NIIT BUSINESS ANALYTICS

La Liga Performance Analysis Project

Analyzing the strategic formula for success in La Liga

Rituparna Sarkar

In this project we will try to explain the dependency of the win and loss for a team playing in La Liga (2013-2014) based on goals forwarded and accepted and carrying to forward to establish relation between shooting efficiency of a team to the goals scored. Then we will do a similar analysis for a home and away matches, try to establish the differences in different conditions.

Contents Introduction ........................................................................................................................................................................ 2

Objective ......................................................................................................................................................................... 2

Data source ..................................................................................................................................................................... 2

Analysis ............................................................................................................................................................................... 3

Data Preparation ............................................................................................................................................................. 3

Data Analysis ................................................................................................................................................................... 4

Conclusion ......................................................................................................................................................................... 11

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Introduction

Objective

The analysis will establish the following:

1) Relations of the goals forwarded by any teams to the number of matches won by them.

2) Relations of the goals accepted by any team to the number of matches won by the team.

3) Relation of the goals forwarded by any team to the number of matches lost by the team.

4) Relation of the goals accepted by any team to the number of matches lost by the team.

5) Relation of the number of goals scored by the team to the number of shots hit by the team.

6) Relation of the number of goals scored by the team to theshots on target hit by the team.

With the result of the above analysis, we will try to establish some suggestions that will help teams to improve their

performance in the upcoming season

Data source

http://www.football-data.co.uk/spainm.php

La Liga Primera Division (2013-2014)_original.csv

All the data use for this analysis are collected from the above website.

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Analysis

Data Preparation

The data contained match wise data for the session, to achieve our objective we need to transform the data into team-

wise data.

Steps followed to prepare the data,

1) Used “remove duplicate data” to find the unique team names

2) Used pivot table, to get the data for individual column and then copied each column data and performed a paste

(values).

The different combinations used are to produce these data columns.

3) The data hence produced was produced for Home and Away scenario, to produce the data for the complete

session a sum of the data for Home and Away has been taken.

4) Also to compute the efficiency of shots, a simple formula of (Shots on target/Total shots) has been used.

Our final datasheet

DataSet_La liga Analysis.xlsx

Keys for our data sheet

Goals_F – Goal Forwarded Goals_A – Goal Accepted Shot_OT- Shot On Target Shots Eff- shot Efficiency H_Win- Home Win H_Loss- Home Loss H_Draw- Home Draw H_Goals_F- Home Goals Forwarded H_Goals_A- Home Goals Accepted H_shots- Home Shot H_shots_OT- Home Shots On Target H_Shot_Eff- Home Shot Efficiency A_Win- Away Win A_Loss- Away Loss A_Draw- Away Draw A_Goals_F- Away Goals Forwarded A_Goals_A- Away Goals Accepted A_shots- Away Shot A_shots_OT- Away Shot On Target A_Shot_Eff- Away Shot Efficiency

11 20 28 276 14 9 11 11 12 12 12 10

27 18 16 13 7 13 1743

66 77100

3649

30 41 35 32 35 39 32

104

69 62 5138 46

60

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Total Win vs Total Goals Scores

Total Win Total Goals Scored

(3)Data Analysis

Primary Analysis

1) Relation between matches won vs the numbers of goals scored by the team

Data columns: Total win/ Total Goals Score

Line graph:

Conclusion:

As we can see from the line graph, the rise

and fall of the Blue line (Total Win) is very

much in sync with the rise and fall of the

Red line (Total Goals scored).

We can very well assume that a very strong

relation can exist between these 2

parameters.

Linear Regression:

Conclusion:

Based on the regression result, we can see that 86% of the Total Win can be explained by the Total Goals Scored in

the tournament. The significance F value also assures that the probability of error is very low.

So we can very well say that a team with a strong offence has performed better in La Liga.

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1120

28 27

614 9 11 11 12 12 12 10

2718 16 13

713 17

71

39

2633

78

54 50 51 54 56

43 46

62

38

52 55 5360

80

44

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Total win Vs Total Goals Accepted

Total Win Total Goals Accepted

2) Relation between matched won vs the number of goals accepted by the team

Data columns: Total win/Total Goals Accepted

Line Graph:

Conclusion:

As the line graph show, there is a

obvious inverse relation between the 2

parameters. We assume the 2

parameters are also related, but the

sync in rise and fall is not as strong as

the previous set of parameters. Linear

regression results will help us establish

the relation more firmly.

Linear Regression:

Conclusion:

As seen the value of R square suggests that the Total Win is not well explained by the Total goals accepted. With this

we can assume that most of the teams in La Liga stress on strong offence rather than defense. Even with high

number of goals accepted, some teams have performed better.

208 4 5

25 17 16 18 18 21 14 17 195 11 11 15 16 21 13

43

6677

100

3649

3041 35 32 35 39 32

104

69 6251

38 4660

Total Loss vs Total Goals Scored

Total Loss Total Goals Scored

3) Relation between matches loss vs the number of goals scored by the team.

Data columns: Total Loss /Total goal scored

Line graph:

Conclusion:

As seen, even these set of

parameters have a inverse

relation. But the relation is

assumed to be strong based on

the visual analysis of the line

graph. A linear regression will

help us establish the relation.

Linear Regression:

Conclusion:

Results of the linear regression show that 73% of the Total Loss can be explained by the Total goals score. This also helps

us believe that team with more goals have won more matches. Hence, we can say a team with strong offence has better

performed in La Liga.

208 4 5

2517 16 18 18 21

14 17 195 11 11 15 16 21

13

71

3926

33

78

54 50 51 54 5643 46

62

3852 55 53

60

80

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Total loss vs Total Goals Accepted

Total Loss Total Goals Accepted

4) Relation between matched loss vs the number of goals accepted by the team.

Data columns: Total Loss / Total goal scored

Line Graph:

Conclusion:

As seen, we can establish a strong

relation between the 2 parameters.

These parameters are directly related

to each other and a rise and fall of one

explains the rise and fall of the other.

The degree of relation will be

established by the linear regression.

Linear Regression:

Conclusion:

Linear regression confirms that the total number of losses can be explained by the total number os goals accepted bye

any team. However, the degree of strength of the relation was stronger in case of (Total Win vs Total Goals Scored),

thereby adding to the fact that teams stress on a strong offence in La Liga.

43 66 77 10036 49 30 41 35 32 35 39 32

104 69 62 51 38 46 60

397

510 503

643

501 494403 415 429 432

364

473 433

743

499 503 524

373

537436

Total Goals Vs Total Shots

Total Goals Scored Total Shots

5) Relation between goals scored vs number of shots

Data columns: Total Goals / Total Shot

Line Graph:

Conclusion:

A visual analysis of the line

graph shows that a relation

does exist between the 2

parameters but of a very

moderate strength. The degree

of rise in Red line is not very will

reflected in the blue line.

Linear Regression:

Conclusion:

Result of the linear regression shows a 70% relation between the 2 parameters. This can help is concluding that even

when the teams have very strong offence, the efficiency of the strategy is not as strong.

4366 77

100

36 49 30 41 35 32 35 39 32

10469 62 51 38 46 60

146189 202

266

162 171125 136 133 129 125

156134

301

163191 176

126176160

Total Goals Scored Vs Shots on target

Total Goals Scored Shots on target

6) Relation between goals scored vs shots on target

Data columns: Goals scored/ shots on target

Line graph:

Conclusion:

The relation between shots

on target gives us a better

reflection of the total goals

scored.

Linear Regression:

Conclusion:

The high value of R square (87%) explains that the goals scored strongly depends on the shots on target.

Combining the above results

The above analysis shows 2 very strong relations.

1) Total Win vs Total Goals

2) Total Goals scored vs Total Shots on target.

As we see, most of the above analysis suggests that teams in La Liga primarily focus on offence rather than defense.

1) Most of the wins are explained by the number of goals scored but not as strongly explained by the number of

goals accepted.

2) Matched lost by the team are equally explained by the total number of goals scored and goals accepted.

Also the later part of the analysis suggests that the teams although are strong in offence are not as efficient.

3) Total goals scored are explained better than shots on target than total shots

Supporting the above fact

1) Only 17 out of (38*20 = 760), i.e less than 3% matches have ended in no goals.

2) Only 100 out of (38*20 = 760), i.e. less than 14% of the matches have seen a team keeping clean sheet.

3) Even the best teams in the league have a maximum efficiency of 41% in shots, almost 60% of the shots are

wasted.

Assumes reasons why this kind of performance is observed

1) Teams use a formation which has less players in defensive position

2) Teams are lacking good defense players

3) Teams are doing more of the offense training

4) Defense teams are not motivated as much as the offensive team

5) Managers are buying offence players

6) Teams are dominated by individual performers

Conclusion

The following are the final set of suggestions for all teams in La Liga to upgrade their performance.

1) Increase defensive strength

a. Use formations with more people in defense.

b. Buy better defensive players in next transfer window.

c. Focus more on defense training.

d. Train players of have a neutral attitude rather than an offensive attitude in matches.

e. Give importance to the defense and motivate them to play more actively.

2) Increase efficiency of shots

a. Work on off the ball running to have a better positioning

b. Train team to efficiently convert the shots off target to shots on target

c. Suggest them to prefer possession of the ball rather than shots off target.

Adopting one or more of the above strategy is believed tohelp teams perform better in the upcoming seasons of the La

Liga.

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