Knowledge Management for

UEFA Champions LeagueBy

Harsha GunnamHetal Mehta

Nargis MemonManish Wadhwa

04/21/23 MIS 580: Knowledge Management 2

Tasks Harsha Hetal Nargis Manish

Initial Research

Literature Review

Data Extraction

Database Creation

Coefficient Analysis

Ranking Analysis

Trend Analysis

Prediction of Winners

Testing of Results

Final Report & Presentation

Individual ContributionsObjectives Process Basic

FindingsIntroducti

onSources Interesting

FindingsFuture Work

Conclusion

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AgendaObjectives Process Basic

FindingsIntroducti

onSources Interesting

FindingsFuture Work

Conclusion

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UEFA Champions League Competition System

1st qualifying round 24

2nd qualifying round 16+12

3rd qualifying round 18+14

Group stage 16+16

First knock-out round 16

Quarter finals 8

Semi-finals 4

Final 2

IntroductionObjectives Process Basic

FindingsIntroducti

onSources Interesting

Findings

UEFA - The governing body of football on the continent of Europe

Champions League – Started in 1992 Most Prestigious Trophy in the Sport Current Champion: AC Milan

Format –

Future Work

Conclusion

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Research ObjectivesObjectives Process Basic

FindingsIntroducti

onSources Interesting

FindingsFuture Work

Conclusion

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Papahristodoulou, Christos, "Team Performance in UEFA Champions League 2005-06." Munich Personal RePEc Archive (2006) Unpublished, Paper #138

Barros, Carlos Pestana, Leach, Stephanie, “Performance evaluation of the English Premier Football League with data envelopment analysis.” Applied Economics Vol. 38 No. 12 (2006): 1449-1458

http://www.betinf.com/champ.htm Sports Betting Information

http://www.betstudy.com/soccer-stats/c/europe/uefa-champions-league/ Online Betting Guide

http://en.uclpredictor.uefa.com/ Online Predictor Game

Literature ReviewObjectives Process Basic

FindingsIntroducti

onSources Interesting

FindingsFuture Work

Conclusion

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Research DesignObjectives Process Basic

FindingsIntroducti

onSources Interesting

Findings

Excel

Data Extraction

Ranking Analysis

Coefficient Analysis

Top 3 Leagues

Top 12 Teams

Array of Winners

Head-to-Head Probability

Home & Away Advantage

MySQL

UEFA Data Source

Future Work

Conclusion

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Data SourcesObjectives Process Basic

FindingsIntroducti

onSources Interesting

Findings

UEFA Data Source http://www.xs4all.nl/~kassiesa/bert/uefa/

Data collected over 6 seasons 2002-2008

Attributes -

Table Name Team Statistics Team Country Team Coefficient Country Coefficient MatchesTeam Team Team Country YearCup Country Team Coefficient Country Coefficient Round

Qualifying Wins Year Year TeamQualifying Draws GoalsQualifying Losses

Number of Wins

Number of Draws

Number of Losses

Bonus

PointsYear

Cardinality 1185 449 788 310 637

Fields

Future Work

Conclusion

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Basic FindingsObjectives Process Basic

FindingsIntroducti

onSources Interesting

FindingsFuture Work

Conclusion

Coefficient Analysis

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Standard UEFA Calculations

Country Coefficient = Number of Points/Number of Teams Calculation Accuracy: 100%

Team Coefficient = Number of Points + 33% of Country Coefficient Calculation Accuracy: 100%

Coefficient AnalysisObjectives Process Basic

FindingsIntroducti

onSources Interesting

FindingsFuture Work

Conclusion

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Basic FindingsObjectives Process Basic

FindingsIntroducti

onSources Interesting

FindingsFuture Work

Conclusion

Ranking Analysis

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Predicted RankingObjectives Process Basic

FindingsIntroducti

onSources Interesting

Findings

Accuracy: 100% Years Considered: 2003-2008 Country Ranking = Summation of 5

years of Country Coefficients Team Ranking = Summation of 5

years of Team Coefficients

Future Work

Conclusion

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Ranking Analysis - LeaguesObjectives Process Basic

FindingsIntroducti

onSources Interesting

Findings

Observations: Spain, England and Italy: Top three leagues for the past six seasons Romania: Rapid Improvement

Future Work

Conclusion

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Top Leagues & TeamsObjectives Process Basic

FindingsIntroducti

onSources Interesting

FindingsFuture Work

Conclusion

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Ranking Analysis - TeamsObjectives Process Basic

FindingsIntroducti

onSources Interesting

Findings

Observations: Consistent Team: FC Barcelona Rapid Improvement: Chelsea

Future Work

Conclusion

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Probability Analysis

Interesting FindingsObjectives Process Basic

FindingsIntroducti

onSources Interesting

FindingsFuture Work

Conclusion

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Technique: Naive Bayes

Observations: Strength: 6 Teams Weakness: FC Barcelona

Head-to-Head Probability AnalysisObjectives Process Basic

FindingsIntroducti

onSources Interesting

FindingsFuture Work

Conclusion

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Technique: Comparison of the signs of the difference between the win probability and

the lose probability Matched signs – Correct Prediction Different signs – Incorrect Prediction

Assumption Difference of zero (win-loss) favors both ways

Accuracy: 80%

Objectives Process Basic Findings

Introduction

Sources Interesting Findings

Team Opponent 2003-07 2008 Prediction

AC Milan Celtic 0.5 0 OK

AC Milan Shakhtar Donetsk 1 1 OK

Arsenal Sparta Praha 1 1 OK

AS Roma Dinamo Kiev -1 1 NOT OK

AS Roma Manchester United 0 -0.75 OK

AS Roma Real Madrid -0.5 1 NOT OK

Chelsea Valencia 0.5 1 OK

FC Barcelona Celtic 0.5 1 OK

Manchester United Olympique Lyon 0 0.5 OK

Real Madrid Olympiakos Piraeus 0.5 0.5 OK

Head-to-Head Probability Testing Future

WorkConclusio

n

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Home-Away Analysis

Interesting FindingsObjectives Process Basic

FindingsIntroducti

onSources Interesting

FindingsFuture Work

Conclusion

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Technique: Mapped advantage on the basis of strength. Strength level decided by the difference in goals scored

Very Strong – Win with a difference of 2 or more goals Strong – Win with a difference of 1 goal Weak – Draw or lose with a difference of 1 goal Very Weak – Lose with a difference of 2 or more goals

Home – Away AnalysisObjectives Process Basic

FindingsIntroducti

onSources Interesting

FindingsFuture Work

Conclusion

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Observations: Strongest Home Team: AC Milan Weakest Home Team: Real Madrid Strongest Visiting Team: Liverpool Weakest Visiting Team: Chelsea

Objectives Process Basic Findings

Introduction

Sources Interesting Findings

Home – Away Analysis Future

WorkConclusio

n

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Winners Analysis

Interesting FindingsObjectives Process Basic

FindingsIntroducti

onSources Interesting

FindingsFuture Work

Conclusion

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Technique: Assigned values to strength levels Aggregated the values of the strength levels Team Win Probability = (Aggregated Strength Value * Probability) /

Number of Matches

Objectives Process Basic Findings

Introduction

Sources Interesting Findings

Prediction of Winners

Team ProbabilityFC Barcelona 0.7115625Manchester United 0.61601563Liverpool 0.60256579Real Madrid 0.58089286Valencia 0.578125Internazionale 0.56819444Arsenal 0.52309783AC Milan 0.50989318Chelsea 0.5002425Juventus 0.45089286Sevilla 0.38125AS Roma 0.29888889

Home Win Probability

Team ProbabilityFC Barcelona 0.62822917Liverpool 0.52776316Manchester United 0.50664063Real Madrid 0.48178571Chelsea 0.4796875AC Milan 0.47955909Valencia 0.4609375Juventus 0.45089286Internazionale 0.445Arsenal 0.42663043Sevilla 0.4125AS Roma 0.295511111

Away Win Probability

Array of WinnersFC BarcelonaManchester UnitedLiverpoolReal Madrid

Future Work

Conclusion

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Dataset considered – 2003-2007 Accuracy:

Home Win: 90% Away Win: 100%

Objectives Process Basic Findings

Introduction

Sources Interesting Findings

Future Work

Conclusion

Testing of Final Prediction

Team ProbabilityFC Barcelona 0.64766447Manchester United 0.58220109Valencia 0.57211538Liverpool 0.52321023Real Madrid 0.5140625Juventus 0.51171875AC Milan 0.503115Internazionale 0.4919325Arsenal 0.4880475Chelsea 0.4759375AS Roma 0.21875

Home Win Probability

Winners for 2008ChelseaManchester UnitedFC BarcelonaLiverpool

Team ProbabilityFC Barcelona 0.58799342Liverpool 0.48579545Chelsea 0.48263889Manchester United 0.46535326AC Milan 0.45249Valencia 0.44711538Real Madrid 0.44375Juventus 0.4390625Internazionale 0.43638205Arsenal 0.43074604AS Roma 0.27083333

Away Win Probability

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ConclusionObjectives Process Basic

FindingsIntroducti

onSources Interesting

FindingsFuture Work

Conclusion

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Applications

Future Work

Applications & Future WorkObjectives Process Basic

FindingsIntroducti

onSources Interesting

FindingsFuture Work

Conclusion

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ReferencesObjectives Process Basic

FindingsIntroducti

onSources Interesting

FindingsFuture Work

Conclusion

Papahristodoulou, Christos, "Team Performance in UEFA Champions League 2005-06." Munich Personal RePEc Archive (2006) Unpublished, Paper #138

Barros, Carlos Pestana, Leach, Stephanie, “Performance evaluation of the English Premier Football League with data envelopment analysis.” Applied Economics Vol. 38 No. 12 (2006): 1449-1458

Websites: http://www.betinf.com/champ.htm http://www.betstudy.com/soccer-stats/c/europe/uefa-champions-league/ http://en.uclpredictor.uefa.com/ http://www.uefa.com/competitions/ucl/index.html http://en.wikipedia.org/wiki/Uefa_Champions_League http://en.wikipedia.org/wiki/Bayes_theorem http://www.xs4all.nl/~kassiesa/bert/uefa/ http://www.soccerbase.com/ http://europeancups.altervista.org/

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Thank YouObjectives Process Basic

FindingsIntroducti

onSources Interesting

FindingsFuture Work

Conclusion

Thank You

Dr. Hsinchun Chen

Yulei Zhang (Gavin)Yan Dang (Mandy)

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QuestionsObjectives Process Basic

FindingsIntroducti

onSources Interesting

FindingsFuture Work

Conclusion

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Head-to-Head Probability AnalysisObjectives Process Basic

FindingsIntroducti

onSources Interesting

FindingsFuture Work

Conclusion

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Head-to-Head Probability AnalysisObjectives Process Basic

FindingsIntroducti

onSources Interesting

FindingsFuture Work

Conclusion

FC Barcelona Vs Others

Liverpool Vs Others