BI/DA System in Football Club

This project examines the use of Business Intelligence (BI) and Data Analytics (DA) systems in Newcastle United Football Club to address the issue of inconsistent player salaries based on performance. It proposes a solution using BI/DA techniques, including an Excel dashboard and regression analysis, and provides recommendations for implementing a performance-based salary structure.

DEVELOPING GLOBAL
MANAGEMENT
COMPETENCIES I – BI
STRAND

Table of Contents
INTRODUCTION...........................................................................................................................1
1. Discussing around and presenting theoretical framework for problem/opportunity statement
by implementing BI (Business Intelligence)/ DA (Data Analytics) system...............................1
2. Evidencing knowledge of BI/DA system................................................................................2
3. Making critical analysis and justifying use of BI/DA system.................................................8
4. Conclusion and recommendation for BI/DA system in football club.....................................9
REFERENCES..............................................................................................................................12

INTRODUCTION
Football game is popular in the UK and Newcastle United Club is professional football
club founded in 1982. Period from 1904-1910 was the era quite successful for club as they have
won FA (Football Association) Cup in this period. While, it struggled over the years and it found
win in early 2000. It recently has won Premier League held in 2017-18. It shows that firm is able
to get desired wins in over the period and will attain more goals quite effectually in coming
seasons as well. Present report deals with problem being faced by the club currently which it
needs to resolve. The performances of players are crucial for winning matches and lift cup more
frequently through solid performance. It is facing problem about that players are not paid fees in
accordance to their performances.
High scorers are paid less and low scorers are offered higher salaries. For resolving this
issue, use and justification of Business Intelligence (BI)/ Data Analytics (DA) will be made.
Moreover, dashboard will be prepared for highlighting performances of players. SAS software
will be used for resolving issue and overall performance will get clarified. Furthermore,
recommendations will be given to avoid such problem and implementation of proper fees
structure will then be provided by management.
1. Discussing around and presenting theoretical framework for problem/opportunity statement by
implementing BI (Business Intelligence)/ DA (Data Analytics) system
Football is popular and quite famous game in the Europe and UK. The football players
are paid hefty amount which provides clarity that they are paid well and as a result, good play is
seen. It can be said that players should be paid in accordance to their performance so as to attain
more win. Newcastle United Club also has quite good name in the field and players are offered
good and attractive fees (Larson and Chang, 2016). However, problem statement can be analysed
that management of Newcastle United Club offers higher fees to players which is not according
to their performance. It simply means that they are paid in accordance to their name only. This
means that structured fees criteria must be revised and formed accordingly to individual players'
performance.
Adequate fees structure must be implemented so that all players may perform well and
also no conflict may prevail regarding fees paid and goals made (Côrte-Real, Oliveira and Ruivo,
2017). This shows that player who score more should be paid higher and other who scores less
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should be paid accordingly. This will gradually enhance overall performance of team will get
better in the best manner possible. In order to resolve this issue, excel dashboard on the overall
statistical data of players of Newcastle United Club will be provided which will provide clarity
to management to apply fees structure. It provides that graphical representation will be made
which will include total goals, key passes per game, average passes, fees paid, fouls made and
pass success percentage etc. With the help of these criteria, excel dashboard will be prepared and
will be fruitful for Newcastle United Club's management to take decision and revise fees
structure.
Business Intelligence is a crucial technique which is used to analyse problem and provide
results for decision-making with ease. Dashboard is useful data visualisation tool which provides
clarity regarding status of metrics and KPI (Key Performance Indicators). On the other hand,
SAS is another useful tool for converting data into the meaningful form so that clear picture of
performance can be ascertained (What is SAS Software – Types of Software in SAS. 2018).
Newcastle United Club will be able to ascertain who are the players performing well and who
scoring low, this information will be provided with the help of results of output by SAS and
solution to problem will be provided in the best manner possible. It can be analysed that apart
from these techniques, regression and cluster analysis of statistics will be used as well.
Regression analysis is used for assessing relationship between two or more variables.
Results of regressions such as dependent and independent variable are ascertained (Dedić and
Stanier, 2016). On the other hand, cluster analysis means to group set of objects in a manner that
objects in same group become similar rather than those cannot be done similarly in other group
such as clusters. In other words, it is a method for classifying sample of objects on basis of
measured variable set which posses same characteristics, hence, placed in group. Thus, main
issue prevailing in Newcastle United Club is that appropriate fees are not offered to players.
High scoring individuals are paid less and low performing players are paid high enough. This
means that fees should not be paid according to big names but should be paid with reference to
overall goals made by them.
2. Evidencing knowledge of BI/DA system
Regression Analysis
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Data Set Name WORK.IMPORT1 Observations 10
Member Type DATA Variables 7
Engine V9 Indexes 0
Created 11/26/2018 16:01:11 Observation Length 56
Last Modified 11/26/2018 16:01:11 Deleted
Observations
0
Protection Compressed NO
Data Set Type Sorted NO
Label
Data Representation SOLARIS_X86_64, LINUX_X86_64, ALPHA_TRU64,
LINUX_IA64
Encoding utf-8 Unicode (UTF-8)
Engine/Host Dependent Information
Data Set Page Size 65536
Number of Data Set Pages1
First Data Page 1
Max Obs per Page 1166
Obs in First Data Page 10
Number of Data Set
Repairs
0
Filename /tmp/SAS_work61EC00001CE2_localhost.localdomain/
SAS_work657700001CE2_localhost.localdomain/import1.sas7bdat
Release Created 9.0401M5
Host Created Linux
3

Engine/Host Dependent Information
Inode Number 409662
Access Permission rw-rw-r--
Owner Name sasdemo
File Size 128KB
File Size (bytes) 131072
Alphabetic List of Variables and Attributes
#Variable Type LenFormat Informat Label
6Fees_paid Num 8BEST. Fees paid
7Fouls Num 8BEST. Fouls
5Key_passes_per_ga
me
Num 8BEST. Key passes per
game
4Passes Num 8BEST. Passes
1Players Char 14$14. $14. Players
2Position Char 1$1. $1. Position
3TOTAL_GOALS Num 8BEST. TOTAL GOALS
Number of Observations Read 10
Number of Observations Used 7
Number of Observations with Missing Values 3
4

Analysis of Variance
Source DF
Sum of
Squares
Mean
Square F Value Pr > F
Model 1 219481 219481 0.27 0.6257
Error 5 4068291 813658
Corrected Total 6 4287771
Root MSE 902.03003R-Square 0.0512
Dependent Mean 2265.7142
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Adj R-Sq -0.1386
Coeff Var 39.81217
Parameter Estimates
Label DF
Parameter
Estimate
Standard
Error t Value Pr > |t|
Intercept 12080.00000494.06220 4.21 0.0084
TOTAL
GOALS
1 118.18182227.54834 0.52 0.6257
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Fit Diagnostics for Fees_paid
-0.139Adj R-Square
0.0512R-Square
813658M SE
5Error DF
2Parameters
7Observations
Proportion Less
0.2 0.8
Residual
0.2 0.8
Fit–Mean
-1000
-500
0
500
1000
1500
-2400 -800 800 2400
Residual
0
10
20
30
40
Percent
1 2 3 4 5 6 7
Observation
0
2
4
6
8
Cook's D
1500 2500 3500
Predicted Value
1500
2000
2500
3000
3500
Fees paid
-1.5 -0.5 0.5 1.5
Quantile
-1000
0
1000
Residual
0.2 0.4 0.6 0.8
Leverage
-2
0
2
4
RStudent
2200 2400 2600
Predicted Value
-2
0
2
4
RStudent
2200 2400 2600
Predicted Value
-1000
-500
0
500
1000
1500
Residual
6

0 1 2 3 4 5
TOTAL GOALS
-1000
-500
0
500
1000
1500
Residual
Residuals for Fees_paid
7

0 1 2 3 4 5
TOTAL GOALS
-1000
-500
0
500
1000
1500
Residual
Residuals for Fees_paid
3. Making critical analysis and justifying use of BI/DA system
Excel Dashboard
The excel dashboard provides graphical representation of players' performance of
Newcastle United Club in the best way possible. It can be assessed that there are various players
of football club playing for the team and scoring goals. Ciaran Clark is a defender who has
scored 2 goals in recent season of football league. Fees paid to him is £5000. While, Ayoze Perez
has also scored 2 goals and fees paid to him is 1600. Salomon Rondon is forward player and
scored 7 goals which is among the highest in the season for any players, fees paid to him is 1350.
Kenedy has scored one goal, whereas fees paid is 9000. Ki Sung-yueng has made no goal in the
season and fees offered is 6000. While, three big names in Newcastle United Club are Matt
Richie, Jacob Murphy and Jonjo Shelvey who have made no goals. Fees are 12000 which is
highest paid to them. Javier Manquillo has also not made single goal and fees is 4500. While,
DeAndre Yedlin has made one goal and fees paid to him is 5000.
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The above analysis make clear that fees paid to players in accordance to their
performance is not adequate. Salomon Rondon is highest scorer and paid considerably low.
Whereas, Matt Richie, Jonjo Shelvey and Jacob Murphy are paid higher even though, they have
made no goals. This clearly shows that salaries or fees offered to players are not adequate which
means that fees criteria needs to be revised (Choi, Chan and Yue, 2017). This will have immense
level of satisfaction among soccer players and they will score more goals. Moreover, highest
scorer could be rewarded which will enhance performance of overall team and as a result,
efficiency can be gathered. Hence, it gets clear with the help of preparation of excel dashboard
that management needs to apply appropriate fees structure so as to enhance morale of every
players and resolve problem quite effectually.
Regression Analysis
The regression analysis is used to study relationship between dependent variable and
independent variables (Shmueli and et.al., 2017). For making assessment of analysis, hypothesis
is to be performed which is provided below-
H0: There is no statistical difference between fees offered and total goals made by Newcastle
United Club
H1: There is statistical difference between fees offered and total goals made by Newcastle
United Club
It can be interpreted that p value is higher which highlights that there is statistical
difference between fees offered and goals made by football players in Newcastle United Football
Club. This means that fees paid have no significance on performance of players. Cluster
sampling is also implied which divides population into separate groups known as clusters.
4. Conclusion and recommendation for BI/DA system in football club
Conclusion
Hereby it can be concluded that players are to be provided with fees in accordance to the
performance only which will provide Newcastle United Club to make proper balance of fees ot
be paid to players. It is required that to improve the performance of all players which can be
effectively improved by equal fees on the basis of performance in effective manner. Players are
to be paid in accordance to the performance carried out by them in football matches held in order
to make proper utilisation of funds and enhancing overall team performance. The outcome that
can be generated from report is that higher scorer player, Salomon Random is getting low fees
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while, Matt Richie, Jacob Murphy and Jonjo Shelvey who have not scored any goal in recent
season. Moreover, it shows that players' performance is to be assessed and only after that, fees
criteria should be set accordingly. This will enhance overall performance of team in effectual
manner.
Fair salaries should be provided on performance basis so that overall team performance
can be enhanced in a better manner. More matches will be won by team if salaries are provided
in accordance to the performance and not on the basis of big names. This means that
management will be able to recreate fees structure in a better manner. Lucrative fees on
performance basis must be imparted which will enhance satisfaction level of people and they will
be able to score more goals and as a result, more matches will be won.
Recommendations
In accordance to outcome provided by SAS and other statistical measure, following
recommendations can be imparted-
 It is hereby recommended that performance should be purely judged, then only fees must
be paid and according to their big names. If fees are less paid to high scorers, then they
will not stay with the team.
 It is required that talented players must be retained in a better manner. It is needed as
increasing monetary benefits to them will prove to be beneficial for management and
team. They will not leave team and would become committed to enhance more goals for
the team.
 The player's skills, abilities, pass success percentage and overall efficiency must be
assessed and after that, proper fees structure should be implemented. This will provide
positive energy among the players and they will not get disheartened.
 It is also recommended to Newcastle United Club management to take help of BI/DA
system which converts data into meaningful form and adequate outcome can be attained
in a better manner. This will help management to enhance morale of employees so that
maximum goals can be made quite effectually.
 Furthermore, with the help excel dashboard, graphical representation of data must be
represented in a better way so as to enable clarity regarding performance of players.
Thus, by referring to and applying these recommendations, management may be able to
resolve problem quite easily.
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REFERENCES
Books and Journals
Choi, T. M., Chan, H. K., & Yue, X. (2017). Recent development in big data analytics for
business operations and risk management. IEEE transactions on cybernetics. 47(1). 81-92.
Côrte-Real, N., Oliveira, T., & Ruivo, P. (2017). Assessing business value of Big Data Analytics
in European firms.Journal of Business Research. 70. 379-390.
Dedić, N., & Stanier, C. (2016, November). Towards differentiating business intelligence, big
data, data analytics and knowledge discovery. In International Conference on Enterprise
Resource Planning Systems (pp. 114-122). Springer, Cham.
Larson, D., & Chang, V. (2016). A review and future direction of agile, business intelligence,
analytics and data science.International Journal of Information Management. 36(5). 700-
710.
Shmueli, G. & et.al., (2017). Data mining for business analytics: concepts, techniques, and
applications in R. John Wiley & Sons.
ONLINE
What is SAS Software – Types of Software in SAS. 2018 [Online] Available Through:
<https://data-flair.training/blogs/sas-software/>
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