In [1]:

import pandas as pd
import numpy as np

import matplotlib.pyplot as plt
from mplsoccer import Pitch

In [2]:

df = pd.read_csv('europaFinal.csv')

In [26]:

df.head(20)

Out[26]:

	level_0	index	minute	second	teamId	x	y	period	type	outcome	playerId	endX	endY	beginning	end	progressive
0	8	227	15	13.0	Villarreal	116.40	77.44	FirstHalf	Pass	Successful	5.0	112.32	39.24	37.612679	7.717513	True
1	11	315	21	29.0	Villarreal	119.64	79.44	FirstHalf	Pass	Unsuccessful	5.0	114.24	62.88	39.441643	23.593898	True
2	12	321	22	15.0	Villarreal	119.40	0.40	FirstHalf	Pass	Unsuccessful	5.0	111.36	38.28	39.604545	8.809540	True
3	15	432	28	52.0	Villarreal	81.36	58.56	FirstHalf	Pass	Successful	5.0	110.64	53.40	42.866341	16.345323	True
4	24	773	47	4.0	Villarreal	119.40	79.60	FirstHalf	Pass	Unsuccessful	5.0	114.24	61.08	39.604545	21.852780	True
5	27	833	47	38.0	Villarreal	99.60	5.44	SecondHalf	Pass	Successful	5.0	92.52	32.88	40.131703	28.387406	True
6	42	1416	82	48.0	Villarreal	71.76	56.40	SecondHalf	Pass	Unsuccessful	5.0	109.08	56.04	50.951522	19.404329	True
7	43	1496	91	31.0	Villarreal	74.04	59.12	SecondHalf	Pass	Unsuccessful	5.0	109.08	41.04	49.778469	10.969412	True
8	50	1677	97	24.0	Villarreal	86.40	54.80	FirstPeriodOfExtraTime	Pass	Unsuccessful	5.0	116.16	40.68	36.715120	3.899744	True
9	53	1724	101	28.0	Villarreal	96.12	71.68	FirstPeriodOfExtraTime	Pass	Unsuccessful	5.0	116.88	50.52	39.672116	10.972912	True
10	54	1728	102	11.0	Villarreal	119.40	0.40	FirstPeriodOfExtraTime	Pass	Unsuccessful	5.0	110.52	55.68	39.604545	18.323013	True
11	57	1838	107	56.0	Villarreal	80.52	20.40	SecondPeriodOfExtraTime	Pass	Unsuccessful	5.0	112.08	68.40	44.077550	29.483663	True

In [4]:

df = df.loc[df['teamId']=='Villarreal']

In [6]:

df = df.loc[df['type']=='Pass']

In [19]:

df = df.loc[df['playerId']==5.0].reset_index()

In [23]:

df = df.loc[df['progressive']==True].reset_index()

In [12]:

df.x = df.x*1.2
df.y = df.y*.8
df.endX = df.endX*1.2
df.endY = df.endY*1.2

In [21]:

df['beginning'] = np.sqrt(np.square(120-df['x']) + np.square(40 - df['y']))
df['end'] = np.sqrt(np.square(120 - df['endX']) + np.square(40 - df['endY']))

df['progressive'] = [(df['end'][x]) / (df['beginning'][x]) < .75 for x in range(len(df.beginning))]

In [28]:

pitch = Pitch(pitch_type='statsbomb')
fig,ax = pitch.draw()

pitch.lines(df.x,df.y,df.endX,df.endY,comet=True,ax=ax)

Out[28]:

<matplotlib.collections.LineCollection at 0x11d709790>

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