Heights and Weights of English Premier League …...English Premier League Height and Weight...

English Premier League Height and Weight Analysis Duncan Williamson December 2016 of 9

Heights and Weights of English Premier League Players

Duncan Williamson excelmaster.co

Introduction

I have played around with the heights and weights of professional footballers for many years and here we are again. This time I managed to get a larger database of players to work from than before:

http://www.footballsquads.co.uk/eng/2016-2017/faprem.htm Although I have only analysed the English Premier League (EPL) it is easy to find data on other English leagues and, indeed, from around the world. In summary, what I wanted to do was to

Find some data and clean it as appropriate

Create an overview of the data such as all heights v all weights and to create the regression equation

Set out descriptive statistics

Create some graphs

Do all of the above for o Individual clubs o By players’ nationality o By players’ position on the field

I was also interested in sharing my methods since there are some things that people are doing with

their analysis and dashboards that are either overdesigned or are more difficult/complex than they ought to be. I use the very effective and efficient DATABASE functions, for example, while others will

use INDEX() and MATCH() or similar combinations.

By the way, I don’t really draw any firm conclusions about this topic since I think you

should draw your own conclusions and let the data speak to you! Similarly, I end this case by encouraging you to create your own dashboard out of my work and, of course,

any additional work you do yourself.

The Data

Using the link I gave in the introduction, I found the data I was looking for although I had to scrape

every page to get what I wanted. Still, I did get what I wanted, the heights and weights of 633 EPL players. The database I used contains 1,107 named players but the heights and weights are not

collected for everyone for some reason. In the database there is also a section showing some players

who are no longer at the club … I found it odd that they would provde these extra few players and ignored them: after all I would be double counting without a doubt in some cases if I did include

them.

The analysis concentrates on the 633 players for whom I got full data, therefore.

The following screenshot shows that data I used although you will see in the file that I have also left

in the columns containing dates of birth, birth place and previous club. In this version of this case, I have not done anything with dates of birth/ages: feel free to work on this by yourself!

http://www.footballsquads.co.uk/eng/2016-2017/faprem.htm


By sorting this table by Height, I was able to isolate all rows of data that did not contain any height

data: similarly with the weights column.

There are 75 nationalities represented in the EPL and I used that in Pivot Table Analysis to analyse maximum and average weights by club and by club and nationality:

In Full

Showing English Players Only

Team Number Name Nat Pos Height Weight

Southampton 1 Fraser Forster ENG G 2.01 93

Stoke City 25 Peter Crouch ENG F 2.01 80

Chelsea 13 Thibaut Courtois BEL G 1.99 88

Stoke City 54 Harry Souttar SCO D 1.98 80

Arsenal 54 Matt Macey ENG G 1.98 81

Arsenal 4 Per Mertesacker GER D 1.98 90

Chelsea 1 Asmir Begović BIH G 1.98 84

Watford 30 Costel Pantilimon ROU G 1.97 96

Crystal Palace 13 Wayne Hennessey WAL G 1.97 89

Everton 22 Maarten Stekelenburg NED G 1.97 92

1.651.7

1.751.8

1.851.9

1.952

2.05

Wei

ght

Heights: Club and (All)

Max Height Ave Height

Nat

MAR ALG ARG ARM AUS AUT BEL BIH BRA CAN CGO CHI CIV CMR COD COL CRC CRO CUW CZE DEN ECU

EGY ENG EQG ESP EST FIN FRA GAB GAM GER GHA GRE HUN IRL ISL ITA JAM JPN KEN KOR LTU MKD

MLI NED NGA NIR NOR NZL POL POR ROU RSA SCO SEN SRB SUI SVK SVN SWE TUN TUR URU USA VEN

WAL ZIM AFG BEN BER FIJ GNB LVA (bl...

0

20

40

60

80

100

120

Wei

ght

Weights: Club and (All)

Max Weight Ave Weight

1.651.7

1.751.8

1.851.9

1.952

2.05

Wei

ght

Heights: Club and ENG


Nat





0102030405060708090

100

Wei

ght

Weights: Club and ENG



Showing German Players Only

This German Only Graphic helps to illustrate that not every club has German players playing for them!

English, French, Spanish, German and Portuguese Players Only

Notice this is a graphics only analysis with no accompanying statistics.

Similarly, there is a pivot chart showing weights by club and by nationality: Burnley and English

players in this case

1.65

1.7

1.75

1.8

1.85

1.9

1.95

2

Arsenal Leicester City Liverpool ManchesterCity

ManchesterUnited

Sunderland Swansea

Wei

ght

Heights: Club and GER


Nat





0

10

20

30

40

50

60

70

80

90

100

Arsenal Leicester City Liverpool ManchesterCity

ManchesterUnited

Sunderland Swansea

Wei

ght

Weights: Club and GER


1.651.7

1.751.8

1.851.9

1.952

2.05

Wei

ght

Heights: Club and (Multiple Items)


Nat





0102030405060708090

100

Wei

ght

Weights: Club and (Multiple Items)


Nat ENG

Row Labels Max Weight Ave Weight Weights: Club and ENG

Burnley 90 76.77

Grand Total 90 76.77

Team

Arsenal Bournemouth

Burnley Chelsea

Crystal Palace Everton

Hull City Leicester City

Liverpool Manchester City

Manchester United Middlesbrough

Southampton Stoke City

Sunderland Swansea

Tottenham Hotspur Watford

West Bromwich Al... West Ham United

Nat

MAR ALG ARG ARM AUS AUT

BEL BIH BRA CAN CGO CHI

CIV CMR COD COL CRC CRO

CUW CZE DEN ECU EGY ENG

EQG ESP EST FIN FRA GAB

GAM GER GHA GRE HUN IRL

ISL ITA JAM JPN KEN KOR

LTU MKD MLI NED NGA NIR

NOR NZL POL POR ROU RSA

SCO SEN SRB SUI SVK SVN

SWE TUN TUR URU USA VEN

WAL ZIM AFG BEN BER FIJ

GNB LVA (bl...

70

75

80

85

90

95

Burnley

WE

IGH

T

Weights: Club and ENG



You can show any club, any nationality. You can combine two or more or all clubs and two or more of

all nationalities. Here is the screenshot for the graph showing everythng for weights:

There is an equivalent pivot chart for heights.

All Heights and Weights

All heights and weights with regression line and R2, which is 0.543 and which is quite high,

suggesting a good association between heights and weights.

The equation Y = 77.967X – 67.232 says that if we know a player’s height, we can predict his weight.

In this case, take Paul Robinson of Burnley: his height is 1.93 metres and according to the regression equation he ought to be 83.2443 kg in weight. In reality he is 90 kg.


Is the regression equation any good? Well, yes and no! No in that it is based on a sample of 633 EPL players and nothing else. Yes in that it gives us an idea of the kinds of height weight combinations

that an EPL player needs to fit into.

Descriptive Statistics

Descriptive statistics are a useful addition to any analysis and here they are for this case:

Anything special in these statistics? Look at Kurtosis ad Skewness. Very low values for Kurtosis tell us

that the frequency distributions are not so tall and whilst heights are slightly negatively skewed,

weights are positively skewed. Let’s look at the frequency distrubtions, in the form of histograms:

Firstly, the tables and then the histograms

Height Weight

Mean 1.8222 74.8515

Standard Error 0.0028 0.2929

Median 1.8300 75.0000

Mode 1.8000 70.0000

Standard Deviation 0.0697 7.3695

Sample Variance 0.0049 54.3102

Kurtosis (0.4044) (0.3065)

Skewness (0.0381) 0.2426

Range 0.3800 39.0000

Minimum 1.6300 57.0000

Maximum 2.0100 96.0000

Sum 1,157.1200 47,381.0000

Count 635 633


We already know from the statistics that these data sets are not normally distributed and now we can see what those Kurtosis and Skewness results are saying!

Detailed View of the Data

I also wanted to illustrate the data in these ways

By club

By nationality of player

By position of the player on the pitch

To achieve this ambition I used Combo Boxes together with the functions you see in the screenshot

that follows, for example:

Height Weight

Bin Freq Bin Freq

1.67 3 60.90 11

1.71 42 64.80 40

1.74 44 68.70 77

1.78 109 72.60 120

1.82 118 76.50 149

1.86 113 80.40 96

1.90 107 84.30 71

1.93 71 88.20 43

1.97 21 92.10 20

2.01 7 96.00 6

0 0


These functions relate only to Club and Height but they are very similar for Weight as well as for

nationality and position. See my file to prove that is true!

In the bove example we can see that I have hightlighted Burnley’s players, all 23 of them for which I have data, all English players in te EPL: 232 of them for which I have data and all Goalkeepers in the

EPL, 86 of them for which I have data.

All of that is fine but I wanted to tune my output even finer than that: I wanted, for example, to

show All English Goalkeepers who play for Burnley … or any club, any nationality, any position. I did it this way on the hts_wts (2) tab:

We can see there are three English goalkeepers playing for Burnley and their average height is 1.897 metres, their average weight is 83.667 Kg. We can also see the tallest and largest as well as shortest

and smallest goalkeepers at Burnley too. How did I do that? You will be surprised when you see that I did NOT use any INDEX() and MATCH() or similar construction to create that output. Here are my

formulas:

Maybe a bit difficult to read so go to the file and see them more clearly. However, in summary:

I linked to the Club shown by the Combo Box in cell R7 as well as the Nationality and Position Combo Boxes in cells U7 and X7.

By Club By Nationality By Position

3 23 1

Height Weight Height Weight Height Weight

Mean 1.83 75.83 Mean 1.81 73.13 Mean 1.90 82.40

Range 0.21 26 Range 0.36 38 Range 0.21 27

Minimum 1.72 64 Minimum 1.65 57 Minimum 1.8 69

Maximum 1.93 90 Maximum 2.01 95 Maximum 2.01 96

Count 23 23 Count 232 232 Count 86 86

Mean =AVERAGEIFS(G6:G640,B6:B640,VLOOKUP(R7,club,2,0))

Range =S13-S12

Minimum =MINIFS(G6:G640,B6:B640,VLOOKUP(R7,club,2,0))

Maximum =MAXIFS(G6:G640,B6:B640,VLOOKUP(R7,club,2,0))

Count =COUNTIFS(B6:B640,VLOOKUP(R7,club,2,0))

Team Nat Pos

Burnley ENG G

Average Maximum Minimum Range

Height 1.897 1.930 1.850 0.080

Weight 83.667 90.000 76.000 14.000

Count 3

Team Nat Pos

=VLOOKUP(R7,club,2,0) =VLOOKUP(U7,nat,2,0) =VLOOKUP(X7,pos,2,0)

Average Maximum Minimum Range

Height =IFERROR(DAVERAGE(B5:K640,"Height",AF22:AH23),"") =IFERROR(DMAX(B5:K640,"Height",AF22:AH23),"") =IFERROR(DMIN(B5:K640,"Height",AF22:AH23),"") =IFERROR(AI26-AJ26,"")

Weight =IFERROR(DAVERAGE(B5:K640,"Weight",AF22:AH23),"") =IFERROR(DMAX(B5:K640,"Weight",AF22:AH23),"") =IFERROR(DMIN(B5:K640,"Weight",AF22:AH23),"") =IFERROR(AI27-AJ27,"")

Count =IFERROR(DCOUNT(B5:K640,"Weight",AF22:AH23),"")


This function in AH26 =IFERROR(DAVERAGE(B5:K640,"Height",AF22:AH23),"") uses the DAVERAGE()

function to find the average height of the English Burnley Goalkeepers.

I used the DCOUNT() function in there too, in cell AH28

Heights v Weights by Club

Finally, I wanted to allow the user to look at the height v weight situation on a club by club basis and

to achieve that I used a slicer in combination with the Excel Table hts_wts_slicer in the hts_wts (3) tab. I have called it the club_graph tab:

I have used Burnley as the example here but how about Arsenal or Chelsea or Middlesbrough?

Arsenal Chelsea Middlesbrough

Do notice that there is a regression equation and R2 result on each graph and they change according to the Club chosen: they are based solely on the data for the Club on the graph.

You can combine the data for two or more clubs if you like:how about Burnley combined with Sunderland and Middlesbrough?

Conclusions

The purpose of this exercise was to put together an analysis of the heights and weights as well as

nationality and player position for players in the English Premier League. As I did that I wanted the user of the file I have created to be able to look at the data from the top down: the whole league and

y = 93.042x - 94.441

R² = 0.5648

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1.50 1.60 1.70 1.80 1.90 2.00

Height v Weight Team

Arsenal Bournemouth Burnley

Chelsea Crystal Palace Everton

Hull City Leicester City Liverpool

Manchester City Manchester United Middlesbrough

Southampton Stoke City Sunderland

Swansea Tottenham Hotspur Watford

West Bromwich A... West Ham United

y = 74.047x - 60.241

R² = 0.5261

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1.50 1.60 1.70 1.80 1.90 2.00

Height v Weight Team

Arsenal Bournemouth Burnley

Chelsea Crystal Palace Everton

Hull City Leicester City Liverpool

Manchester City Manchester United Middlesbrough

Southampton Stoke City Sunderland

Swansea Tottenham Hotspur Watford

West Bromwich A... West Ham United


from the bottom up: on a club by club basis. I also wanted to illustrate the functions and formulas I

used to alert you to DATABASE functions among others.

Finally, Finally: for you to do

Why not take what I have done and create a meaningful dashboard or dashboards from the various

graphs, tables and formulas I have created?

Duncan Williamson 29th December 2016

Heights and Weights of English Premier League …...English Premier League Height and Weight...

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