quantitative techniqes forbusiness decisions on arsenal football club

7/28/2019 quantitative techniqes forbusiness decisions on arsenal football club

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QUANTITATIVE TECHNIQUES FOR BUSINESS DECISIONS

REPORT ON

ARSENALFOOTBALL CLUB

Submitted by:

SAMIKSHA KALRA (2012267)

SAURABH SURANA (2012283)SHREYAS TIWARI (2012299)

SUNEET SHOME (2012315)


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Industry/company profile

Arsenal Football Club is an English Premier League football club based inHolloway, London. One of the most successful clubs in English football, it haswon 13 First Division and Premier League titles and 10 FA Cups. Arsenal holds

the record for the longest uninterrupted period in the English top flight and would be placed first in an aggregated league of the entire 20th century. It is the secondside to complete an English top flight season unbeaten (in the 2003 04 season) ,and the only one to do it across 38 matches.

Arsenal was founded in 1886 in Woolwich and in 1893 became the first club fromthe south of England to join the Football League. In 1913, it moved north acrossthe city to Arsenal Stadium in Highbury. In the 1930s the club won five LeagueChampionship titles and two FA Cups. After a lean period in the post-war years itwon the League and FA Cup Double, in the 1970 71 season, and in the 1990s andfirst decade of the 21st century won two more Doubles and reached the 2006

UEFA Champions League Final. Arsenal has a long-standing rivalry withneighbours Tottenham Hotspur, with whom it contests the North London derby. Arsenal is the fourth most valuable association football club in the world as of 2012, valued at $1.3 billion.
http://en.wikipedia.org/wiki/Englandhttp://en.wikipedia.org/wiki/Premier_Leaguehttp://en.wikipedia.org/wiki/Association_footballhttp://en.wikipedia.org/wiki/Holloway,_Londonhttp://en.wikipedia.org/wiki/Londonhttp://en.wikipedia.org/wiki/Football_records_in_England#Most_successful_clubs_overall_.281871_.E2.80.93_present.29http://en.wikipedia.org/wiki/Football_League_First_Divisionhttp://en.wikipedia.org/wiki/FA_Cuphttp://en.wikipedia.org/wiki/The_Invincibles_(football)http://en.wikipedia.org/wiki/2003%E2%80%9304_FA_Premier_Leaguehttp://en.wikipedia.org/wiki/2003%E2%80%9304_FA_Premier_Leaguehttp://en.wikipedia.org/wiki/2003%E2%80%9304_FA_Premier_Leaguehttp://en.wikipedia.org/wiki/Woolwichhttp://en.wikipedia.org/wiki/The_Football_Leaguehttp://en.wikipedia.org/wiki/Arsenal_Stadiumhttp://en.wikipedia.org/wiki/Highburyhttp://en.wikipedia.org/wiki/Double_(association_football)http://en.wikipedia.org/wiki/1970%E2%80%9371_in_English_footballhttp://en.wikipedia.org/wiki/1970%E2%80%9371_in_English_footballhttp://en.wikipedia.org/wiki/1970%E2%80%9371_in_English_footballhttp://en.wikipedia.org/wiki/2006_UEFA_Champions_League_Finalhttp://en.wikipedia.org/wiki/2006_UEFA_Champions_League_Finalhttp://en.wikipedia.org/wiki/Tottenham_Hotspur_F.C.http://en.wikipedia.org/wiki/North_London_derbyhttp://en.wikipedia.org/wiki/North_London_derbyhttp://en.wikipedia.org/wiki/Tottenham_Hotspur_F.C.http://en.wikipedia.org/wiki/2006_UEFA_Champions_League_Finalhttp://en.wikipedia.org/wiki/2006_UEFA_Champions_League_Finalhttp://en.wikipedia.org/wiki/1970%E2%80%9371_in_English_footballhttp://en.wikipedia.org/wiki/Double_(association_football)http://en.wikipedia.org/wiki/Highburyhttp://en.wikipedia.org/wiki/Arsenal_Stadiumhttp://en.wikipedia.org/wiki/The_Football_Leaguehttp://en.wikipedia.org/wiki/Woolwichhttp://en.wikipedia.org/wiki/2003%E2%80%9304_FA_Premier_Leaguehttp://en.wikipedia.org/wiki/The_Invincibles_(football)http://en.wikipedia.org/wiki/FA_Cuphttp://en.wikipedia.org/wiki/Football_League_First_Divisionhttp://en.wikipedia.org/wiki/Football_records_in_England#Most_successful_clubs_overall_.281871_.E2.80.93_present.29http://en.wikipedia.org/wiki/Londonhttp://en.wikipedia.org/wiki/Holloway,_Londonhttp://en.wikipedia.org/wiki/Association_footballhttp://en.wikipedia.org/wiki/Premier_Leaguehttp://en.wikipedia.org/wiki/England


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Objectives of the study1. To analyze previous years data on Player Trading, Broadcasting rights and Corporate Rights to

understand the central tendencies and dispersions in these factors.2. To apply the understanding of statistical techniques to forecast the values of the mentioned

factors.3. Forecast the values of Broadcasting Rights, Corporate Rights and Player Trading figures to

estimate the availability of funds for payer trading in the next season.

Methodology

To arrive at the objective, we have used the following statistical tools

1. Computation of mean, median, standard deviation and variance.2. Hypothesis testing.3. Forecast the values of Broadcasting Rights, Corporate Rights and Player Trading usingi) Semi average methodii) MS Excel software package

4. Multiple regression analysis to forecast value of Player Trading depending on forecasted valuesof Broadcasting Rights and Corporate Rights using MS Excel software package.


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Analysis and findings with implications

Data, Measures of Central Tendency & Measures of Dispersion

The three variables used in the study are:- Broadcasting Rights Corporate Rights Player Trading

Where Broadcasting Rights and Corporate Rights form a major part of the Total Revenue andare treated as Independent Variable , while Player Trading forms a major part of the totalexpenses and is treated is Dependent Variable .

Year Broadcasting Corporate Player Trading2004 59.87 -12.18 0.52005 48.6 -8.736 02006 54.87 3.9 0.1392007 44.312 0.2 0.5442008 68.4 5.2 0.4722009 73.2 2.9 3.5892010 84.584 0.14 0.462011 85.244 0.394 0.735

MEDIAN 64.135 0.297 0.486MEAN 64.885 -1.02275 0.804875

STANDARDDEVIATION 15.57440178 6.178034726 1.148800422VARIANCE 242.5619908 38.16811308 1.3197241

Note: All values are in million pounds.

Forecasting

Forecasting has been done for the 3 variables:- Broadcasting Rights Corporate Rights Player Trading

Forecasting has been done using two approaches:- Using Ms Excel Semi Averages Method

Calculation done with confidence level of 95%


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Forecasting for broadcasting

Year Broadcasting

2004 59.87

2005 48.62006 54.87

2007 44.3122008 68.42009 73.22010 84.5842011 85.244

Forecast using MS Excel (2012) 88.27514286

Semi-Averages MethodAverage of first 4 years (2004 to 2007) 51.913Average of last 4 years (2008 to 2011) 77.857

Slope of the trend line (b) 6.486Intercept ( a ) 51.913

Forecasted value for the year 2012 = a+bx, where x=B 103.801

0

20

40

60

80

100

120

2004 2005 2006 2007 2008 2009 2010 2011 2012

A c t u a

l V a

l u e s

( i n m

)

Years

Broadcasting Rights

Actual Values

Linear (Actual Values)


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Forecasting For Corporate

Year Corporate

2004 -12.182005 -8.7362006 3.9

2007 0.22008 5.22009 2.9

2010 0.142011 0.394


Semi-Averages MethodAverage of first 4 years (2004 to 2007) -4.204Average of last 4 years (2008 to 2011) 2.1585

Slope of the trend line (b) 1.590625Intercept ( a ) -4.204


-15

-10

-5

0

5

10

15

2004 2005 2006 2007 2008 2009 2010 2011 2012

A c t u a

l V a

l u e s

( i n m

)

Years

Corporate Rights

Actual Values



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Forecasting for Player Trading

Year Player Trading

2004 0.52005 02006 0.139

2007 0.5442008 0.4722009 3.589

2010 0.462011 0.735


Semi-Averages MethodAverage of first 4 years (2004 to 2007) 0.29575Average of last 4 years (2008 to 2011) 1.314

Slope of the trend line (b) 0.2545625Intercept ( a ) 0.29575


0

0.5

1

1.5

2

2.5

3

3.5

4

1 3 5 7 9 11

A c t u a

l V a

l u e s

( i n m

)

Years

Player Trading

Actual Values



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REGRESSION ANALYSIS

Regression Analysis has been done using multiple regression model with two independent variable,Broadcasting Rights and Corporate Rights and the dependent variable, Player Trading. Using the model,the value of Player Trading has been forecasted from the forecasted values (obtained using MS Excel) of

Broadcasting Rights and Corporate Rights.

ANOVA Column1 Column2 Column3 Column4 Column5

Df SS MS FSignificance

FRegression 2 1.321400753 0.660700376 0.41727762 0.679838286

Residual 5 7.916796122 1.583359224Total 7 9.238196875

olumn1 Coefficients StandardError t Stat P-value Lower 95% Upper 95% Lower95.0% Upper95.0%

ntercept-

0.38601547 2.162978463 -0.17846478 0.86536369-

5.94612862 5.174097674-

5.94612862 5.17409767Variable

1 0.01896255 0.032195027 0.588989982 0.58147058 -0.0637974 0.1017225 -0.0637974 0.1017225Variable

2 0.03861597 0.081161455 0.475791956 0.6542841-

0.17001619 0.247248129-

0.17001619 0.24724813

RESIDUAL OUTPUT

Observation Predicted Y Residuals Standard Residuals1 0.278929818 0.221070182 0.207876051

2 0.198215289 -0.198215289 -0.1863852073 0.805061831 -0.666061831 -0.6263092654 0.461976166 0.082023834 0.0771284065 1.111825868 -0.639825868 -0.6016391436 1.114029376 2.474970624 2.327256962

Regression Statistics Column1Multiple R 0.378201867R Square 0.143036652

Adjusted R Square-

0.199748687

Standard Error 1.258316027Observations 8


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7 1.223318957 -0.763318957 -0.7177617948 1.245642694 -0.510642694 -0.480166008

Probability Output

Percentile Y6.25 0

18.75 0.139

31.25 0.46

43.75 0.472

56.25 0.5

68.75 0.544

81.25 0.735

93.75 3.589

Equation for Multiple Regression line with two Independent variables,

Y- hat = B0+B1X1+B2X2

Where,

B0= -0.38602

B1= 0.018963

B2= 0.038616

X1, Forecasted value of Broadcasting Rights through MS Excel = 88.27514286

X2, Forecasted value of Corporate Rights through MS Excel = 6.1771429

Y-hat = Proposed forecast of player trading

Therefore from calculations Y-hat= 1.526

The proposed forecast of player trading calculated using multiple regression analysis is similar to the

forecasted value calculated using the forecast method of MS Excel.


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Conclusion and scope for further study

As per our objectives, we analyzed previous years data on Player Trading, Broadcasting rights and

Corporate Rights and computed the trends in central tendencies and dispersion.

The Forecasted values calculated using the two approaches with confidence level of 95%:- Using Ms Excel for

i) Broadcasting Rights 88.27514286ii) Corporate Rights 6.177142857iii) Player Trading 1.566821429

Using Semi Averages Method for

i) Broadcasting Rights 103.801ii) Corporate Rights 8.521iii) Player Trading 2.33225

Comparing with previous year data,

Year Broadcasting Corporate Player Trading2011 85.244 0.394 0.735

Revenue from the Broadcasting rights and the Corporate rights are expected to increase hence, fundsavailable for Player trading would be greater for the next season which is confirmed from theforecasting as well.

Regression Analysis has been done using multiple regression model with two independent variable,Broadcasting Rights and Corporate Rights and the dependent variable, Player Trading

The proposed forecast of player trading calculated using multiple regression analysis ( Y-hat= 1.526) issimilar to the forecasted value calculated using the forecast method of MS Excel.

Scope of further study.

When analyzing a Football club business, we have to consider multiple factors to do a comparative study

in real business scenario. The study can be completed with considering more factors such as

Ticket sales

Property Development

Retail Merchandising

Returns on Investment


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Amortization of player registrations

and others to get a accurate model for statistical analysis.

Bibliography

www.arsenal.com

Delloite Football Money Leage Feb. 2012 document.

www.bbc.co.uk

www.office.com
http://www.arsenal.com/http://www.bbc.co.uk/http://www.bbc.co.uk/http://www.arsenal.com/

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quantitative techniqes forbusiness decisions on arsenal football club