Machine Learning and Data Mining for Sports Analytics: 9th International Workshop, MLSA 2022, Grenoble, France, September 19, 2022, Revised Selected Papers PDF
Preview Machine Learning and Data Mining for Sports Analytics: 9th International Workshop, MLSA 2022, Grenoble, France, September 19, 2022, Revised Selected Papers
Ulf Brefeld Jesse Davis Jan Van Haaren Albrecht Zimmermann (Eds.) Communications in Computer and Information Science 1783 Machine Learning and Data Mining for Sports Analytics 9th International Workshop, MLSA 2022 Grenoble, France, September 19, 2022 Revised Selected Papers Communications in Computer and Information Science 1783 EditorialBoardMembers JoaquimFilipe ,PolytechnicInstituteofSetúbal,Setúbal,Portugal AshishGhosh ,IndianStatisticalInstitute,Kolkata,India RaquelOliveiraPrates ,FederalUniversityofMinasGerais(UFMG), BeloHorizonte,Brazil LizhuZhou,TsinghuaUniversity,Beijing,China Rationale The CCIS series is devoted to the publication of proceedings of computer science conferences.Itsaimistoefficientlydisseminateoriginalresearchresultsininformatics inprintedandelectronicform.Whilethefocusisonpublicationofpeer-reviewedfull paperspresentingmaturework,inclusionofreviewedshortpapersreportingonworkin progressiswelcome,too.Besidesgloballyrelevantmeetingswithinternationallyrepre- sentativeprogramcommitteesguaranteeingastrictpeer-reviewingandpaperselection process,conferencesrunbysocietiesorofhighregionalornationalrelevancearealso consideredforpublication. 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Ulf Brefeld · Jesse Davis · Jan Van Haaren · Albrecht Zimmermann Editors Machine Learning and Data Mining for Sports Analytics 9th International Workshop, MLSA 2022 Grenoble, France, September 19, 2022 Revised Selected Papers Editors UlfBrefeld JesseDavis LeuphanaUniversityofLüneburg KULeuven Lüneburg,Germany Leuven,Belgium JanVanHaaren AlbrechtZimmermann KULeuven UniversityofCaenNormandy Leuven,Belgium Caen,France ISSN 1865-0929 ISSN 1865-0937 (electronic) CommunicationsinComputerandInformationScience ISBN 978-3-031-27526-5 ISBN 978-3-031-27527-2 (eBook) https://doi.org/10.1007/978-3-031-27527-2 ©TheEditor(s)(ifapplicable)andTheAuthor(s),underexclusivelicense toSpringerNatureSwitzerlandAG2023 Thisworkissubjecttocopyright.AllrightsarereservedbythePublisher,whetherthewholeorpartof thematerialisconcerned,specificallytherightsoftranslation,reprinting,reuseofillustrations,recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storageandretrieval,electronicadaptation,computersoftware,orbysimilarordissimilarmethodologynow knownorhereafterdeveloped. Theuseofgeneraldescriptivenames,registerednames,trademarks,servicemarks,etc.inthispublication doesnotimply,evenintheabsenceofaspecificstatement,thatsuchnamesareexemptfromtherelevant protectivelawsandregulationsandthereforefreeforgeneraluse. Thepublisher,theauthors,andtheeditorsaresafetoassumethattheadviceandinformationinthisbook arebelievedtobetrueandaccurateatthedateofpublication.Neitherthepublishernortheauthorsorthe editorsgiveawarranty,expressedorimplied,withrespecttothematerialcontainedhereinorforanyerrors oromissionsthatmayhavebeenmade.Thepublisherremainsneutralwithregardtojurisdictionalclaimsin publishedmapsandinstitutionalaffiliations. ThisSpringerimprintispublishedbytheregisteredcompanySpringerNatureSwitzerlandAG Theregisteredcompanyaddressis:Gewerbestrasse11,6330Cham,Switzerland Preface TheMachineLearningandDataMiningforSportsAnalyticsworkshopaimedtobring together a diverse set of researchers working on Sports Analytics in a broad sense. In particular,itaimedtoattractinterestfromresearchersworkingonsportsfromoutside ofmachinelearninganddatamining.The9theditionoftheworkshopwasco-located with the European Conference on Machine Learning and Principles and Practice of KnowledgeDiscovery2022. SportsAnalyticshasbeenasteadilygrowingandrapidlyevolvingareaoverthelast decade, both inUS professionalsportsleagues and inEuropean footballleagues. The recentimplementationofstrictfinancialfair-playregulationsinEuropeanfootballwill definitelyincreasetheimportanceofSportsAnalyticsinthecomingyears.Inaddition, there is the popularity of sports betting. The developed techniques are being used for decisionsupportinallaspectsofprofessionalsports,includingbutnotlimitedto: – Matchstrategy,tactics,andanalysis – Playeracquisition,playervaluation,andteamspending – Trainingregimensandfocus – Injurypredictionandprevention – Performancemanagementandprediction – Matchoutcomeandleaguetableprediction – Tournamentdesignandscheduling – Bettingoddscalculation The interest in the topic has grown so much that there is now an annual confer- ence on Sports Analytics at the MIT Sloan School of Management, which has been attendedbyrepresentativesfromover70professionalsportsteamsineminentleagues such as Major League Baseball, National Basketball Association, National Football League,NationalHockeyLeague,MajorLeagueSoccer,EnglishPremierLeague,and theGermanBundesliga.Furthermore,sportsdataproviderssuchasStatsbomb,StatsPer- form,andWyscouthavestartedmakingperformancedatapubliclyavailabletostimulate researcherswhohavetheskillsandvisiontomakeadifferenceinthesportsanalytics community. Moreover, the National Football League has been sponsoring a Big Data Bowl where they release data and a concrete question to try to engage the analytics community. TherehasbeengrowinginterestintheMachineLearningandDataMiningcommu- nityaboutthistopic,andthe2022editionofMLSAbuiltonthesuccessofprioreditions atECMLPKDD2013andECMLPKDD2015–ECML/PKDD2021. Both the community’s on-going interest in submitting to and participating in the MLSAworkshopseries,andthefactthatyouarereadingthefourthvolumeofMLSA proceedingsshowthatourworkshophasbecomeavitalvenueforpublishingandpre- senting sports analytics results. In fact, as participants, many of whom had submitted before, expressed during the workshop itself, venues for presenting machine learning vi Preface anddatamining-basedsportsanalyticsworkremainrare,motivatingustocontinueto organizetheworkshopinfutureyears. In 2022, the workshop received 18 submissions of which 11 were selected after a single-blindreviewingprocessinvolvingatleastthreeprogramcommitteemembersper paper.Oneoftheacceptedpaperswaswithdrawnfrompublicationintheproceedings; asecondonewasanextendedabstractbasedonajournalpublication.Intermsofthe sportsrepresented,2022sawareturntoprioryearswithsoccermakingupthemajorityof submissions,andaslightmajorityofacceptedpapers.Topicsincludedtacticalanalysis, outcomepredictions,dataacquisition,performanceoptimization,andplayerevaluation. TheworkshopfeaturedaninvitedpresentationbyStephanieKovalchikfromZelus Analyticson“Model-basedmethodsforhigh-performanceanalysisinsports”: Thehowofwhatmakesgreatathletesgreatisoneofthemajortopicsofsportsana- lyticsresearch.Valueattributionisafundamentaltoolforquantifyingthespecific actionsandskillsthatimproveoutcomesinsport.Withthegrowthinspatialtemporal datainhigh-performancesport,methodsforvalueattributionarebecomingincreas- inglygranularandsophisticated.Inthistalk,Iwillreviewseveralcommontypesof model-basedmethodsforvalueattributionandpresentapplicationsinmultiplepro sports. Furtherinformationabouttheworkshopcanbefoundontheworkshop’swebsiteat https://dtai.cs.kuleuven.be/events/MLSA22/. October2022 UlfBrefeld JesseDavis JanVanHaaren AlbrechtZimmermann Organization WorkshopCo-chairs UlfBrefeld LeuphanaUniversity,Lüneburg,Germany JesseDavis KULeuven,Belgium JanVanHaaren ClubBrugge,Belgium&KULeuven,Belgium AlbrechtZimmermann UniversitédeCaenNormandie,France ProgramCommittee MichaelAlcorn AuburnUniversity,USA GennadyAndrienko Fraunhofer,Germany SwarupRanjanBehera IndianInstituteofTechnology,Guwahati,India HarishS.Bhat UniversityofCalifornia,USA LotteBransen SciSports,TheNetherlands PaoloCintia UniversityofPisa,Italy Arie-WillemdeLeeuw UniversiteitLeiden,Belgium TomDecroos Meta,USA WouterDuivesteijn EindhovenUniversityofTechnology, TheNetherlands MartinEastwood www.pena.lt/y,UK ClémentGautrais Brightclue,France KilianHendrickx KULeuven/SiemensDigitalIndustriesSoftware, Belgium MehdiKaytoue Infologic,France LeonidKholkine UniversityofAntwerp,Belgium StephanieKovalchik ZelusAnalytics,USA PatrickLambrix LinköpingUniversity,Sweden JanLasek SystemsResearchInstitute,Poland LaurentiusMeerhoff LeidenInstituteofAdvancedComputerScience, TheNetherlands WannesMeert KULeuven,Belgium LucaPappalardo UniversityofPisa,Italy KonstantinosPelechrinis UniversityofPittsburgh,USA viii Organization FrançoisRioult GREYCCNRSUMR6072-UniversitédeCaen Normandie,France PieterRobberechts KULeuven,Belgium MaaikeVanRoy KULeuven,Belgium Contents Football TowardsExpectedCounter-UsingComprehensibleFeaturestoPredict Counterattacks ........................................................ 3 HenrikBiermann, Franz-GeorgWieland, JensTimmer, DanielMemmert,andAshwinPhatak ShotAnalysisinDifferentLevelsofGermanFootballUsingExpectedGoals ... 14 LaurynasRaudoniusandThomasSeidl Analyzing Passing Sequences for the Prediction of Goal-Scoring Opportunities ......................................................... 27 ConorMcCarthy, PanagiotisTampakis, MarcoChiarandini, MortenBredsgaardRanders,StefanJänicke,andArthurZimek Let’sPenetratetheDefense:AMachineLearningModelforPrediction andValuationofPenetrativePasses ...................................... 41 PegahRahimian, DayanaGraycedaSilvaGuerraGomes, FanniBerkovics,andLaszloToka EvaluationofCreatingScoringOpportunitiesforTeammatesinSoccer viaTrajectoryPrediction ............................................... 53 MasakiyoTeranishi,KazushiTsutsui,KazuyaTakeda,andKeisukeFujii Cost-EfficientandBias-RobustSportsPlayerTrackingbyIntegratingGPS andVideo ............................................................ 74 HyunsungKim, ChangJoKim, MinchulJeong, JaechanLee, JinsungYoon,andSang-KiKo RacketSports PredictingTennisServeDirectionswithMachineLearning .................. 89 YingZhuandRuthuparnaNaikar Discovering and Visualizing Tactics in a Table Tennis Game Based onSubgroupDiscovery ................................................ 101 PierreDuluard, XinqingLi, MarcPlantevit, CélineRobardet, andRomainVuillemot
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