LFC Data Analysis: The Elite Strikers¶

See Terry's blog LFC: The Elite Strikers for a discussion of of the data analysis.

This notebook analyses Liverpool FC's elite strikers data from 1962-1963 to 2014-2015. An elite striker is defined as a player who scored 20 or more league goals in a season. I've started the analysis at 1962 as this was when Bill Shankly returned Liverpool to the top flight of English football. The analysis uses IPython Notebook, python, pandas and matplotlib to explore the data.

Notebook Change Log¶

In [1]:

%%html
<! left align the change log table in next cell >
<style>
table {float:left}
</style>

Date	Change Description
23rd July 2015	Initial baseline

Set-up¶

Import the modules needed for the analysis.

In [2]:

import pandas as pd
import matplotlib as mpl
import matplotlib.pyplot as plt
import numpy as np
import sys
import collections
from datetime import datetime
from __future__ import division

# enable inline plotting
%matplotlib inline

Print version numbers.

In [3]:

print 'python version: {}'.format(sys.version)
print 'pandas version: {}'.format(pd.__version__)
print 'matplotlib version: {}'.format(mpl.__version__)
print 'numpy version: {}'.format(np.__version__)

python version: 2.7.8 |Anaconda 2.3.0 (64-bit)| (default, Jul  2 2014, 15:12:11) [MSC v.1500 64 bit (AMD64)]
pandas version: 0.16.2
matplotlib version: 1.4.3
numpy version: 1.9.2

Load the LFC data into a dataframes and munge¶

Create dataframe of scorers in top level seasons¶

In [4]:

LFC_SCORERS_CSV_FILE = 'data\lfc_scorers_1892-1893_2014-2015.csv'
dflfc_scorers = pd.read_csv(LFC_SCORERS_CSV_FILE)

# sort by season, then league goals
dflfc_scorers = dflfc_scorers.sort(['season', 'league'], ascending=([False, False]))
dflfc_scorers.shape

Out[4]:

(1398, 3)

In [5]:

dflfc_scorers.head()

Out[5]:

	season	player	league
1382	2014-2015	Steven Gerrard	9
1383	2014-2015	Raheem Sterling	7
1385	2014-2015	Jordan Henderson	6
1384	2014-2015	Philippe Coutinho	5
1386	2014-2015	Adam Lallana	5

In [6]:

dflfc_scorers.tail()

Out[6]:

	season	player	league
5	1892-1893	Jonathan Cameron	4
6	1892-1893	Jim McBride	4
7	1892-1893	Hugh McQueen	3
9	1892-1893	Joe McQue	2
8	1892-1893	Own goals	1

In [7]:

# note that scorers includes own goals
dflfc_scorers[dflfc_scorers.player == 'Own goals'].head()

Out[7]:

	season	player	league
1388	2014-2015	Own goals	4
1374	2013-2014	Own goals	5
1356	2012-2013	Own goals	4
1343	2011-2012	Own goals	5
1334	2010-2011	Own goals	1

In [8]:

# note: war years already excluded
LANCS_YRS = ['1892-1893']
SECOND_DIV_YRS = ['1893-1894', '1895-1896', '1904-1905', '1961-1962', 
                  '1954-1955', '1955-1956', '1956-1957', '1957-1958', 
                  '1958-1959', '1959-1960', '1960-1961']

NOT_TOP_LEVEL_YRS = LANCS_YRS + SECOND_DIV_YRS
dflfc_scorers_tl = dflfc_scorers[~dflfc_scorers.season.isin(NOT_TOP_LEVEL_YRS)].copy()
dflfc_scorers_tl.shape

Out[8]:

(1250, 3)

In [9]:

## check number of seasons aligns with http://www.lfchistory.net/Stats/LeagueOverall.aspx
## expect 100 total
print 'num seasons is {}'.format(len(dflfc_scorers_tl.season.unique()))

num seasons is 100

In [10]:

# show most league goals in a season in top level
# cross-check with http://en.wikipedia.org/wiki/List_of_Liverpool_F.C._records_and_statistics#Goalscorers
# expect 101 in 2013-14
dflfc_scorers_tl[['season', 'league']].groupby(['season']).sum().sort('league', ascending=False).head(1)

Out[10]:

	league
season
2013-2014	101

In [11]:

# remove OG
dflfc_scorers_tl = dflfc_scorers_tl[dflfc_scorers_tl.player != 'Own goals']
dflfc_scorers_tl.shape

Out[11]:

(1181, 3)

In [12]:

# check 2013-14
dflfc_scorers_tl[dflfc_scorers_tl.season == '2013-2014'].head(10)

Out[12]:

	season	player	league
1369	2013-2014	Luis Suarez	31
1370	2013-2014	Daniel Sturridge	21
1371	2013-2014	Steven Gerrard	13
1372	2013-2014	Raheem Sterling	9
1373	2013-2014	Martin Skrtel	7
1375	2013-2014	Philippe Coutinho	5
1376	2013-2014	Jordan Henderson	4
1378	2013-2014	Daniel Agger	2
1377	2013-2014	Victor Moses	1
1379	2013-2014	Joe Allen	1

Create dataframe of squads giving age of each player¶

In [13]:

LFC_SQUADS_CSV_FILE = 'data/lfc_squads_1892-1893_2014-2015.csv'
dflfc_squads = pd.read_csv(LFC_SQUADS_CSV_FILE)
dflfc_squads.shape

Out[13]:

(2902, 3)

In [14]:

dflfc_squads.head()

Out[14]:

	season	player	position
0	1892-1893	Sydney Ross	Goalkeeper
1	1892-1893	Billy McOwen	Goalkeeper
2	1892-1893	Jim McBride	Defender
3	1892-1893	John McCartney	Defender
4	1892-1893	Andrew Hannah	Defender

In [15]:

dflfc_squads.tail()

Out[15]:

	season	player	position
2897	2014-2015	Kristoffer Peterson	Striker
2898	2014-2015	Suso	Striker
2899	2014-2015	Mario Balotelli	Striker
2900	2014-2015	Fabio Borini	Striker
2901	2014-2015	Jerome Sinclair	Striker

Create dataframe of league tables¶

In [16]:

LFC_LEAGUE_CSV_FILE = 'data/lfc_league_1892-1893_2014-2015.csv'
dflfc_league = pd.read_csv(LFC_LEAGUE_CSV_FILE)
dflfc_league.shape

Out[16]:

(112, 18)

In [17]:

dflfc_league.head()

Out[17]:

	Season	League	Pos	PLD	HW	HD	HL	HF	HA	AW	AD	AL	AF	AA	PTS	GF	GA	GD
0	1893-1894	2nd Division	1	28	14	0	0	46	6	8	6	0	31	12	50	77	18	59
1	1894-1895	1st Division	15	30	6	4	5	38	28	1	4	10	13	42	22	51	70	-19
2	1895-1896	2nd Division	1	30	14	1	0	65	11	8	1	6	41	21	46	106	32	74
3	1896-1897	1st Division	5	30	7	6	2	25	10	5	3	7	21	28	33	46	38	8
4	1897-1898	1st Division	9	30	7	4	4	27	16	4	2	9	21	29	28	48	45	3

In [18]:

dflfc_league.tail()

Out[18]:

	Season	League	Pos	PLD	HW	HD	HL	HF	HA	AW	AD	AL	AF	AA	PTS	GF	GA	GD
107	2010-2011	Premier League	6	38	12	4	3	37	14	5	3	11	22	30	58	59	44	15
108	2011-2012	Premier League	8	38	6	9	4	24	16	8	1	10	23	24	52	47	40	7
109	2012-2013	Premier League	7	38	9	6	4	33	16	7	7	5	38	27	61	71	43	28
110	2013-2014	Premier League	2	38	16	1	2	53	18	10	5	4	48	32	84	101	50	51
111	2014-2015	Premier League	6	38	10	5	4	30	20	8	3	8	22	28	62	52	48	4

Create merged dataframe, combining scorers with position¶

In [19]:

dflfc_scorers_tl_pos = pd.DataFrame.merge(dflfc_scorers_tl, dflfc_squads)
dflfc_scorers_tl_pos.shape

Out[19]:

(1181, 4)

In [20]:

dflfc_scorers_tl_pos.head()

Out[20]:

	season	player	league	position
0	2014-2015	Steven Gerrard	9	Midfielder
1	2014-2015	Raheem Sterling	7	Midfielder
2	2014-2015	Jordan Henderson	6	Midfielder
3	2014-2015	Philippe Coutinho	5	Midfielder
4	2014-2015	Adam Lallana	5	Midfielder

In [21]:

dflfc_scorers_tl_pos.tail()

Out[21]:

	season	player	league	position
1176	1894-1895	Frank Becton	4	Striker
1177	1894-1895	Neil Kerr	3	Midfielder
1178	1894-1895	Hugh McQueen	2	Midfielder
1179	1894-1895	Joe McQue	1	Defender
1180	1894-1895	Patrick Gordon	1	Midfielder

Create dataframe of players giving birthdate of each player¶

In [22]:

LFC_PLAYERS_CSV_FILE = 'data\lfc_players_july2015_upd.csv' 
dflfc_players = pd.read_csv(LFC_PLAYERS_CSV_FILE, parse_dates=['birthdate'])
dflfc_players.shape

Out[22]:

(748, 3)

In [23]:

dflfc_players.head()

Out[23]:

	player	birthdate	country
0	Gary Ablett	1965-11-19	England
1	Alan A'Court	1934-09-30	England
2	Charlie Adam	1985-12-10	Scotland
3	Daniel Agger	1984-12-12	Denmark
4	Andrew Aitken	1909-08-25	England

In [24]:

dflfc_players.tail()

Out[24]:

	player	birthdate	country
743	Ron Yeats	1937-11-15	Scotland
744	Samed Yesil	1994-05-25	Germany
745	Tommy Younger	1930-04-10	Scotland
746	Bolo Zenden	1976-08-15	Netherlands
747	Christian Ziege	1972-02-01	Germany

Add players age to the dataframe¶

In [25]:

def age_at_season(row):
    """Return player's age at mid-point of season, assumed to be 1st Jan.
    
        row.player -> player's name
        row.season -> season
        
        uses dflfc_players to look-up birthdate, keyed on player
         - return average age if player is missing from dflfc_players
    """
    
    AVERAGE_AGE = 26.5
    
    mid_point = '01 January {}'.format(row.season[-4:])
    try:
        dob = dflfc_players[dflfc_players.player == row.player].birthdate.values[0]
    except:
        # use average age if player's birthdate not available
        print 'error: age not found for player {} in season {}, using average age {}'.format(row.player, 
                                                                                             row.season, 
                                                                                             AVERAGE_AGE)
        return AVERAGE_AGE
    return round((pd.Timestamp(mid_point) - dob).days/365.0, 1)

In [26]:

# add age column
dflfc_scorers_tl_pos['age'] = dflfc_scorers_tl_pos.apply(lambda row: age_at_season(row), axis=1)

error: age not found for player William Walker in season 1897-1898, using average age 26.5

In [27]:

dflfc_scorers_tl_pos_age = dflfc_scorers_tl_pos.copy()

In [28]:

dflfc_scorers_tl_pos_age.head()

Out[28]:

	season	player	league	position	age
0	2014-2015	Steven Gerrard	9	Midfielder	34.6
1	2014-2015	Raheem Sterling	7	Midfielder	20.1
2	2014-2015	Jordan Henderson	6	Midfielder	24.6
3	2014-2015	Philippe Coutinho	5	Midfielder	22.6
4	2014-2015	Adam Lallana	5	Midfielder	26.7

Analyse the data¶

Ask a question and find the answer.

In [29]:

# check number of seasons in top flight between 1960 and 2014 (expect 53)
tf = dflfc_scorers_tl_pos_age[(dflfc_scorers_tl_pos_age.season.str[0:4] >= '1960') &
                             (dflfc_scorers_tl_pos_age.season.str[0:4] <= '2014')].season.unique()
tf[-1], tf[0], len(tf)

Out[29]:

('1962-1963', '2014-2015', 53)

In [30]:

# show modern scorers who scored >20, with age - aka elite strikers
dflfc_elite = dflfc_scorers_tl_pos_age[(dflfc_scorers_tl_pos_age.season.str[0:4] >= '1962') & 
                                       (dflfc_scorers_tl_pos_age.league >= 20)].sort('league', ascending=False)
dflfc_elite.reset_index(drop=True, inplace=True)
dflfc_elite

Out[30]:

	season	player	league	position	age
0	1983-1984	Ian Rush	32	Striker	22.2
1	1963-1964	Roger Hunt	31	Striker	25.5
2	2013-2014	Luis Suarez	31	Striker	27.0
3	1986-1987	Ian Rush	30	Striker	25.2
4	1965-1966	Roger Hunt	29	Striker	27.5
5	1995-1996	Robbie Fowler	28	Striker	20.7
6	1987-1988	John Aldridge	26	Striker	29.3
7	1994-1995	Robbie Fowler	25	Striker	19.7
8	1964-1965	Roger Hunt	25	Striker	26.5
9	1967-1968	Roger Hunt	25	Striker	29.5
10	2007-2008	Fernando Torres	24	Striker	23.8
11	1982-1983	Ian Rush	24	Striker	21.2
12	1962-1963	Roger Hunt	24	Striker	24.5
13	2012-2013	Luis Suarez	23	Striker	26.0
14	1985-1986	Ian Rush	22	Striker	24.2
15	1989-1990	John Barnes	22	Striker	26.2
16	2013-2014	Daniel Sturridge	21	Striker	24.4
17	1979-1980	David Johnson	21	Striker	28.2
18	1978-1979	Kenny Dalglish	21	Striker	27.8
19	1988-1989	John Aldridge	21	Striker	30.3
20	1963-1964	Ian St John	21	Striker	25.6
21	1977-1978	Kenny Dalglish	20	Striker	26.8

In [31]:

# show near misses - modern scorers who scored >=18 and <=19, with age
dflfc_scorers_tl_pos_age[(dflfc_scorers_tl_pos_age.season.str[0:4] >= '1962') & 
                         (dflfc_scorers_tl_pos_age.league >= 18) &
                         (dflfc_scorers_tl_pos_age.league <= 19)].sort('league', ascending=False)

Out[31]:

	season	player	league	position	age
159	2002-2003	Michael Owen	19	Striker	23.1
169	2001-2002	Michael Owen	19	Striker	22.1
648	1962-1963	Ian St John	19	Striker	24.6
68	2009-2010	Fernando Torres	18	Striker	25.8
210	1998-1999	Michael Owen	18	Striker	19.1
222	1997-1998	Michael Owen	18	Striker	18.1
233	1996-1997	Robbie Fowler	18	Striker	21.7
320	1989-1990	Ian Rush	18	Striker	28.2
376	1984-1985	John Wark	18	Midfielder	27.4
401	1982-1983	Kenny Dalglish	18	Midfielder	31.9

In [32]:

# show number of games played in seasons when strikers scored >20
dflfc_league[['Season', 'League', 'Pos', 'PLD']][dflfc_league.Season.isin(dflfc_elite.season)]

Out[32]:

	Season	League	Pos	PLD
59	1962-1963	1st Division	8	42
60	1963-1964	1st Division	1	42
61	1964-1965	1st Division	7	42
62	1965-1966	1st Division	1	42
64	1967-1968	1st Division	3	42
74	1977-1978	1st Division	2	42
75	1978-1979	1st Division	1	42
76	1979-1980	1st Division	1	42
79	1982-1983	1st Division	1	42
80	1983-1984	1st Division	1	42
82	1985-1986	1st Division	1	42
83	1986-1987	1st Division	2	42
84	1987-1988	1st Division	1	40
85	1988-1989	1st Division	2	38
86	1989-1990	1st Division	1	38
91	1994-1995	Premier League	4	42
92	1995-1996	Premier League	3	38
104	2007-2008	Premier League	4	38
109	2012-2013	Premier League	7	38
110	2013-2014	Premier League	2	38

In [33]:

# show strikers with total scored >20
df_striker_tot = dflfc_elite[['player', 'league']].groupby('player').sum()
df_striker_tot.rename(columns={'league': 'Tot'}, inplace=True)
df_striker_tot.index.name = 'Player'
df_striker_tot.sort('Tot', ascending=False).head()

Out[33]:

	Tot
Player
Roger Hunt	134
Ian Rush	108
Luis Suarez	54
Robbie Fowler	53
John Aldridge	47

In [34]:

# show number of elite strikers who scored >20
len(dflfc_elite)

Out[34]:

In [35]:

# show number of unique strikers who scored >20
top20_lu = dflfc_elite.sort('league', ascending=False).player.unique()
print len(top20_lu)
print top20_lu

11
['Ian Rush' 'Roger Hunt' 'Luis Suarez' 'Robbie Fowler' 'John Aldridge'
 'Fernando Torres' 'John Barnes' 'Daniel Sturridge' 'David Johnson'
 'Kenny Dalglish' 'Ian St John']

In [36]:

# show number of unique scorers who scored >20 - pretty print
player_d = collections.defaultdict(list)
top20_l = dflfc_elite.sort('league', ascending=False).values
for season, player, goals, position, age, in top20_l:
    # season, player, goals, age
    player_d[player].append('{} ({})'.format(season, goals))

for k,v in player_d.iteritems():
    print '{}: {}'.format(k, ', '.join(v))

Daniel Sturridge: 2013-2014 (21)
Roger Hunt: 1963-1964 (31), 1965-1966 (29), 1964-1965 (25), 1967-1968 (25), 1962-1963 (24)
Fernando Torres: 2007-2008 (24)
Luis Suarez: 2013-2014 (31), 2012-2013 (23)
John Barnes: 1989-1990 (22)
Ian Rush: 1983-1984 (32), 1986-1987 (30), 1982-1983 (24), 1985-1986 (22)
David Johnson: 1979-1980 (21)
Kenny Dalglish: 1978-1979 (21), 1977-1978 (20)
Robbie Fowler: 1995-1996 (28), 1994-1995 (25)
John Aldridge: 1987-1988 (26), 1988-1989 (21)
Ian St John: 1963-1964 (21)

In [37]:

# construct table (dataframe) to summarise the data

# col 0 of dataframe is the list of season (goals) converted to a comma separated string
df = pd.DataFrame.from_dict({k: ', '.join(v) for k,v in player_d.iteritems()}, orient='index')

# col 1 is number of times player has scored 20+ (derived from number of brackets)
df[1] = df[0].apply(lambda x: x.count('('))

# change column order and rename
df = df[[1, 0]]
df.rename(columns={1: 'Times 20+ Achieved', 
                   0: 'Seasons in which player scored 20+ goals (with number of league goals scored)'}, inplace=True)
df.index.name = 'Player'

# add total (sum of goals in brackets)
df = df.merge(df_striker_tot, left_index=True, right_index=True)

# set pandas option that avoids the default curtailing of long rows with ...
pd.set_option('display.max_colwidth', -1)

# show dataframe sorted by number of times achieved
df = df.sort(['Times 20+ Achieved', 'Tot'], ascending=(False, False))
df[['Times 20+ Achieved', 'Seasons in which player scored 20+ goals (with number of league goals scored)']]

Out[37]:

	Times 20+ Achieved	Seasons in which player scored 20+ goals (with number of league goals scored)
Player
Roger Hunt	5	1963-1964 (31), 1965-1966 (29), 1964-1965 (25), 1967-1968 (25), 1962-1963 (24)
Ian Rush	4	1983-1984 (32), 1986-1987 (30), 1982-1983 (24), 1985-1986 (22)
Luis Suarez	2	2013-2014 (31), 2012-2013 (23)
Robbie Fowler	2	1995-1996 (28), 1994-1995 (25)
John Aldridge	2	1987-1988 (26), 1988-1989 (21)
Kenny Dalglish	2	1978-1979 (21), 1977-1978 (20)
Fernando Torres	1	2007-2008 (24)
John Barnes	1	1989-1990 (22)
Daniel Sturridge	1	2013-2014 (21)
David Johnson	1	1979-1980 (21)
Ian St John	1	1963-1964 (21)

In [38]:

# show youngest elite scorers who scored >20
dflfc_elite.sort('league', ascending=False).sort('age').head(5)

Out[38]:

	season	player	league	position	age
7	1994-1995	Robbie Fowler	25	Striker	19.7
5	1995-1996	Robbie Fowler	28	Striker	20.7
11	1982-1983	Ian Rush	24	Striker	21.2
0	1983-1984	Ian Rush	32	Striker	22.2
10	2007-2008	Fernando Torres	24	Striker	23.8

In [39]:

# check to see if anyone has matched Robbie's feat...
# show youngest elite scorers who scored >20 for ALL seasons
dflfc_scorers_tl_pos_age[(dflfc_scorers_tl_pos_age.league >= 20)].sort('league', ascending=False).sort('age').head(5)

Out[39]:

	season	player	league	position	age
256	1994-1995	Robbie Fowler	25	Striker	19.7
246	1995-1996	Robbie Fowler	28	Striker	20.7
400	1982-1983	Ian Rush	24	Striker	21.2
388	1983-1984	Ian Rush	32	Striker	22.2
968	1914-1915	Fred Pagnam	24	Striker	23.3

No, only God has done that!

In [40]:

# show oldest elite scorers who scored >20
dflfc_elite.sort('league', ascending=False).sort('age').tail(5)

Out[40]:

	season	player	league	position	age
18	1978-1979	Kenny Dalglish	21	Striker	27.8
17	1979-1980	David Johnson	21	Striker	28.2
6	1987-1988	John Aldridge	26	Striker	29.3
9	1967-1968	Roger Hunt	25	Striker	29.5
19	1988-1989	John Aldridge	21	Striker	30.3

In [41]:

# show most appearances of elite strikers who scored >20
dflfc_elite.sort('league', ascending=False).player.value_counts()

Out[41]:

Roger Hunt          5
Ian Rush            4
John Aldridge       2
Robbie Fowler       2
Luis Suarez         2
Kenny Dalglish      2
Ian St John         1
Fernando Torres     1
Daniel Sturridge    1
David Johnson       1
John Barnes         1
dtype: int64

In [42]:

# show average (mean) age of elite strikers who scored >20
dflfc_elite.sort('league', ascending=False).mean()

Out[42]:

league    24.818182
age       25.550000
dtype: float64

In [43]:

# show average (median) age of elite strikers who scored >20
dflfc_elite.sort('league', ascending=False).median()

Out[43]:

league    24.0
age       25.8
dtype: float64

In [44]:

# show most appearances of elite strikers who scored >20 for ALL seasons
dflfc_scorers_tl_pos_age[(dflfc_scorers_tl_pos_age.league >= 20)].sort('league', ascending=False).player.value_counts()

Out[44]:

Gordon Hodgson      7
Roger Hunt          5
Ian Rush            4
Joe Hewitt          2
John Aldridge       2
Harry Chambers      2
Kenny Dalglish      2
Albert Stubbins     2
Robbie Fowler       2
Luis Suarez         2
Dick Forshaw        1
David Johnson       1
Daniel Sturridge    1
Jimmy Smith         1
Ian St John         1
John Barnes         1
Fred Pagnam         1
Sam Raybould        1
Jack Balmer         1
Ronald Orr          1
Fernando Torres     1
Jack Parkinson      1
dtype: int64

In [45]:

# show most appearances of elite strikers who scored >25 for ALL seasons
dflfc_scorers_tl_pos_age[(dflfc_scorers_tl_pos_age.league >= 25)].sort('league', ascending=False).player.value_counts()

Out[45]:

Gordon Hodgson    4
Roger Hunt        4
Ian Rush          2
Robbie Fowler     2
Dick Forshaw      1
Luis Suarez       1
John Aldridge     1
Sam Raybould      1
Jack Parkinson    1
dtype: int64

In [46]:

# show frequency of elite scorers who scored >20
top20_freq = dflfc_elite['player'].groupby(dflfc_elite.season).count()
top20_freq

Out[46]:

season
1962-1963    1
1963-1964    2
1964-1965    1
1965-1966    1
1967-1968    1
1977-1978    1
1978-1979    1
1979-1980    1
1982-1983    1
1983-1984    1
1985-1986    1
1986-1987    1
1987-1988    1
1988-1989    1
1989-1990    1
1994-1995    1
1995-1996    1
2007-2008    1
2012-2013    1
2013-2014    2
Name: player, dtype: int64

In [47]:

# produce list of all modern seasons (since 1962)
START_MOD_YR = 1962
END_MOD_YR = 2015
all_mod_yrs = list('{}-{}'.format(i, i+1) for i in range(START_MOD_YR, END_MOD_YR))
print len(all_mod_yrs) # expect 53
all_mod_yrs[0:5]

Out[47]:

['1962-1963', '1963-1964', '1964-1965', '1965-1966', '1966-1967']

In [48]:

# identify missing years and update frequency so it shows all years 
missing_mod_years = [year for year in all_mod_yrs if year not in top20_freq.index.values]
for yr in missing_mod_years:
    top20_freq[yr] = 0
top20_freq = top20_freq.sort_index()
top20_freq[0:5]

Out[48]:

season
1962-1963    1
1963-1964    2
1964-1965    1
1965-1966    1
1966-1967    0
Name: player, dtype: int64

In [49]:

# create list of seasons when LFC were champions
CHAMPS = ['1900-1901', '1905-1906', '1921-1922', '1922-1923', '1946-1947', '1963-1964',\
          '1965-1966', '1972-1973', '1975-1976', '1976-1977', '1978-1979', '1979-1980',\
          '1981-1982', '1982-1983', '1983-1984', '1985-1986', '1987-1988', '1989-1990']
CHAMPS[0:5]

Out[49]:

['1900-1901', '1905-1906', '1921-1922', '1922-1923', '1946-1947']

Plot the number of players scoring 20 or more goals by season

In [50]:

ax = top20_freq.plot(kind='bar', figsize=(14, 5), color='y', yticks=[0, 1, 2], ylim=(0,2.5), grid=False)
ax.set_xlabel('Season')
ax.set_ylabel('Number of players')
ax.set_title('Number of players scoring 20 or more goals by Season')
ax.text(-0.2, 2.36, 'prepared by: @terry8dolan', bbox=dict(facecolor='none', edgecolor='none', alpha=0.6))

# add vertical line for title winning seasons since 1962
champs_since_62 = [list(top20_freq.index.values).index(yr) for yr in CHAMPS if yr[0:4] >= '1962']
for x in champs_since_62:
    plt.axvline(x, color='r', linestyle='--')
    
# create fake legend
l1 = plt.Line2D([], [], linewidth=1, color='r', linestyle='--')
l2 = plt.Line2D([], [], linewidth=5, color='y')
labels = ['LFC Title Winning Seasons', 'Players scoring 20+ goals in the league']
ax.legend([l1, l2], labels, fancybox=True, shadow=True, framealpha=0.8)

# plot and save current figure
fig = plt.gcf() 
plt.show()
fig.savefig('20+PlayervsGoals.png', bbox_inches='tight')

Show percentage of title winning seasons that have had striker with >20 goals

In [51]:

# create a dataframe showing position in league in top flight season since 1962
dflfc_league_pos = dflfc_league[['Season', 'Pos']][dflfc_league.Season.str[0:4] >= '1962']
dflfc_league_pos.rename(columns={'Season': 'season', 'Pos': 'pos'}, inplace=True)
dflfc_league_pos.head()

Out[51]:

	season	pos
59	1962-1963	8
60	1963-1964	1
61	1964-1965	7
62	1965-1966	1
63	1966-1967	5

In [52]:

# create dataframe showing position in league when players have scored >20
top20_seasons = dflfc_elite.season.unique()
dflfc_elite_pos = dflfc_league_pos[dflfc_league_pos.season.isin(top20_seasons)]
dflfc_elite_pos.head()

Out[52]:

	season	pos
59	1962-1963	8
60	1963-1964	1
61	1964-1965	7
62	1965-1966	1
64	1967-1968	3

In [53]:

# show position in league when players have scored >20
val_cnts = dflfc_league_pos[['season', 'pos']][dflfc_league_pos.season.isin(top20_seasons)]['pos'].value_counts()
val_cnts

Out[53]:

1    9
2    4
7    2
4    2
3    2
8    1
dtype: int64

In [54]:

# show % of title winning seasons that have had striker with >20 goals
tot_champs_since_62 = len(dflfc_league_pos[(dflfc_league_pos.pos == 1)])
tot_elite_champs = len(dflfc_elite_pos[(dflfc_elite_pos.pos == 1)])
print '{} of {} ({}%) of title winning seasons have had striker with >20 goals'\
                        .format(tot_elite_champs,
                                tot_champs_since_62,
                                round(100*tot_elite_champs/tot_champs_since_62, 1))

9 of 13 (69.2%) of title winning seasons have had striker with >20 goals

In [55]:

# show the 4 title winning seasons since 1962 that didn't have an elite scorer
dflfc_scorers_tl_pos_age[(dflfc_scorers_tl_pos_age.season.str[0:4] >= '1962') & 
                        (dflfc_scorers_tl_pos_age.season.isin(CHAMPS))].sort(['season', 'league'], ascending=[True, False])\
                        .groupby(dflfc_scorers_tl_pos_age.season).head(1).sort('league').head(4)

Out[55]:

	season	player	league	position	age
472	1976-1977	Kevin Keegan	12	Striker	25.9
522	1972-1973	Kevin Keegan	13	Striker	21.9
485	1975-1976	John Toshack	16	Striker	26.8
411	1981-1982	Ian Rush	17	Striker	20.2

In [56]:

# show top goalscorers in modern seasons when Liverpool won the league without a striker scoring >20
s = ['1976-1977', '1972-1973', '1975-1976', '1981-1982']
dflfc_scorers_tl_pos_age[dflfc_scorers_tl_pos_age.season.isin(s)].groupby('season').head(3)

Out[56]:

	season	player	league	position	age
411	1981-1982	Ian Rush	17	Striker	20.2
412	1981-1982	Terry McDermott	14	Midfielder	30.1
413	1981-1982	Kenny Dalglish	13	Striker	30.9
472	1976-1977	Kevin Keegan	12	Striker	25.9
473	1976-1977	John Toshack	10	Striker	27.8
474	1976-1977	Steve Heighway	8	Midfielder	29.1
485	1975-1976	John Toshack	16	Striker	26.8
486	1975-1976	Kevin Keegan	12	Striker	24.9
487	1975-1976	David Fairclough	7	Striker	19.0
522	1972-1973	Kevin Keegan	13	Striker	21.9
523	1972-1973	John Toshack	13	Striker	23.8
524	1972-1973	Peter Cormack	8	Midfielder	26.5

Show distribution of strikers with more than 20 goals by age

In [57]:

# create 'cut' of value counts
pd.value_counts(pd.cut(dflfc_elite.age.values, range(19,32)))

Out[57]:

(26, 27]    4
(25, 26]    4
(24, 25]    3
(29, 30]    2
(27, 28]    2
(30, 31]    1
(28, 29]    1
(23, 24]    1
(22, 23]    1
(21, 22]    1
(20, 21]    1
(19, 20]    1
dtype: int64

In [58]:

# create dataframe of value counts of age cut into 1 year bins from 19 to 31
MIN_AGE = int(np.floor(dflfc_elite.age.min()))
MAX_AGE = int(np.ceil(dflfc_elite.age.max()))

df = pd.DataFrame(pd.value_counts(pd.cut(dflfc_elite.age.values, 
                                         range(MIN_AGE, MAX_AGE+1), 
                                         labels=['{} to {}'.format(i, i+1) for i in range(MIN_AGE, MAX_AGE)])))
df.sort_index(inplace=True)
df

Out[58]:

	0
19 to 20	1
20 to 21	1
21 to 22	1
22 to 23	1
23 to 24	1
24 to 25	3
25 to 26	4
26 to 27	4
27 to 28	2
28 to 29	1
29 to 30	2
30 to 31	1

In [59]:

# plot
ax = df.plot(kind='bar', figsize=(9, 6), grid=False, ylim=(0, 4.5), yticks=range(1,5), legend=False, color='r')
ax.set_xlabel('Age')
ax.set_ylabel('Number of players')
ax.set_title('Number of players scoring 20 or more goals by Age')
ax.text(-0.4, 4.3, 'prepared by: @terry8dolan', bbox=dict(facecolor='none', edgecolor='none', alpha=0.6))

# plot and save current figure
fig = plt.gcf() 
plt.show()
fig.savefig('20+PlayervsAge.png', bbox_inches='tight')

In [ ]: