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analyzeNflMarkov.py
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analyzeNflMarkov.py
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#! /usr/bin/env python
import os, sys
import nflMarkov
import numpy as np
import matplotlib
import matplotlib.pyplot as plt
import pylab
#########################
def readCsv(ifile):
skeys = ['date', 'homeTeam', 'awayTeam', 'game_id','player','posteam','oldstate','newstate']
ikeys = ['seas','igame_id','yds']
fkeys = []
dt = []
lines = [l.strip() for l in open(ifile).readlines()]
hd = lines[0]
ks = hd.split(',')
for k in ks:
if k in skeys:
tmp = (k, 'S64')
elif k in ikeys:
tmp = (k, 'i4')
elif k in fkeys:
tmp = (k, 'f4')
else:
tmp = (k, 'f8')
dt.append(tmp)
dt = pylab.dtype(dt)
data = pylab.genfromtxt(ifile, dtype=dt, skip_header=1, delimiter=',')
return data
#########################
def loadPlayByPlay(csvfile, vbose=0):
skeys = ['game_id','type','playerName','posTeam','awayTeam','homeTeam']
ikeys = ['seas','igame_id','dwn','ytg','yfog','yds']
fkeys = []
lines = [l.strip() for l in open(csvfile).readlines()]
hd = lines[0]
ks = hd.split(',')
dt = []
for k in ks:
# postgres copy to file makes headers lower-case; this is a kludge
if k=='playername':
k = 'playerName'
elif k=='posteam':
k = 'posTeam'
elif k=='away_team':
k = 'awayTeam'
elif k=='awayteam':
k = 'awayTeam'
elif k=='home_team':
k = 'homeTeam'
elif k=='hometeam':
k = 'homeTeam'
if k in skeys:
tmp = (k, 'S16')
elif k in ikeys:
tmp = (k, 'i4')
else:
tmp = (k, 'f8')
if vbose>=1:
print k, tmp
dt.append(tmp)
dt = pylab.dtype(dt)
data = pylab.genfromtxt(csvfile, dtype=dt, delimiter=',', skip_header=1)
return data
#########################
def getExpectedPoints(nm, state):
i = nm.state2int[state]
return nm.expectedPoints[i,0]
#########################
def loadStoredModels(nm, modName):
nm.readPickle(modName)
#########################
if __name__=='__main__':
nm = nflMarkov.nflMarkov()
# modName = 'outputData/emp_05142014.pkl'
modName = 'outputData/emp_05312014.pkl'
# csvfile = 'inputData/pbp_2009_2013.csv'
# csvfile = 'inputData/pbp_2002_2010.csv'
csvfile = 'inputData/pbp_nfldb_2009_2013.csv'
loadStoredModels(nm, modName)
k = nm.storedModels.keys()[0]
mod = nm.storedModels[k]
tm = mod['transitionMatrix']
rs = np.transpose(mod['resultMatrix'])
x = np.reshape(np.array(nm.endStatePoints), (4,1))
nm.expectedPoints = rs.dot(x)
xp = np.transpose(nm.expectedPoints)
pbp = loadPlayByPlay(csvfile, vbose=0)
print pbp
pp = []
ishow = True
# csvfile = 'pe7920_2013.csv'
# csvfile = 'pe7920_2002_2010.csv'
csvfile = 'pe7920_nfldb_2009_2013.csv'
ofp = open(csvfile, 'w')
ofp.write('seas,game_id,awayTeam,homeTeam,player,posteam,oldstate,oldpoints,pltype,yds,newstate,newpoints,dPE\n')
for p in pbp:
print 'hereisp', p
# print p.dtype
seas = p['seas']
if seas!=2013:
# continue
pass
ptype = p['type']
if not ptype in ['PASS', 'RUSH']:
continue
dwn, ytg, yfog, yds = p['dwn'], p['ytg'], p['yfog'], p['yds']
pl = p['playerName']
posteam = p['posTeam']
if dwn==0:
continue
if yfog==0:
continue
if ytg>20:
ytg=20
oldState = nm.infoToState(dwn, ytg, yfog)
newState = nm.getNewState(yds, oldState)
oldPoints = getExpectedPoints(nm, oldState)
newPoints = getExpectedPoints(nm, newState)
ii = nm.state2int[oldState]
y = np.reshape(tm[:,ii], (7924, 1))
ans = xp.dot(y)
avgNewPoints = ans[0,0]
dPE = newPoints-oldPoints
aPE = avgNewPoints-oldPoints
PEAA = dPE-aPE
if not 'game_id' in p.dtype.fields:
gid = '%4d_%04d' % (seas, p['igame_id'])
else:
gid = p['game_id']
if not 'awayTeam' in p.dtype.fields:
awayTeam = 'AAA'
else:
awayTeam = p['awayTeam']
if not 'homeTeam' in p.dtype.fields:
homeTeam = 'HHH'
else:
homeTeam = p['homeTeam']
print (p['seas'], gid, pl, p['posTeam'], oldState, oldPoints, p['type'], yds, newState, newPoints, dPE)
ofp.write('%d,%s,%s,%s,%s,%s,%s,%.4f,%s,%d,%s,%.4f,%.6f\n'
%
(p['seas']
, gid
, awayTeam, homeTeam
, pl
, p['posTeam']
, oldState, oldPoints, p['type']
, yds, newState
, newPoints, dPE
)
)
pp.append(dPE)
ofp.close()
pylab.hist(pp, bins=90, color='c')
pylab.xlabel('d(Points Expectancy)')
pylab.ylabel('N')
ax = pylab.gca()
pylab.text(0.65, 0.8, 'mean= %.3f' % pylab.mean(pp), transform=ax.transAxes)
pylab.text(0.65, 0.75, 'std = %.3f' % pylab.std(pp), transform=ax.transAxes)
pylab.title('PE7920 (2013)')
pylab.savefig('PE7920_2013_1.png')
if ishow:
pylab.show()
data = readCsv(csvfile)