Knowledge Management for UEFA Champions League By Harsha Gunnam Hetal Mehta Nargis Memon Manish Wadhwa

6/10/2015MIS 580: Knowledge Management2 TasksHarshaHetalNargisManish Initial Research Literature Review Data Extraction Database Creation Coefficient Analysis Ranking Analysis Trend Analysis Prediction of Winners Testing of Results Final Report & Presentation Individual Contributions Objectives Process Basic Findings Introduction Sources Interesting FindingsFuture WorkConclusion

6/10/2015MIS 580: Knowledge Management3 Agenda Objectives Process Basic Findings Introduction Sources Interesting Findings IntroductionObjectivesProcessSourcesBasic FindingsInteresting FindingsConclusionFuture Work Conclusion

6/10/2015MIS 580: Knowledge Management4 UEFA Champions League Competition System 1st qualifying round24 2nd qualifying round rd qualifying round18+14 Group stage16+16 First knock-out round16 Quarter finals8 Semi-finals4 Final2 Introduction Objectives Process Basic Findings Introduction Sources 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 WorkConclusion

6/10/2015MIS 580: Knowledge Management5 Identify the top three leagues for Identify top 4 clubs for the top 3 leaguesIdentify the home and away advantageIdentify the head-to-head probabilityIdentify possible array of winners for Research Objectives Objectives Process Basic Findings Introduction Sources Interesting FindingsFuture WorkConclusion

6/10/2015MIS 580: Knowledge Management6  Papahristodoulou, Christos, "Team Performance in UEFA Champions League " Munich Personal RePEc Archive (2006) Unpublished, Paper #138  Barros, Carlos Pestana, Leach, Stephanie, “Performance evaluation of the English Premier Football League with data envelopment analysis.”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):   Sports Betting Information   Online Betting Guide   Online Predictor Game Literature Review Objectives Process Basic Findings Introduction Sources Interesting FindingsFuture WorkConclusion

6/10/2015MIS 580: Knowledge Management7 Research Design Objectives Process Basic Findings Introduction Sources 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 WorkConclusion

6/10/2015MIS 580: Knowledge Management8 Data Sources Objectives Process Basic Findings Introduction Sources Interesting Findings  UEFA Data Source   Data collected over 6 seasons   Attributes - Future WorkConclusion

6/10/2015MIS 580: Knowledge Management9 Basic Findings Objectives Process Basic Findings Introduction Sources Interesting FindingsFuture WorkConclusion Coefficient Analysis

6/10/2015MIS 580: Knowledge Management10  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 Analysis Objectives Process Basic Findings Introduction Sources Interesting FindingsFuture WorkConclusion

6/10/2015MIS 580: Knowledge Management11 Basic Findings Objectives Process Basic Findings Introduction Sources Interesting FindingsFuture WorkConclusion Ranking Analysis

6/10/2015MIS 580: Knowledge Management12 Predicted Ranking Objectives Process Basic Findings Introduction Sources Interesting Findings  Accuracy: 100%  Years Considered:  Country Ranking = Summation of 5 years of Country Coefficients  Team Ranking = Summation of 5 years of Team Coefficients Future WorkConclusion

6/10/2015MIS 580: Knowledge Management13 Ranking Analysis - Leagues Objectives Process Basic Findings Introduction Sources Interesting Findings  Observations:  Spain, England and Italy: Top three leagues for the past six seasons  Romania: Rapid Improvement Future WorkConclusion

6/10/2015MIS 580: Knowledge Management14 Top Leagues & Teams Objectives Process Basic Findings Introduction Sources Interesting FindingsFuture WorkConclusion Spain FC Barcelona Real Madrid Sevilla Valencia England Arsenal Chelsea Liverpool Manchester United Italy AC Milan AS Roma Internazionale Juventus

6/10/2015MIS 580: Knowledge Management15 Ranking Analysis - Teams Objectives Process Basic Findings Introduction Sources Interesting Findings  Observations:  Consistent Team: FC Barcelona  Rapid Improvement: Chelsea Future WorkConclusion

6/10/2015MIS 580: Knowledge Management16 Probability Analysis Interesting Findings Objectives Process Basic Findings Introduction Sources Interesting FindingsFuture WorkConclusion

6/10/2015MIS 580: Knowledge Management17  Technique:  Naive Bayes  Observations:  Strength: 6 Teams  Weakness: FC Barcelona Head-to-Head Probability Analysis Objectives Process Basic Findings Introduction Sources Interesting FindingsFuture WorkConclusion

6/10/2015MIS 580: Knowledge Management18  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 TeamOpponent Prediction AC MilanCeltic0.50OK AC MilanShakhtar Donetsk11OK ArsenalSparta Praha11OK AS RomaDinamo Kiev1NOT OK AS RomaManchester United0-0.75OK AS RomaReal Madrid-0.51NOT OK ChelseaValencia0.51OK FC BarcelonaCeltic0.51OK Manchester UnitedOlympique Lyon00.5OK Real MadridOlympiakos Piraeus0.5 OK Head-to-Head Probability Testing Future WorkConclusion

6/10/2015MIS 580: Knowledge Management19 Home-Away Analysis Interesting Findings Objectives Process Basic Findings Introduction Sources Interesting FindingsFuture WorkConclusion

6/10/2015MIS 580: Knowledge Management20  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 Analysis Objectives Process Basic Findings Introduction Sources Interesting FindingsFuture WorkConclusion

6/10/2015MIS 580: Knowledge Management21  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 WorkConclusion

6/10/2015MIS 580: Knowledge Management22 Winners Analysis Interesting Findings Objectives Process Basic Findings Introduction Sources Interesting FindingsFuture WorkConclusion

6/10/2015MIS 580: Knowledge Management23  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 Future WorkConclusion

6/10/2015MIS 580: Knowledge Management24  Dataset considered –  Accuracy:  Home Win: 90%  Away Win: 100% Objectives Process Basic Findings Introduction Sources Interesting FindingsFuture WorkConclusion Testing of Final Prediction

6/10/2015MIS 580: Knowledge Management25 Good visiting teams have a better chance at the trophySports knowledge can be transferred from tacit to explicitField with a wide scope for researchGood career choice – Sports Consultant Conclusion Objectives Process Basic Findings Introduction Sources Interesting FindingsFuture WorkConclusion

6/10/2015MIS 580: Knowledge Management26 Extended data setRound level analysisPlayer level analysisTeam strategy analysisConsideration of UEFA Cup Sports BettingSports Consulting Applications Future Work Applications & Future Work Objectives Process Basic Findings Introduction Sources Interesting FindingsFuture WorkConclusion

6/10/2015MIS 580: Knowledge Management27 References Objectives Process Basic Findings Introduction Sources Interesting FindingsFuture WorkConclusion  Papahristodoulou, Christos, "Team Performance in UEFA Champions League " 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):  Websites:         

6/10/2015MIS 580: Knowledge Management28 Thank You Objectives Process Basic Findings Introduction Sources Interesting FindingsFuture WorkConclusion Thank You Dr. Hsinchun Chen Yulei Zhang (Gavin) Yan Dang (Mandy)

6/10/2015MIS 580: Knowledge Management29 Questions Objectives Process Basic Findings Introduction Sources Interesting FindingsFuture WorkConclusion

6/10/2015MIS 580: Knowledge Management30 Head-to-Head Probability Analysis Objectives Process Basic Findings Introduction Sources Interesting FindingsFuture WorkConclusion

6/10/2015MIS 580: Knowledge Management31 Head-to-Head Probability Analysis Objectives Process Basic Findings Introduction Sources Interesting FindingsFuture WorkConclusion FC Barcelona Vs Others Liverpool Vs Others