
(ss, regularOrPlayoffs[i]))
for gm in tqdm(gms):
game = Game(gm, regularOrPlayoffs[i])
record = LoadPickle(gameMarkToDir(gm, regularOrPlayoffs[i], tp=3))
rot = game.rotation(record)
bxs, rot = game.replayer(record, rot)
et = '%d:00.0' % (48 + 5 * (game.quarters - 4))
for tmix, tm in enumerate(list(game.bxscr[0])): # 分别回溯两支球队
if tm not in lines:
lines[tm] = {}
RoH = list(game.bxscr[0]).index(tm)
for ix, r in enumerate(rot):
line = inline(r)
if ' '.join(line) not in lines[tm]:
lines[tm][' '.join(line)] = [
MPTime('0:00.0'), 0,
[np.zeros((21, )),
np.zeros((21, ))]
# ================ 球员单场数据准备 ================
mpsum += mp
pts = float(sgm['PTS'])
fta, ft, fga, fg, tpa, tp = float(
sgm['FTA']), float(sgm['FT']), float(
sgm['FGA']), float(sgm['FG']), float(
sgm['3PA']), float(sgm['3P'])
drb, orb, trb = float(sgm['DRB']), float(
sgm['ORB']), float(sgm['TRB'])
ast, stl, blk, tov, pf = float(
sgm['AST']), float(sgm['STL']), float(
sgm['BLK']), float(sgm['TOV']), float(
sgm['PF'])
# ================ 球员本队数据准备 ================
gm = sgm['Playoffs' if i else 'Date'].values[0]
game = Game(gm, RoF[i])
tm_gametime = 48 if game.quarters == 4 else 48 + 5 * (
game.quarters - 4)
plyrs = game.teamplyrs()
ts = 0 if pm in plyrs[0] else 1
os = 0 if ts else 1
ttl = [
game.bxscr[1][0][-1], game.bxscr[1][1][-1]
]
tm_ast, tm_fg = int(ttl[ts][14]), int(
ttl[ts][2])
# 0.5 * ((Tm FGA + 0.4 * Tm FTA - 1.07 * (Tm ORB / (Tm ORB + Opp DRB)) * (Tm FGA - Tm FG) + Tm TOV) +
# (Opp FGA + 0.4 * Opp FTA - 1.07 * (Opp ORB / (Opp ORB + Tm DRB)) * (Opp FGA - Opp FG) + Opp TOV))
tm_poss = int(ttl[ts][3]) + 0.4 * int(
ttl[ts][9]) - 1.07 * (
int(ttl[ts][11]) /
[MPTime('0:00.0'), MPTime('0:00.0'), MPTime('0:00.0'), MPTime('0:00.0'), MPTime('0:00.0'), MPTime('0:00.0'), MPTime('0:00.0'), MPTime('0:00.0'), MPTime('0:00.0')],
[MPTime('0:00.0'), MPTime('0:00.0'), MPTime('0:00.0'), MPTime('0:00.0'), MPTime('0:00.0'), MPTime('0:00.0'), MPTime('0:00.0'), MPTime('0:00.0'), MPTime('0:00.0')]],
[[MPTime('0:00.0'), MPTime('0:00.0'), MPTime('0:00.0'), MPTime('0:00.0'), MPTime('0:00.0'), MPTime('0:00.0'), MPTime('0:00.0'), MPTime('0:00.0'), MPTime('0:00.0')],
[MPTime('0:00.0'), MPTime('0:00.0'), MPTime('0:00.0'), MPTime('0:00.0'), MPTime('0:00.0'), MPTime('0:00.0'), MPTime('0:00.0'), MPTime('0:00.0'), MPTime('0:00.0')],
[MPTime('0:00.0'), MPTime('0:00.0'), MPTime('0:00.0'), MPTime('0:00.0'), MPTime('0:00.0'), MPTime('0:00.0'), MPTime('0:00.0'), MPTime('0:00.0'), MPTime('0:00.0')]]]
average_time = [[['', '', '', '', '', '', '', '', ''], ['', '', '', '', '', '', '', '', ''], ['', '', '', '', '', '', '', '', '']],
[['', '', '', '', '', '', '', '', ''], ['', '', '', '', '', '', '', '', ''], ['', '', '', '', '', '', '', '', '']]]
count_score = np.zeros((2, 3, 9))
ss = '%d_%d' % (season, season + 1)
# print(ss)
for i in range(2): # 分别统计常规赛、季后赛
gms = os.listdir('D:/sunyiwu/stat/data/seasons/%s/%s/' % (ss, regularOrPlayoffs[i]))
for gm in tqdm(gms):
count_games[i] += 1
# print('\t\t\t' + gm)
game = Game(gm[:-7], regularOrPlayoffs[i])
gameplyrs = game.teamplyrs()
record = LoadPickle(gameMarkToDir(gm[:-7], regularOrPlayoffs[i], tp=3))
# _, _, _, record = game.game_scanner(gm[:-7])
zoom = 0
bp = -1
pm = ''
for rec in record:
if zoom: # 处于抢断/失误观察期内
# 出现得失分
if 'MK' in rec or 'MS' in rec:
GoM = 1 if 'MK' in rec else 0
KoS = 'MK' if GoM else 'MS'
plyr_side = 0 if pm in gameplyrs[0] else 1
if tar_item:
plyr_side = 0 if plyr_side else 1
#!/usr/bin/python
# -*- coding:utf8 -*-
from klasses.Game import Game
from klasses.miscellaneous import MPTime
gm = '200102280DEN'
game = Game(gm, 'regular')
# print(game.teamplyrs())
_, _, _, record = game.game_scanner(gm)
for i in record:
# if 'MK' in i or 'MS' in i:
print(i)
# game.game_analyser(gm, record)
# game.pace(gm, record)
game.find_time_series(gm, record)
# a = MPTime('47:36.1')
# b = MPTime('47:36.0')
# print(a >= b) # True
#!/usr/bin/python
# -*- coding:utf8 -*-
from klasses.Game import Game
from klasses.Player import Player
from util import LoadPickle, playerMarkToDir, writeToPickle, gameMarkToSeason
from stats_nba.Game_nba import Game_nba
import pandas as pd
import numpy as np
np.set_printoptions(suppress=True)
pd.options.display.expand_frame_repr = False
pd.options.display.width = 50
RoF = 0
gm = '201201070NJN'
game = Game(gm, 'playoff' if RoF else 'regular')
record = game.game_scanner()
# for i in record:
# print(i)
record = game.game_analyser(record)
record = game.game_analyser(record, T=1)
ss = gameMarkToSeason(gm)
rof = 'playoff' if RoF else 'regular'
season_dir = 'D:/sunyiwu/stat/data/seasons_scanned/%s/%s/' % (ss, rof)
writeToPickle(season_dir + gm + '_scanned.pickle', record)
for i in record:
print(i)
# print()
game.find_time_series(record)
game.start_of_quarter(record)
inter = 600 # 设置按时间归并区间的间隔
inter_s = inter // 10
whole = 34800 # 整场比赛时间（双加时为止）
max_diff = 40
diff_inter = 5
# 1、2、3分 x 命中数、出手数 x -40~40分差 x 间隔统计时间
shoots = np.zeros((3, 2, max_diff * 2 // diff_inter + 1, whole // inter))
prctg = np.zeros((3, max_diff * 2 // diff_inter + 1, whole // inter))
for season in player.yieldSeasons():
for gameInf in player.yieldGames(season):
# score += int(gameInf[26])
gm = gameInf[1]
team = gameInf[3]
op = gameInf[5]
game = Game(gm, ROP, team, op)
for qtr in range(game.quarters):
for playInf in game.yieldPlay(qtr):
play = Play(playInf, qtr, pm=pm, HOA=game.HOA)
if play.playRecord() and play.teamPlay():
if play.playerAst(): # 助攻
asts += 1
elif play.playerMadeShoot(): # 命中投篮
s, d, t = score_diff_time(play, game, max_diff)
d -= s # 关注的是球员得分前的分差
score += s
t = tailTime(t, inter_s)
d = groupDiff(d + 40, max_diff, diff_inter)
shoots[s - 1, 0, d, t] += 1
shoots[s - 1, 1, d, t] += 1