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Big Data Baseball Wig data and analytics are sweeping the business base running, and stealing. 5kinl in fielding is espeworld, and the professional sports industry is no cially valued today. For example, Mike Trout, center exoeption. Baseball, toothall, soccer, hockey, ten-_ fielder for the Los Angeles Angels, is highly cegarded nis, and even sailboat racing are finding ways to by beld team owners because he's an excoptional fielder analyze data about playess ind conpecing teams in and base rumner and an exreptionsily intelligent and big data has revolutionized the game of base- base ball player, even though he lacked stellat staball as we know it, including defensive shifts, swing not whether co use big data in basehall but haw to path changes, and how teams acquire and develop use it effectively, It is not always possible to inters players.GiventhehugedisparitiesinMajorLeagueBaseball(MLB)teambudgets,wealthierteamstypi-ofdatyhavetheadvantageinrecruitingthebestplay-ers.MichaelLewissbookMoneyball,publishedin2003,describeshowOaklandAthleticsmanagerBillyBeanewasabletoturntheunderdogAsintoawin-ningteambyusingbigdataanalyticstoguidedeci-sionsaboutwhichplayerstorecruitandcultivate.Rigorousstatisticalanalysishaddemonstratedthaton-basepercentageandsluggingpercentagewerebetterindicatorsofoffensivesuccess(andcheapertoobtainontheopenmarket)thanmorehistoricallyuseiteffectively.Itisnotalwayspossibletointer-pretthedataandseparateoutwhatis"noise"andwhatisactuallyactionableinformation.Theamountoverwhelming-pitchusage,swingplanes,spinrates,etc.Whenaplayerstepsintothebattersbox,everyhitterisdifferentintermsofhawmuchinformationthatpersoncanabsorbbeforegettingboggeddowninit.Somewanttoknowwhatapitcherwilldoincer-tainsituations-whatpitchcsthepitcherwilluseandhowoftenthatpersonusesthem-whilesomewanttojuststepinwithaclearheadandlookfortheball.Theresonlysomuchdataapersoncanusewithoutdissectingtoomuchandgettingtoodistractedfrom to obtain on the open market) than more historically dissecting too muct valued qualities such as speed and contact. These valuedqualitiessuchasspeedandcontact.Thesespbservationsflewinthefaceofconventionalbase-ballwisdomandthebeliefsofmanybaseballtalentscoutsandcoaches.BeanerebuilttheAsbasedonthesefindings,producingaconsistentlywinningteamforanumberofyearsbyusingadvancedana-lyticstogaininsightsintoeachplayersvalueandcontributiontoteamsuccessthatwealthierteamsbadoverlooked.BigdataiscreditedwithhelpingtheBostonRedSoxwintheWorldSeriesin2004andtheSt.Louisthetaskathand.Manybaseballexpertsstillbelievethattradi-tionalmethodsofplayerevaluation,alongwithgutinstinct,money,andluck,arestillkeyingredientsforwinningteams.Forexample,theSanFranciscoGiantsusebigdataandstatistics,butalsobasetheirplayerrecruitmentdecisionsontheopinionsofscoutsandcoaches,AcoordingtoGiantsbenchcoachRonWotus,numbersreallycanttellthewholestoryaboutthequalityoftheplayer;sotheGiantsinte-gratestatisticaldatawithscouting,coaching,and Cardinals win in 2006 and 2011. To varying degrees, player experience, especially when dealing with opevery Major League Baseball team today uses big ponents outside the National League that the Giants. mata and deep analytics to support decisions about_do socts of the game. However, some teams, vidual player's strengths comes more from knowing such as the Pittsburgh Pirates, Chicago Cubs, and the player and his ability as opposed to the statistics, HoustonAstros,wereslowertodosothanothers,fartherfromhomeplatethannormalattimes,whileWotusbelieves.Shortstopswithgoodarmscanplay and suffered lackluster performance until they em- farther from home plate than normal at times, braced big data more fully. Findings from big data analytics have changed the usual. There are nuances to defending the opposition importance baseball teams attach to specific skills of that are not statistically related, but statistics help players. Skills that previously could not be quantified when you don't know players well enough to know are now receiving more attention, including fielding, what to expect from them