RONSHANDLER

TheBABSPROJECT3.0

BOOK1

WhyWeNeedaNewSystem

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LastUpdate:January1,2020Copyright2020,TheShandlerCompany,LLCAll rights reserved. No part of this publication may be reproduced, resold, distributed, transmitted or displayed for any commercial purpose, including incorporating into a website without the prior permission of the publisher, except for brief excerpts used in reviews. You may not create derivative works based upon the product. This product is intended for entertainment purposes only. Neither the author nor publisher assume any liability beyond the purchase price for any reason. The Shandler Company, LLC Port St. Lucie, FL baseball@ronshandler.com

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BOOK1-CONTENTSIntroduction MyConversationwithYou 4

Chapter1 HowtheStatsareOuttoGetYou 7

Chapter2 HowtheMarketplaceisOuttoGetYou 17

Chapter3 HowYourBrainisOuttoGetYou 24

BOOK2 TheBroadAssessmentBalanceSheet

BOOK3 BABSinPractice

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WhyFantasyBaseballWinnersLoveBABS

"Fantastic,thoughtprovokingstuff,evenforagrizzledveteranof31consecutiveRotoseasons.Isuspectaquarterofacenturyfromnowitisthisstuffthatyouwillberememberedandreveredfor.WhatdidEarlWeaverliketosay?It'swhatyoulearnafteryouknowitallthatisimportant.Thatcouldbeyouraptsubtitle."–J.Morgan"Ijustwanttomakeastatementhereofsimplegratitude:yourthoughtsandsystems—theForecaster,andnowBABS—havegivenmeeffective,analyticaltoolsIcanuseinconstructingmyfantasyteams,whichisaformofintellectualplaythatIfindimmenselyfun.Hugelyfun.So,aresoundingthankyou."–B.Crenshaw"Ithadneverinalltheseseasonsoccurredtometoseethepatternsasthewayplayersaremostlyallalike.Ihadalwayslookedfordifferences.Revolutionarythinking."–D.Emerson"IwanttothankyouandBABSforescortingmetoachampionshipthisyear.Thiswasthe27thyearofourverycompetitiveleague.Ihadfinishedtiedforfirsttwiceovertheyearsbuthadneverwontheleagueoutright.I’manumbersguy,whichiswhyIwasturnedontoyouatHQ,butthatmadeithardtogetcomfortablewithBABS.ButthesystemdefinitelyhelpedandIlookforwardtoitscontinueddevelopment."–B.Wentz"Wow.That.Was.Awesome.I'mcompletelysoldonthesystem,therankingprocessandthespreadsheetthathelpsputitalltogether."–D.Morris

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TheBABSProjectIntroduction

MyConversationwithYouME:Hey,welcome.

YOU:HiRon.Iseeyou'reback.What'sup?AneweditionofTheBABSProject.ThepreviousbookseemedalittledauntingtosomereaderssoI'vedivideditupintothreemini-booksandtriedtostreamlinetheBroadAssessmentBalanceSheet(BABS)programabit.

Istherealotdifferentfromtheoriginalbook?It'ssomewhatthesame,Ithink.I'vesplittheoriginalincarnationintomoreeasilydigestiblesections.ThenIaddedabunchofnewstuff,updatedsomeotherstuffandclarifiedstuffthatwasconfusing.Theclarificationsledmetomakeafewotheradditionsanddeletionstoaidinusability.Hmm…inretrospect,it'snotsomewhatthesame.Itis,butitisn't.

Stillconfusingreaders,Ron.Um,okay.I'lldobetter.InPartOne–"WhyWeNeedANewSystem"–Iamgoingtopresentyouwithlonglistsoffactsabouthowbadweareatpredictingthefutureandhowwearemisusinginformation.Weprobablyknowandacknowledgethesefactsindividually.We'llnodourheadsandsay,"Yeah,projectionsarenotgospel.Igetit."Butno,wereallydon'tgetit.Weknowthatbaseballcultivatesaloveaffairwithstatistics.But,thosenumbersworkbestindescribingwhathasalreadyhappened.Usedcorrectly,theydoaterrificjobofthat.Butwetakeamassiveleapoffaithinproclaimingouraptitudeassoothsayers.Yes,paststatisticscanbemanipulatedtoprojectfutureperformance,butwithinaverywiderangeofoutcomes.Extraordinarilywide.Theproblemis,forourfantasyleagues,weneedfarmoreprecisionthanwecancurrentlyachieve.Yetwecontinuetogointoeachseasonwithmeticulously-craftedrankingslists,playervaluesandtargets. Areyousayingthatallmydraftprepisawasteoftime?It'snotacompletewasteoftime,butweputfartoomucheffortintotheprocessandfartoomuchcredenceintheminutia.Westilllookata40-HRperformance–or40steals,or200strikeouts,etc.etc.–andfixateonthosenumbersasiftheyholdsome

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religioussignificance.Wearestillseducedintomakingimportantdecisionsbasedonthewildallureofsmallsamples.Westilltrytoferretoutpatternsinthestats,evenifwhatwe'relookingatismostlynoise.Westilllookatresearchresultsbasedonaggregatedataanddrawfiniteconclusionsaboutindividualplayers.Andrecencybias?Oh,don'tgetmestarted.Ashardasitistocomprehend,thereisoftennotasignificantdifferencebetweena3rdroundplayerandan8throundplayer,orbetweena$19playeranda$9player.AndyetweagonizeoverADPsandengageinauctionbiddingwars.PartOneisintendedtomakeusawareofthefallibilityofourinformation,whichcreatestheneedforanewdraftpreparationprocessthatgivesusmorecontrol.InPartTwo–"TheBroadAssessmentBalanceSheet"–I'lldescribethenewsystem(BABS)andhowitworkstoresolvetheissuesoutlinedinPartOne.BABSlooksattheprocessofbuildingacompetitivefantasybaseballrosterthroughanunorthodoxlens.Foroverthreedecades,we'vetakenabottom-upapproachtorosterconstruction,focusingonprojectingplayerperformanceandthenbuildingfromthere.BABStakesatop-downapproach,focusingonthestructureoftherosteritself,andthenfillinginthepieces.Afterall,winningisnotaboutnailingprojections;it'saboutweighingskillversusrisk,anduncoveringprofit.Itdoesn'tmatterifyouthinkMikeTroutwillhit48HRs,or38,or28.Youmightberight;you'llprobablybewrong.Itmattershowhisoverallprofilefitsintoawell-constructedroster.OnDraftDay,successfullyreachingstatisticaltargetsprovidesfalsecomfort;howmanypost-draftstandingsprojectionsevercometrue?Butcreatingasolidfoundationandstructure,andthenbuildingitoutbybalancingassetsandliabilitiesprovidesahigher-levelperspectivethatallowsforbetterrostermanagement.Finally,inPartThree–"BABSinPractice"–weputBABStowork.We'lllookathowyoucanusethesystemandadaptittodifferentgameformatsandsituations.Backinthe1990s,thegreatestadvantageyoucouldhavewaspossessingbetterinformation.Theinternetleveledthatplayingfieldandleftuslookingforothercompetitiveedges.Overthepast25years,we'vegonethroughnumerousiterationsinvolvingstatisticalmodeling,newsimpactanalysisandevengametheory,butthegoalwasalwaystogetbetterplayerprojections.Thisisdifferent.That'swhyyouneedBABS.

Geez,itsoundslikeyou'retossingoffalltheyearsofresearchyou'vedoneintheBaseballForecasterandonBaseballHQ.com.

No,notatall.TheBaseballForecasterisstillthebibleoffanalyticsandprobablythemostimportantresourceforsettingbaselinesforplayerperformance.BaseballHQ

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stillprovidesthedeepestfantasy-baseball-relevantinformationanywhereandistheonlyonlinesourceofthiscaliberthatis100percentbaseball,24/7/365.TheyarestillkeyinputstoBABSandtheplacesweneedtogotofindaccurateskillsassessment.That'sthefoundationuponwhichBABSisbuilt.Itisstillimportanttobeabletoevaluateperformanceinitscomponentpartsandunderstandhowthatrelatestothesurfacestatswithwhichweplayourgames.Thedifferencehereisthat,oncewe'vedonethatevaluation,Idon’twanttomaketheleaptoastatisticalprojection.IntheForecaster,wedoallthatevaluationandthenareforcedtocullitdowntoasinglelineofnumbers.I'vealwayshateddoingthat,butweneedthedataforourdraftprepsowekeeppublishingthosenumbers.However,likeIwriteintheConsumerAdvisoryinthefrontofthatbookeachyear,therearefarmoreimportantthingstolookatbeyondthatprojectedstatline.SowithBABSIgettosay,"Sorry,I'mnotgoingtodoit."IfyouabsolutelyneedtoknowhowmanybasesTreaTurnerisgoingtostealsoyoucanplugitintoyourfantasymodel,feelfreetogoelsewhere.Youwon'tfindthatnumberhere.Butifyou'reatleastcuriousabouttryingadifferentway,well,that'swhyyoumustbereadingthisrightnow.

Sorry,butI'mnotgoingtogiveupmystats.SoamIgoingtogetanyuseoutofthisbook?

Youdon'tneedtoabandonyourstatsbutyou'llhavetobewillingtotryrelyingonthemabitless.WithBABS,playersarenotstat-producingmachines;infact,theyarealsoprettyflawedashumanlifeforms.Ratherthanattemptingtofigureoutwhattypeofnumberstheyaregoingtoputup,myfocusisondescribingtheminthemostaccuratenon-statisticalterms,andthenassemblingtheseformlessentitiesintoproductiverosters.

Soundslikeyouaretryingtoreinventhowtowinatfantasybaseball.Thatseemsoverlyambitioustome.

InevershyawayfromachallengewhenIbelievethereisabetterwaytodosomething.AndIdobelievewe'vebeendoingthingswrongforaverylongtime.It'simportanttonotethatTheBABSProjectisintendedtobean"evergreen"referenceresource.Theexamplesandexhibitsarefromtheperiod2015-2019andarepresentedingeneralterms.Thatmeansthisbookdoesnotincludeanyplayerratings,rankingsorcheatsheetsfortheupcomingseason.Allthattime-sensitivedata,forthisyearandallfutureyears,appearsonlineatBABSbaseball.com.

Okay,howdowestart?Let'sstartwithabunchofharshrealitychecks.

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TheBABSProjectChapter1

HowtheStatsareOuttoGetYou"Thisisaverysimplegame.Youthrowtheball,youcatchtheball,youhittheball.Sometimesyouwin,sometimesyoulose,sometimesitrains."NukeLaloosh,BullDurhamThestructureofthegameofbaseballlendsitselftoanalysis.Theresultofeachat-batisanindividualeventthatcanbemeasured.Butthismeasurementisalwaysafterthefact.Wecancounthowmanyhomerunsaplayerhits,butthatisonlyafterhe'shitthem.Theproblemcomeswhenwetrytotakethenextapparentlylogicalstep.Ifaspecificeventchroniclesareal,measurableskillandwecancountitandtrackitstrendsovertime,thencan'twealsopredictit?No,notreally,atleastnotwiththelevelofprecisionnecessarytohavemeaningfulcontroloverbuildingafantasybaseballteam.Buteveryyear,thequestcontinuestocreate,enhanceandfine-tunepredictivemodels.

Again,areyoudissingalltheworkwe'veputintoadvancedbaseballanalysisovertheyears?

No,thereisnothingwrongwithmoreandbetterdata.ThemetricsintheBaseballForecaster,atBaseballHQ.com,now-mainstreamsabermetricgaugeslikeWARandwOBA,advancedgranulardatafromPitchF/X,Statcastandheatmaps–areallvery,veryimportant.Thebetterthatwecandescribetheelementsofperformance,thebetterwecanassessskill.Thenweoftentakethenextstepandtrytousethosemethodstovalidatestatisticaloutput.That'sareasonableexercisetoo.Yes,aplayermighthit40homeruns,butwhenwedeconstructeventsintogranularcomponentssuchascontactrate,exitvelocity,trajectoryandbattedballdistance,wecangetasenseofhow"real"those40HRswere.Wecandeterminewhethertheplayer'sskillsetsupportedthathomerunoutputingeneralterms.That'sstillusableanalysis.Butthenweoftentakeitasteptoofar;wetrytoattachanumbertoit.Weanalyze:"Basedonthecomparableexitvelocityofallotherplayers,heshouldhavehitthreemoreHRs,allthingsbeingequal."Wedrawtheseconclusionsfromthevariancesbetweenexpectationandreality,basedonassumptionswemakeaboutunderlyingskill.Andweexcusethefallacyoftheexercisebyaddingthefauxqualifier,allthingsbeingequal.

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Butallthingsareneverequal.Youcanneverreplicateoneseason'sperformanceinanotherseason.Conditionsarealwaysdifferent.Sowhilethisisaninterestingexercise,itprovideslittleactionableinformationwhenitcomestosubsequentyears.Tellmethattheindicatorspointtoanincreaseordecreaseinskills,showmetheareasofgrowthorerosion,evengooutonalimbandtellmethataplayerisgoingtofalloffacliff–butdon'ttellmethataplayerisgoingtohit37HRs.Don’ttellmeheisgoingtosteal45bases.Don'teventellmethatheisgoingtohaveanERAsomewherebetween3.25and3.50. But,but…weneedthosenumbers.Iknow–weneedthosenumberstoplaythegame.Wemusthaveplayerprojectionsandweneedtoconvertthemintodollarvaluesorrankingpositions.Weneedtobuildbudgetsandrosterplans,andsetstatisticaltargetsbasedonallthisdata.Thatiswhatwe'vealways"needed."Butnomatterhowexhaustiveajobwedoinassemblingourdraftprepmaterials,thenumbersweusetoplanoutourrostersarealwayswrong.Checkitoutyourself.Lookbackatlastseason'sprojectionsoneventhestableplayers.Theyneverhitexactlytheprojectednumber,andoftenit'snotevenclose.AplayerlikeMikeTrout,whohasbeenonthetopoftheleaderboardformostofthepastdecade,haspostedverydifferentnumberseachyear.Evenwitharangetoworkwith,thefinaloutputisalmostaslikelytoendupsomewhereoutsidethatrangeasinsideit.

Yes,noprojectionisgoingtobeexact.Butcan'tweexpectthattheover-projectionsandunder-projectionsaregoingtoevenoutacrossanentireroster?

No,wecan'texpectthatatall.Infact,yourleague'swinnersandloserswillmostlikelybedeterminedbyabasicreportcardofoversandunders.Theteamwiththemostorbiggestover-performerswillalwayshavethebestoddsofwinning,regardlessofhowcloseyourprojectionswereoverall.Truestory:Backinthe2015FSTAexpertsleague,myoveralldraftreportcardwasprettydamning.Ihadfiveon-parpicks,nineprofitablepicksand15outrightlosers,includingsixinthefirsteightrounds.Byallrights,thisteamshouldhavebeenadisaster.Butmyninewinnerswerebigwinners,includingthebreakoutyearsofJakeArrieta(9thround),J.D.Martinez(14),MannyMachado(15),XanderBogaerts(16)andDallasKeuchel(19).Ifinishedonedayandtwopointsshortofatitle,eventhoughmyoverallprognosticatingprowesswasawful.Sowereallycan'trelyontheprojectionsgettingustowhereweneedtogo.Yeteveryspringwegobackthroughthesameprocessalloveragain.

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Well,ofcourse.Whatelsecanwedo?Well,let'sstartbyrecognizingwherewetendtogoastray.Youwouldn'tknowitfromallthisextremeanalysisgoingon,butbaseballisasimplegame.Evenfantasytendstodigfardeeperintotheminutiathanisnecessary.Hereisarundownofmanyofthelessons,truismsandproclamationswe'vemadeovertheyears.Somanyacceptedtruths,somuchofitmisguided.Thesearethecliffswekeepstumblingoff.Therearesomanywaysthatwearelookingatthingsincorrectly.Thefollowingresearchfindingsareallvalid;thecitedauthorsarefromtheBaseballForecaster,BaseballHQ.comandothersources.Ifnoauthoriscited,it'smyownresearch.StatisticalBaselines:AreTheyReal?Withthetoolscurrentlyavailabletous,themaximumprojectiveaccuracywecanhopetoachieveis70percent.Thisisanumberthatwe'vebeenthrowingaroundforalongtime.Butwhatthatmeansis,thebestwecanhopetobeis30percentwrong.Thirtypercentisalot!Itmeansbeingoff,onaverage,bynineHRsfora30-HRhitter,60strikeoutsfora200-Kpitcheror12savesfora40-savecloser.That'sthebestlevelofwrongnesswecanexpecttoachieve.Andfewofuswilleverachieve"best."

Seriously?Isthistrue?

Eh,Idon'tknow.That'sthenumberwe'vebeentossingaroundalltheseyears,andfrankly,Idon'trecallhowtheyarrivedat70percent.It'spossibletherecouldbeasystemthatexceeds70percentbutIdon'tknowthatyou'dbeabletoproveit. Why?Becauseoneseasonrepresentsonlyasingledatapointforanalysis,andthatissimplynotenough.Everyyear,wegainnewknowledgethatcompelsustoimproveandfine-tuneourforecastingmodels.Amodelweusedin2019mightbecompletelyoverhauledby2022.However,that2019modelmighthavebeenmoreaccurateoverafiveor10-yearperiod.Wenevergiveourselvesachancetofindout.What'smore,giventhatthestatisticallandscapeisalwayschanging,we'relikelynevergoingtohavedatathat'sstableenoughtodeemanymodeloptimalanyway.Ifwemadeadjustmentstoa2014modeltoaccommodatethe2015season,oddsareitwouldbeacompletefailuregiventheoffensivesurgethatyear.Andthenifweappropriatelyprojectedregressionfor2016,we'dhavebeenwrongagain.Wherewouldwegofromthere?

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Maybeyoucan'tevaluateanentireseasonofprojectionsonamacrobasis,butwhataboutindividualplayers?That'sallthatmattersforusanyway.

Sure,wecantry.Thereareoverallskillsmetricsthatareconsideredgoodevaluatorsoftalent,likeonbaseplusslugging(OPS).Butlet'ssaythatIprojectaplayertohaveanOPSof.840andheendsupwithanOPSofexactly.840. Um,thatwouldbegreat!Except,this:

2019 HR SB BA OBP Slg OPSAdamEaton 15 15 .279 .365 .427 .792KoleCalhoun 33 4 .232 .325 .467 .792

IfIprojectedCalhounnumbersandheproducedlikeEaton,I'dhardlycallthatasuccessfulprojection.ButOPSthinksso.Therearedozensoftheseeveryyear.Baseballanalystsusevariousstatisticalprocessestocomparetheaccuracyofonesetofmetricstoanother.You'llseethesemethodsusedtomeasuretheaccuracyofplayerprojectionstoo.Therearefrequentstudiesthatinvolveagroupofforecasters,oftencomparedtoacontrolgroup–oftenasimpleage-adjusted,weightedthree-yearaverage(theMarcelMethod)–andtoeachother.Usingtheresultsofthesestudiestodeterminethebestsystemhaslittlevalue.Thetestgroupstypicallycoverhundreds,orthousands,ofplayers.Thevariancebetweenanyonesystemandanotherusuallyamountstopercentagepointsovertheentirestudygroup.It'snotsomethingthat'sgoingtoprovideanybenefitforatinysampleof23playersonafantasyroster.Thereisnowaythatyoucancoveryourriskofvolatilityoverarostersizeofjust23players.ThisisapointIamgoingtocomebacktoseveraltimes.About15yearsago,beforeweweresmarter,aleadingwebsiteoncepublishedacomparativeanalysisofabunchofforecastingsystems,usingthestatisticalmeasuresofcorrelationcoefficient,meanerrorandrootmeansquarederror(don'tworry,you'renotgoingtobetestedonthis).Theirresults: Mean

Correl Error RMSESystemA .690 .067 .084SystemB .694.066.084SystemC .711.064.085SystemD .692.067.085SystemE .683.068.086SystemF .715.064.081SystemG .672.071.091

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Forwhatit'sworth,SystemCwasdeemedmostaccurate,thewinner,theprognosticationchampion!(Theywerealso,coincidentally,thepurveyoroftheanalysis.)Evenwithoutthebias,thereisnowayforyoutoleveragethatminutevarianceinaccuracyoverjust23players,or40,orevenseveralfantasyrosters'worth.Soyoucanpickalmostanysystemandhavejustasgoodofachanceofwinningasanyother.TheTruthAboutVolatilityAccordingtotheresearchofPatrickDavittofBaseballHQ.com,normalproductionvolatilityvarieswidelyoverany150-gamespan.A.300careerhittercanhitanywherefrom.250to.350,a40-HRhitterfrom30-50,anda3.70/1.15pitcherfrom2.60/0.95to6.00/1.55.Alloftheserepresentnormalranges.Soifabatterhits31-.250oneyear,36-.280thenextyearand40-.310thethirdyear,youdon'tknowwhetherthatisgrowthornormalvolatility.Infact,thelow-endand/orhigh-endpointscouldbeisolatedoutliers.Butnearlyeveryonewillseeitasatrendandcallitgrowth.AprojectionforyearNo.4willeithercontinuethisperceivedtrendorshowsomeregression.Andanyoneofthemcouldberight.Orwrong.ItactuallywouldbealoteasierifeveryplayerperformedlikeChrisDavisdidearlierinhiscareer:

Year HR BA OBP Slg R$2012 33 .270 .326 .501 $182013 53 .286 .370 .634 $362014 26 .196 .300 .404 $82015 47 .262 .361 .562 $262016 38 .221 .332 .459 $12

IloveChris.Hedidn'thidehisvolatility.Itwasall-clothes-off,outthereintheBaltimoresun.Hetrumpetedthefactthattherewasnowaytopinhimdown.Washea.220hitterora.270hitter?Couldweexpect30HRsor50HRs?Butwhilethisdatasetwasimpossibletoprojectintothefollowingseason,itwasnearlyconsistentwithinanormalrange.Infact,2014lookslikeaslightoutlierinthisparticularscan,buthissubsequentcareerprovedthatitwasn't.Youprobablycouldn’tconvincemanypeople,butthisisprettymuchthesameplayereveryyear. I'mstartingtopullmyhairout.Completelyunderstandable.Butthere'smore.Researchhasshownthat150games,oraboutthelengthofasinglebaseballseason,isnotenoughofasamplesizetobeareliableindicatorofskillforsomestatistics.

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Forinstance,astatlikebattingaveragedoesn'tprovideareasonableapproximationofaplayer'strueskillleveluntilabout910AB,accordingtoRussellCarleton.Sowedefinitelycan'tdrawconclusionsafteroneseason.Youcan'tlookatabatterwhohits.230oneyearand.270thenextandcallthat"growth."Whatyou'dmorelikelycallthatisa.250hitter.MyfriendChris?Atthepointinhiscareershownabove,hewasyourbasic.240shitter,eventhoughhe'dneveractuallyhadabattingaverageinthe.240s.Butwhatdoes.240meananyway?Or.300?Or.250,or.200?Thelinewedrawinskillsbenchmarksisincrediblygrey.

• We'llchasea.300hitterasbeingsignificantlybetterthana.250hitter,however,over550AB,thedifferenceisaboutahitaweek.

• Thedifferencebetweena.272averageanda.249average–stillperceptivelydifferent–istwohitspermonth,orahiteveryotherweek.

• We'lloptforapitcherwitha3.95ERA,passingoveronewitha4.05ERA.Butwhat'stherealdifference?Apitcherwhoallows5runsin21/3inningswillseeadifferentERAimpactthanonewhoallows9runsin3innings,eventhough,forallintentsandpurposes,bothgotrocked.Thatcouldbeyour0.10varianceinERArightthere.

Thelinewedrawbetweensuccessandfailureisalsoincrediblygrey.

• AbatterwhoseHRoutputdropsmighthavehadaconcurrentincreaseindoublesandtriples.

• ApitcherwhoseERAspikesmayhaveseennodegradationinskillsbutwasbackedbyapoordefenseandabullpenthatallowedmoreinheritedrunnerstoscore.

• AspeedstermayhaveseenhisSBtotalplummetonlybecausehewastradedtoateamthatdidn’trun.

• Aclosermayhavebeenaseffectiveaseverbutlostthe9thinningroleasaresultofatradeoramanagerwithaquickhook.

It'slikenothingisrealanymore.Oh,it'sreal.Theissueishowyouinterprettheserealities.I'mtryingtomakeacasethatourtrusted,comfortablestatisticsarenottheplacetofind"real."Thisbecomesmoreproblematicwhenwetrytoprojectthefuture.Garbagein,garbageout.Andhonestly,beyondthevolatilityinthenumbers,thereistoomuchuncertaintyformanyplayerstopindownastatlineanyway.

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• Howdoyouhandleplayerscomingoffofaninjury-marredseason?• Canyoureasonablypro-rateamid-seasoncall-up'sstatlinetoafullseason?• Islastyear'spitchingbreakoutstarreallynowinthesameclassasthe

game'selite?

Idon’tknow.Youdon'tknow.Nobodyknows.Butsomeoneisgoingtohavetoslapabunchofnumbersontheseguysinorderforyoutodraft,right?

Um,right.Well,won’tthey?Theywill,butyoudon'thavetobuyintoanyofit.HereisafactthatI'vesaidoften:Thetwomostpowerfulforcesknowntomanareregressionandgravity.Ifyou'reeverfacedwiththequestionofwhethertoprojectaplayertoimproveordecline,thebetterpercentageplaywillalwaysbeDECLINE.Butthatrunscountertowhatwewanttoseeinourplayers.That'swhywearesoinfatuatedwithupwardlymobilerookiesandanydatathatevenremotelyhintsatimprovement.Wecravesleepers!Bringmemoresleepers!TheLogicalTruthsAboutPEDsIhatewritingaboutthis,especiallysincethetopiccyclesinandoutoftheheadlineseachyear.Andreally,theperformance-enhancingdrugsthemselvesarenottheissueasmuchastheirimpactonthestatisticsthatdriveourgame.Whilethereremainsdisagreementamonganalystsabouthowrealormeasurablethatimpactis,therearefivelogicaltruthsthataretoughtodeny.1.Peoplearegenerallyhonest,exceptifit'sachoicebetweenhonestyandsurvival.2.Forproathletes,survivaloftenequatestomaintaininganedgetostaygainfullyemployed.3.IfPEDsdidnotimproveorsustainperformanceinordertogiveathletesanedge,whywouldtheyaccepttheriskofusingthem?4.Thedruglaboratorieswillalwaysbeonestepaheadofthedrugtesters.5.Youcan'tdismissthepossibilitythatanyradicalswinginproductivitycouldbecausedbyaplayer'suseordiscontinuanceofPEDs.

Ugh.IhatetalkaboutPEDs.Areyoutryingtosaythatallplayersaremotivatedtocheat?

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No.Butit'syetonemorevariablethatputsthe"realness"ofallstatisticsatrisk.Andunfortunately,it'snaïvetothinkthatthelackofdailyPEDheadlinesmeanstheproblemhasbeencontained.Theabovetruthsdon'tchange;neitherdoestheefforttocoverupPEDuse.

ButwhataboutallthoseminorleaguersthatwereintheMitchellReport?Aren'ttheyproofthatPEDsdon'twork?

ForanyallegedPEDuserswhofellshortofarealMajorLeaguecareer,it'spossiblethattheyneverwouldhavemadeitoutofrookieballwithoutthathelp.Wedon'tknow.TheimpactofPEDsisrelativetoeachplayer'sactualskilllevel.Thatmeansweneedtoquestionthelegitimacyofperformancestatsthroughouteverylevelofproball.Probablycollegeandhighschooltoo. Ithinkmyheadisgoingtoexplode.Trytohangon.There'sonemorestatvariable.I'vesavedthebiggestoneforlast.TheBlackHoleofPlayingTimeYoucandoalltheskillsassessmentyouwant,butthebaneofourexistencehasbecometheblackholeofprojectingplayingtime.It'sanearlyimpossibletask.

Youmakeitsoundlikeit'sanewproblem.Becauseitisarelativelynewproblem.Twentyyearsago,projectingplayingtimewasjustanothervariablepronetosomenormalvolatility.Itwasnomoredifficulttoprojectthanhomersorstrikeouts. So,whatchanged?ContinuallyescalatingMLBplayersalariesandthecrackdownonPEDsreachedatippingpointinthemid-2000s.Theresult?Withteamsbendingoverbackwardstoprotecttheirhigh-pricedinvestmentsandplayersrunningscaredofgettingnailedbydrugtesters,thesafeharbortostashbodiesbecametheDisabled(nowInjured)List.In2007,thenumberofILdaysspikedfrom22,472to28,524.Fiveyearslater,itcracked30,000.Afterafewyearsaround31,000itspikedagainto34,284in2018andthento36,394in2019.EachtimeaplayerhitstheIL,itcreatesanopeningforanotherplayertofillthevoid.MoreILstintsmeanmorenewplayersclaimingapieceoftheplayingtimepie.

Sowhat?Wecan'tbetalkingaboutthatmanynewplayers.

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Well,waybackin1985,about39players,onaverage,wouldappearonasingleteam'srosterduringthecourseofaseason.In2018,thatnumberhit54.Whilethenumberofplayersseeingmajorleagueactioneachyearisrising,thenumberofgameshasremainedthesame.Eachteamstillplays162games,whichgeneratesanearlyfixednumberofoutsandinnings,andaverynarrowrangeofplateappearances.Thesedays,availableplayingtimeisthesamebut15moreplayersperteamarefightingforapieceofit.We'vebeengoingintoour15-teamdraftswithprojectionsallotting6500ABand1450IPofplayingtimeto345players(15teamsx23playersperteam).Butwereallyneedtoallotthosesameat-batsandinningstothenumberwhoareactuallygoingtobeseeingthatplayingtime,whichismanymore.Ifwefailtoaccountforthatreality–andarenotatleastreasonablyaccurateinthateffort–thefalloutishuge:In2018,60percentoftheADP'stop300playerslostplayingtimeduetotheinjuredlist,demotion,suspensionorrelease–arecordforsingleseasonattrition.Sinceplayingtimeisazero-sumproposition,thoselostABandIPhadtogosomewhere,andinfact,morethan70percentofthemostprofitableplayersweredrivenbyunexpectedincreasesinplayingtime.Theopportunityforthoseplayingtimeincreaseswaslargelydependentonexternalevents,virtuallynoneofwhichwerepredictableonDraftDay.Andso,morethan70percentofeachseason'smostprofitableplayerswereunpredictableonDraftDay.Asyouwouldexpect,thesemostprofitableplayershadadisproportionatelylargeimpactonwhowontheirleagues.Researchshowedthat25percentoftheteamsowningoneormoreofthemostprofitableplayerswontheirleagueoutright.Oneoutoffour!Morethan50percentofthoseteamswiththemostprofitableplayersfinishednolowerthanthirdplace.Thebiggestdrivingforcebehindallthat–changesinplayingtime–wasunpredictableonDraftDay.

Wow.So,allinall,areyoutellingmethat,despiteallthemassiveeffortwe'vebeenexpendingtoconstructelaboratesystemstoprojectplayerperformance,noneofthenumberscanbetrusted?

Well,wecanalittle,butnotenoughforittomatter.Backin2010,Iasked12ofthemostprolificfantasychampionsinhighstakesleaguesandnationalexpertscompetitionstoranksixvariablesbasedonhowimportanttheyweretowinningconsistently."Moreaccurateplayerprojections"cameindeadlast.

Whatdidtheysaywerethemostimportantvariablesforwinningconsistently?Hereweretheresults:

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1.Betterin-draftstrategy/tactics2.Bettersenseofvalue3.Betterluck4.Bettergraspofcontextualelementsthataffectplayers5.Betterin-seasonrostermanagement6.MoreaccurateplayerprojectionsTherewasactuallyaseventhvariablebroughtupbyLarrySchechter–betteruseandaccesstotime.Hesaidthatthemoretimeinvestedintheentireprocess,thebettertheresults.Researchsupportsthefactthatbetterdecisionsaremadewhenmoretimeistakentoanalyzetheimportantinputvariables.Larry'strackrecord–sixToutWarstitles–certainlysupportsthat.Buthere'saquestion:Canyoubuildasuccessfulteamwithoutstatisticalplayerprojectionsatall?Givenhowfaultythosenumbersare,itisaquestionweneedtoanswer.Butfirst,weneedtodiscusssomemoreobstaclestosuccess.

17

TheBABSProjectChapter2

HowtheMarketplaceisOuttoGetYouImaginethatwehavefiveplayerswiththeexactsameprojection:

AB HR SB BAGeorge 600 25 10 .275Herman 600 25 10 .275Willie 600 25 10 .275Joe 600 25 10 .275Hank 600 25 10 .275

Inthiscase,itwouldn'tmatterwhichplayeryoutook,right?

Well,sure.Iguess.MaybeyoumightdrawadistinctionbasedontheteamWillieplayson,orHank'shomestadium,orsomeothervariable.Andevenifthisdatarepresentedsomestatisticalmeanoutcomeorgeneralconsensusofpotential,thepointremains:atminimum,thesefiveplayersareexpectedtoproduceroughlycomparablenumbers.Butweknowtherearevariablesthataffectperformance,eveniftheyarenotblatantlyreflectedinthenumbers.Thosevariablesoftencomeoutinthemarketvaluesoftheplayers.Oncefantasyleaguersstartearlydraftsorrunningmocks,itwouldnotbeunusualtoseeourfiveplayersrankedlikethis:

ADP R$ AB HR SB BA37 $28 Joe 600 25 10 .27539 $27 Willie 600 25 10 .27543 $25 George 600 25 10 .27559 $20 Hank 600 25 10 .27576 $16 Herman 600 25 10 .275

Nowthemarketplacedetermineswhichplayersarethebetterpicks.Perhaps:

• Joewasaconsistent.250hitterwhohada.350runinSeptember.• Willieisridingsomemajorrookiehypeandhadagreatspring.• Georgeisa30-year-oldveteranwho'sputupthesenumbersconsistently.• Hankhadacareeryearlastseasonandisexpectedtoregress.• Hermanwasa35-HRhittercomingoffofJanuarywristsurgery.

Whenalltheinputsconverge,thenumbersmayenduplookingthesame,butthemarketplacehelpsrevealthenuances.Still,allthatmattersiswhatnumbersthese

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playersaregoingtoaddtoyourbottomline,soifallfivearegoingtoendupinthesameplace,doesitreallymatterwhichoneyoupick?

Well,theywon'tallendupexactlythesame.Thenuancesthatthemarketshowsusareimportanttoseparatethem.

Ifonlythatwastrue.Theproblemis…themarketplaceisgenerallywrong.

• Joe'sSeptembercouldhavenoimpactonhisperformance.• Williecouldbeover-hyped.• Georgecouldbefacingthebeginningofhisdeclinephase.• Hank'scareeryearcouldbethebeginningofanewlevel.• Herman'swristcouldbecompletelyhealed.

Wethinkweknow,butit'sallspeculation.Let'stakealookathowthesedraftrankingscomeaboutinthefirstplace.Itexplainsalot…Itallstartsintheearlyfall,whenagroupofpeopledecidestohavea"waytooearly"mockdraftforthefollowingyear.Sometimesthistakesplaceevenbeforethecurrentseasonends(whichleadsmetobelievethesemightbefolkswhoseteamsarealreadyoutofcontention,whichpotentiallyaddsalayerofbias).Thesearethefirstpioneersofthefutureseason'sAverageDraftPositionrankings.Then,someofthespringannualshaveearlydeadlines(Decemberforsome)andhavetoconducttheirmag'smockdraftaroundThanksgiving.It'smereweeksafterthelastoutoftheWorldSeries,wellbeforetheWinterMeetingsorwhenfreeagentshavestartedtosign.Someofthemagmock'sparticipantsmayusetheresultsofthepioneermocksasaguide;it'stoughtotell.Theseearlymocksandearlymagshavetorelyonsomethingtorankplayers.Thatsomethingistypicallytherecencybiasofthepreviousseasonandspeculationaboutcontextualvariablesthatmightaffectthefollowingseason.Somenationalcompetitionsopentheirdoorstodraftsasearlyasmid-November,maybeaslateastheWinterMeetings,butstillwellbeforeallthefreeagentshavefoundhomes.Thereisstilllittleinformationtoanalyze,sotheADPsgeneratedbythesedraftswilltendtofeedoffthefirstones,usingthemasbenchmarks,especiallyforplayerswhohaveanuncertainfuture.Thatlastpointisanimportantoneastheuncertainplayersareoftentheonesmostlikelytobequestionablypositionedintherankings.Themoreofthesethatarepublishedoverthewinter,themorethattheearlyranksgainafootingandwestartformingopinionsaboutwhereplayersshouldbedrafted.

19

Therankingsineachsuccessivedraftbecomeself-perpetuating.Beforeyouknowit,wereachcriticalmass.Therankingsbecamelessaboutrealityandmoreaboutgroup-think.Oncespringcampsopen,ourexpectationsareprettymuchlockedin.So,insummary…TheADPsaredrivenbyearlyspeculatorsplantingstakesinthegroundbasedonincompleteinformation.Andallthisisdoneasearlyassixmonthsbeforeeveryonewillbedraftingforreal.Backinthefallof2015,everyonewasexcitedaboutCarlosCorreaafterhislateseasondebut.Afewpeopledecidedtopushtheenvelopewithafirstroundselectioninearlymockdrafts.ThepickgainedtractionovernumerouswintermocksandCorreaneverfelloutoffirstroundconsiderationafterthat.He'dentertheseasonrankedNo.6overall.He'dfinish2016outsidethetop70.Fouryearslater,hehasyettocrackthefirstroundinearnings.TheextentofthefalloutisdescribedinaresearchpieceIwroteforTheAthletic.comin2019.IlookedathowtheADPs–essentially,themarketplace–faredagainstactualperformancein2018.Itexposedsomehorrifyingrealities.ThenIreranthestudyfor2019,publishedinthe2020BaseballForecaster,withsimilarresults.Thefollowingchartsareallbasedona15-teammixedleague,andshow:

Rounds RoundsorrangeofroundsstudiedPar PctofpicksthatearnedthesamevalueasthedraftroundProfit PctofpicksthatearnedmorevaluethanthedraftroundLoss Pctofpicksthatearned1-3roundsworsethandraftroundBust Pctofpicksthatearnedmorethan3roundsworseDisaster Pctofpickswithearningsoutsidethetop750,essentiallyundraftableina

50-roundleague."Disaster"picksareasubsetof"Bust"picksThesechartsrepresenttheaggregateresultsfrom2018and2019. PERCENTAGES

Round Par Profit Loss Bust Disaster1-5 11% 21% 24% 45% 4%

6-10 7% 26% 18% 49% 5%11-15 1% 31% 7% 61% 21%16-20 2% 34% 7% 57% 26%21-25 2% 39% 4% 54% 30%26-30 2% 39% 3% 55% 34%31-35 0% 25% 1% 75% 63%36-40 1% 23% 1% 75% 67%41-45 1% 28% 2% 69% 67%46-50 0% 31% 3% 67% 66%

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Fromthetopofthedraftboard,thereisasteadydeclinethatquicklydevolvesintoamassiveplummet.Andadifferentperspective: PERCENTAGES

DraftStage Par Profit Loss Bust DisasterActive 5% 30% 13% 53% 17%

Reserve 1% 30% 2% 67% 57%Tryingtonailtheexactroundtodraftaplayerisafool'squest–afivepercentplay.

Wow.Thetruetakeaway:"Intheactiverosterportionofthedraft,athirdofourpicksperformedatparorbetter;twothirdsperformedworsethanwherewedraftedthem.Fullyhalfofthemcouldhavebeenconsideredbusts."

Wowagain.SowhydoweplacesuchimportanceonADPs? Nah…IdraftwhoeverIwant.I'mnotswayedbytheADPs.Maybe.ButI'dwageraguessthatyou'remorelockedinthanyouthink.Let'ssayit'spre-season2019andImakeaveryconvincingargumentthatFreddieFreemanshouldbedraftedaheadofNolanArenado.Youmightconsidermyanalysis,andevenifyouagree,youwillbereluctanttochangeyourexpectationsmuch.Why?BecauseallthepublishedanalyseslistArenadoasa1st-rounderandFreemannot.Shandlerisjustonevoiceinacrowdnomatterhowstrongmyargumentmightbe.Andfrankly,youdon'twanttoriskpublicscornbydraftingFreemantoohigh. ButFreemanisnotafirst-rounder.Whynot?Howdoyouknow?Therearemanyplayerswhoarenotconsideredfirst-roundersbutwhocouldbe.InsteadofFreeman,whatifIhadsaidCodyBellinger?I'llbetyoudon'trememberthatthefollowingplayersoncegeneratedfirstroundearnings:AdamJones,HunterPence,ChaseHeadley,CurtisGrandersonandMarkReynolds. MarkReynolds?C'mon.Hewasthe12thbestplayerinbaseballin2009.Ithappens.

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Ican'tstressenoughabouttherealitiesofgroup-thinkexpectations.Asmuchaswemaydenyit,theADPsdoinfluenceourdraftbehaviorandwehavetobeawareofthat. Still,overallwedoaprettygoodjobpickingourfirst-rounders,right?Notsomuch.FACT:ThesuccessrateofADPrankingscorrectlyidentifyingeachseason’stop15players(inanyorder)isonly33.75percent.Infact,thosetop15playersfinishsomewhereinthetop30only53percentofthetime.(Studyperiod:2004-2019)Sohere'sthetakeaway:Whenyousitdownatthedrafttable(oryourcomputer,whatever)andstartagonizingoverwhoisgoingtofalltoyouinthefirstround,thereisnearlyatwo-in-threechancethatwhoeveryouendupdraftingwillbewrong.About10ofthefirst15playerstakeninyourdraftwillnotearnbacktheirowner'sinvestment.

That'scrazy.Okay,here'salittlequiz.Whatdothefollowing21playershaveincommon?

RyanBraunKrisBryantMadisonBumgarnerCarlosCorreaChrisDavisPrinceFielderCarlosGomezAdrianGonzalezCarlosGonzalezJoshHamiltonBryceHarperFelixHernandezRyanHowardAaronJudgeMattKempEvanLongoriaAndrewMcCutchenChrisSaleGiancarloStantonMarkTeixeiraTroyTulowitzki

Lotsofstarsandsemi-starsthere.It'spossibleallofthemwerefirst-roundersat

onetime,Isuppose.

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Yes,theywere.Allofthemwerefirstrounddraftpickssometimebetween2011and2019.Andall21alsoholdanotherdistinction…everyonefinishedtheseasonatleast100spotslowerthanthatfirst-roundADP.DraftedinRound1;earnedbacknobetterthanRound7.It'sjustfurtherevidenceofthevolatilityofstatistics,evenatthetop.

Isitanybetterinauctionleagues?Nah.TryingtofindsomestabilitywithinRotisseriedollarearningsorAverageAuctionValues(AAVs)isnolessfrustrating.FACT:Playerswhoearn$30inaseasonareonlya34percentbettorepeatorimprovethefollowingseason.(MattCederholm)FACT:Pitcherswhoearnlessthan$24inaseasonretainonly52percentoftheirvaluethefollowingyear.Moreexpensivepitchersdoretain80percentoftheirvalue.(MichaelWeddell)That80percentisnicebutitstillmeansyouracepitcher'svalueisgoingtodecline.FACT:Thereisonlya65%chancethataplayerprojectedforacertaindollarvaluewillfinishtheseasonwithinplus-or-minus$5ofthatprojection.Thatmeans,ifyouprojectaplayerwillearn$25andyouagonizewhenbiddinghits$27,thereisonlyabouta2-in-3shotofhimfinishingsomewherebetween$20and$30. SoIshouldn'tworryaboutthoseextrafewbucks?Inmostcases,no.Butauctionpricingisgoingtobemarket-drivenanyway.So,ifyouareconvincedthataplayerisworth$25andlandhimfor$21,youwillhaveoverpaidiftherestofyourleagueseeshimasnomorethana$19player.Evenifheisreallyworth$30.

Arrrgh!Igiveup.AreyousayingIshouldjustpaywhateverforwhoeverandnotworryaboutbudgetsorbargainsorvalueoranything?!

Youstillneedtofollowthemarketandhavearoughbudget,butingeneral,yes.Forecasterswillgiveyouastatlinethatwillsplitthedifferencebetweenhigh-endandlow-endprobabilities.Theyhavenochoicebuttohedge;thereistoomuchrisktocommittoanyoneendoftheperformancespectrum.Reputationsareatstake!Soifallthetopanalystsdon'tknowwhattheheckeachplayerisgoingtodo,clearlytheotherownersinyourleaguehavenoclueeither.Youneedtodecidewhethera

23

playerisworthowningandfitsyourplan,andthenjustfollowthemarket.Mostfantasyleaguersdon'tdraftthatway. Thisisincrediblyfrustrating.Indeed.Ifyouarelookingforvalueretentionorareasonablereturnonyourinvestmentinthisgame,you'replayingthewronggame.

So,thestatisticscan'tbetrustedandthemarketplacecan'tbetrusted.Butwecantrustourownjudgment,right?

Notsofast.

24

TheBABSProjectChapter3

HowYourBrainisOuttoGetYouBeyondeverythingI'vewrittensofar,ourbrainalsoplaysitsowntricksonus.Therearecognitivebiases,nefariouslittlebrainflakesthatsurreptitiouslyderaillogicaldecision-makingprocesses.Weusuallydon'tevenknowwhenit'shappening;that'showeviltheyare.Herearesomeofthemostdamagingpsychologicalpitfalls:Webasedecisionsonsmalldatasamples.Timeforafairytale."Onceuponatime,therewasafringeoutfieldprospectintheTampaBayRayssystemnamedJoeyRickard.TheRaysthoughtsohighlyofthisprospect–whohadslammed13HRsin1,237careerminorleagueABs–thattheylefthimunprotectedinthe2015Rule5draft,wherehewasquicklygrabbedupbytheBaltimoreOrioles.Now,theOrioleshadnoshortageoffringeoutfieldtalentthatMarch.ButRickard'sspringtrainingperformancewasHall-of-Fame-worthy–arobust.397/.472/.571slashlinein63at-bats(withonehomerun)againstamixtureofveteransgettingtheirrustoff,marginalmajorleaguersworkingonanewpitch,andminorleaguersplayinglikeminorleaguers.TheO'sweresoimpressedthattheynamedhimtheirOpeningDaystartingleft-fielder.Thankfully,participantsinthenationalexpertsleagueswerenotfooled.Theyknewthat1,237minorleagueat-batsfaroutweighedRickard'squestionable63-ABsmallsampleMarchperformance.SoRickardwentundraftedinnearlyeveryexpertsleague.Butinthefirstweekoftheseason,Rickardposteda.467/.438/.733line(withonehomerun)in15AB.Thatweekend,morethan50expertsacrosssixleaguesplacedfreeagentbidsfortheO'sstartingleft-fielder,withanaveragewinningbidofnearly$150(outofa$1000budget).Isupposeevenexpertscanlosetheirminds.Allthosepreciousfreeagentdollarsweretossedarounddueto15atbats!Andnotjustany15AB.Itwas15ABagainstthepoorMinnesotaandTampaBaypitchingstaffs.ThearmsRickardfacedinthosecoldBaltimoreoutingshadnameslike

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Santana,Fien,Gibson,HughesandArcher,whocollectivelyposteda7.23ERAin18.2IPthatweek.RickardfinishedAprilwitha.280average,twoHRsandoneSB.HefinishedMaywitha.249average,fourHRsandthreeSBs.Hewascutfromnearlyalltheexperts'rostersbymid-June.TheOriolesputhimontheILwithathumbinjuryinJuly,wherehestayedfortherestoftheseason.Andnobodylivedhappilyeverafter."

Fessup,Shandler.Ibetevenyouplacedabid.Sadly,yes.I'lladmitthatIplacedalosingbidof$57inTout-AL.Intoday'sfantasyenvironment,weallthinkweneedtoatleasthaveahorseintherace.Thereisalwaystheslightestchancethataplayercouldsustaintheirperformancelongenoughtohaveapositiveimpactonyourroster.ButRickard'swinningownersinvested15percentoftheirentirefreeagentbudgetsonaspeculationthat78at-batsagainstquestionablecompetitionweremorelegitimatethantheprevious1,237ABs.Thatdecision-makingshowshowyoucanbeblindedbysmalldatasamples.Wetrytoferretoutpatternswithinstatisticalnoise.Humans(includingyouandI)arehard-wiredtotrytofindpatterns.Initsgrandestsense,wedothistosurvive.Theworldisfullofchaos–eveninnon-electionyears–andit'sthewayourbrainsattempttocreateorder.Baseballanalysisissimilarlyallaboutfindingpatternsindata.Weseeabatterhitting8,10and12homerunsinsuccessiveyears,andweimmediatelylabelthatasagrowthtrend.Maybeitis.Butresearchbackin2010byEdDeCariashowedthattheoddsofthenextdatapointinthatseriesbeing14aresmall.Infact,thegreatestoddsarethatthenextpointregressesbackto10,oreven9.AsdescribedinChapter1,sincethatwedon'tevenknowhowreal8,10and12are,it'sdifficulttoconcludethatthereisanytrendatall.That8-HRyearcouldhavebeen13iffiveofhisdoubleshadtraveledanother5feet.That12-HRyearmighthavebeen9ifnotforthosethreenightswhenthewindwasblowingout.Wefantasyleaguersneedtofindpatterns.That'sthestartingpointfortheentireforecastingprocess.Butwhenthedataitselfissuspect–obscuredingreatmeasurebynoise–maybeit'sbetternottobelookingforsomethingthatmightnotexist.Likebettersentencestructure.

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Let'splayalittlegame. Oo,Ilikegames!Good!Hereisashortseriesofdatapointsrepresentingoneplayer'sRotisserieearningsduringhisfirstthreeyearsinthemajors:$7,$15,$18.TellmewhatyouthinkheearnsinyearNo.4.

Well…itseemslikegrowth,butyouwarnedmeagainstassumingthat.I'lltakethebait.I'llsaythatheearns$16inyearNo.4.

That'saveryreasonableguess.Anyof$14,$15or$16wouldtakeanappropriatelevelofregressionintoaccount.InyearNo.4,thisplayeractuallyearned$23. What?Youtrickedme!Ididn'ttrickyou;thisisanactualplayer.Nothingisever100percent.So,nowyou'refacedwithafour-yeartrend:$7,$15,$18,$23.WhatdoesthisplayerearninyearNo.5?

Okay,nowyou'rescrewingwithme.LogicdictatesthatIsay$19or$20,butyou'vealreadyprimedmetoexpecttheunexpected.I'llsay$25.

Anothergoodguess.Mostanalystswouldprobablyhavestuckwithsometypeofregressedvalue,andIcantellyouthattheForecasterprojectedthisplayertoearn$22inyearNo.5.Butheactuallyearned$28.

Ofcourse.Fourstraightyearsofincreasingearnings–isthisarealplayer?ShouldIbelieveyou?

Youcanchoosewhattobelieve.Butlet'skeepgoing.We'renowat$7,$15,$18,$23,$28.WhatdoeshedoinyearNo.6?

Thereisnowaythiscankeepgoing.I'mgoingtosay$24.That'smyfinalanswer.

Andthatisthecorrectplay.Regressionisalwaysthecorrectplay.TheForecasterprojected$26.Butheactuallyearned$32.

You'replayingme.Youclearlypickedanoutlier…ifheactuallyexistsatall.Well,that'sonethingyougotright.Aplayerwiththisconsistentafive-yeartrendisclearlyanoutlier.Doyouwanttokeepgoing? Sure,whynot?It'sonlyaguessinggameatthispoint.

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Okay.$7,$15,$18,$23,$28,$32.What'snext? Regressionisalwaysthecorrectplay…evenwhenitisn't.I'llsay$29.RememberthatMattCederholmsaid,"Playerswhoearn$30inaseasonareonlya34percentbettorepeatorimprovethefollowingseason."Giventhat,itwouldseemthattheoddsofhimcontinuingtoimprove,orevenholdingsteady,arelow.InyearNo.7,heearned…Waitforit…$28. Hooray!Theplanetsfinallyalign!Doesitkeepgoing?Forsure.Let'sdotwomoredatapoints.$7,$15,$18,$23,$28,$32,$28.It’snolesstrickynow.Was$28anoutlier?Doesherebound?Ordoesthedownwardtrendcontinue?

I'dhavetosayhe'sathispeakandwouldprobablybouncearoundabitforafewyears.I'llpeghisearningsat$30.

Yeah,that'sareasonableassumption.But,no.Heonlyearned$19. $19?!Yougottabefreakin'kiddingme.It'sallreal.$7,$15,$18,$23,$28,$32,$28,$19.Forthelastdatapointinthisexercise,I'llgiveyouonehint:hewas30yearsoldthatseason. Ugh.Thiscouldbethebeginningofthedownslope.Buthe'snotthatoldthathe couldstillreboundalittle.I'llsay…$22.Nah,$14.Forecastingisatoughgame. Morelikeasucker'sgame.Whowastheplayer?Washereal?AdamJonesisveryreal.Andasmuchasthisexercisewasfrustrating,alookatJones'careerprovidesaprettyslickbellcurve:$7,$15,$18,$23,$28,$32,$28,$19.$14.Sincethen,heplateauedbetween$17and$19forafewyearsbeforedroppingto$10in2019.Wewouldbesoluckyifeveryplayer'scareerfollowedasfineatrendasthis.They'dbeacinchtoprojecteachyear(oh,theirony!).

Waitaminute.Isanyofthisdatavalid?CanweevenuseRotisserieearningstoevaluateplayers?Isn'tthisthesameargumentyoumadeagainstusingOPS?

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You'reright;nicejob.That'swhyallofthesedatapointsaresuspect.AdamJones'bellcurveisprobablynotnearlyasconsistentasitseems.Still,therearetwoareaswhereRotisseriedollarscanhavesomevalue.1.Iwouldn'tusepastRotoearningstoprojectnextyear'sdollarvalue,buttheydohaveanadvantageoverothermetrics.Thisisbecausethedollarcalculationnormalizesstatisticstothelevelofoffenseandpitchingeachyear.Soa30-HRperformanceinahighoffenseseason(like2019)wouldearnfewerdollarsthanthatsame30-HRperformanceinalowoffenseseason(like2014).Theabovedatasetsarefinetoevaluatewithinthelimitationoftheimpreciseinputs.2.Sharpchangesinperformancearereflectedprettyaccurately,eveniftheprecisedollarvaluesareinexact.Sowecanuserotodollarstosuggestthemagnitudeofabreakoutorbreakdownperformance.Welookatresearchresultsbasedonaggregatedataanddrawfiniteconclusionsaboutindividualplayers.Therehasbeenatonofresearchdoneoverthepast30years.Mostofthisstuffisincrediblyinsightfulandthefindingsreallyhelpusunderstandthecomponentsoftrueskill.Theproblemisthattheseresultsreflecttendenciesonamacrolevel.Noneofthemproduceapercentageplaythat'sgoodenoughtomakemicroplayerdecisionswithanyconfidence.Astandardfantasyrosterwith23playersiswaytoosmallasamplesizeforanyofthistomatter.(There'sthatstatementagain.)Youarenotgoingtobeabletoleverageminisculepercentagedifferenceswithsofewchancestoberightorwrong.Those23playersarejustnotenoughopportunitiestocoveryourrisk.Herearethreewidely-usedvariablesthatarealmostalwaysawasteoftimetoworryabout.Age:Researchshowsthatplayers'skillspeakatacertainage–26,23,28,31–pickanumber,anynumber.Butthosearejustroughaverages.Noteveryplayerisgoingtopeakatagivenage.Sotargeting28-year-oldsinyourdraftmightpayoffonlyifyou'reinabout30leagues.Andeventhen,youmightenduppassingona21-year-oldrookiewhohitsthegroundrunningoradecliningveteranwhohasahugereboundseasonatage39.Thoseerrorsmightcostyouatitle.Withonly23chances,theoddsofrosteringanoutlierarenotmuchdifferentfromtheoddsofrosteringaplayerthatfitsyourtarget.However…thereareafewtimeswhentheoddsarehighenoughtopursue.Eventually,playersageoutofrosterableskills.Thatageisdifferentforeveryplayer,

29

buttheoldertheyget,thehighertheodds.So,ifaplayerhasacareeryearinhismid-to-late30s,betagainstarepeat.Ifaplayerhasacrappyyearinhislate30s,betagainstarebound.Thosearehigherpercentageplaysandareprettymuchtheonlyonesworthchasing.Buteventhosearenotabsolutes.Parkeffects:Iknowfromexperiencethatmosttoutsgothroughapainstakingconversionprocesseverytimeaplayerswitchesteams.Iusedtoaswell.ButI'vecometofindtheexerciseofadjustingprojectionsforparkeffectsmostlyawasteoftime.AsoftenasaChristianYelichbreaksoutmovingfromMiamitoMilwaukee,therewillbeanIanDesmondorJonathanLucroywhofailstocapitalizeonamovetoCoorsField.Evenextremeballparkchangesareinconclusivebecausetherearealwaysothervariablesinplay.Thatbringsupabiggerquestion:howdoyouknowthatanincreaseordecreaseinaplayer'soutputisreallypark-related?Ifa30-HRhittermovestoaparkthatincreasespowerby20percent–whichisahugeleap–thenwecouldexpecthimtonowbea33-HRhitter(thepercentageonlyaffectshomegames).Buta3-HRincreaseiswellwithinthelimitsofnormalstatisticalvariance.Howdoweknowthatnormalskillsgrowthdidn'tdrivetheincreaseinhomeruns?Orsimplestatisticalvolatility?Oratrioofwell-timedgustsofwind?It'sevenmorefuzzywithratiogauges.However…ifyouaregoingtouseitatall,focusonthemargins.Thenoticeableimpactsareonlygoingtocomefromahittermovingfromoneofthebesthittersparkstooneoftheworst,orviceversa.Theinversegoesforpitchers,obviously.Ihavegivenupcalculatinganythinginbetween.Teamsupport:Ifyouhavetwoplayersofcomparableskill,butoneplaysonacontenderandtheotherplaysonadoormat,you'llalmostalwaysoptfortheplayeronthebetterclub.Teamenvironmentmatters,right?MorerunsandRBIs,morewinsandsaves.UnlessyouinvestedintheNationalsin2018,ateamthatwassupposedtocontend.OrmaybeyoubetheavilyonthedefendingchampionRoyalstobebetterthana.500clubin2016.Orthe2018championRedSoxtofinishcloserthan19gamesoutin2019.Failuretocorrectlypredictteamenvironmentforthoseclubshadahugeimpact.Evenpickingtherightteamisnoguarantee.In2016,CarlosCarrascoandDannySalazaronthe94-winIndiansonlywon11gamesapiece.Similarly,the89-winBrewersin2019hadonlytwopitcherswithdouble-digitswintotals–BrandonWoodruff(11)andZachDavies(10).The2015Dodgersshouldhavebeenaprimetargetforoffensiveproduction,butnobodybehindAdrianGonzalezamassedmorethan60RBIs.

30

Asatie-breakerwheneverythingelseisequal?Sure.ButI'mwillingtobetyoucanfindsomeothervariablethatwillhavemoreofanimpact.Wearelargelydrivenbyrecencybias.Weliveinaworldwherewe'reinundatedininformation.It'sfartoomuchtoprocesssowehavetorelyonsmallerchunksthatareeasiertoremember.Andtheeasiestpiecesofdatatorememberarethoseclosesttothesurfaceofourconsciousness.AskmewhatIhadforbreakfastthismorningbutforgetaboutmerememberingwhatIhadfordinnertwonightsago.("RedcurryatthatThairestaurant."–Wife)Theeffectsofrecencybiasonmanagingourfantasyteamshavegrownovertimeastheamountofinformationwe'vehadtoprocesshasgrown.Partofitisjusttheendlessquesttograbatwhateverwecan.I'vealreadytalkedaboutsmallsamplesizes–that'spartofit–butthesedays,evenapartialseasonofaberrantperformanceoftentrumpsa10-yearcareerofconsistency.Recencybiasdriveseachyear'sADPs.Thequickestwaytoearnafirstroundrankingistopostfirst-roundearningsthepreviousyear.Thesenewriserswhohavesupplantedthevetscouldwellbethenextwaveofstartalent,butarewepassingjudgmentafterjustoneseason?Afterall,outliersrunbothways.It'slikewecompletelyignoreoneoftheveryfirsttenetsofbaseballprognosticating:Don'tprojectaplayerbasedononeseason'sstats.After30years,havewelearnednothing?Thehistoricaltrackrecordshowsthatpitchersearningfirstroundvalueinoneseasonarepoorbetstorepeatthefeatinconsecutiveyears.ClaytonKershawmanagedtodefythisformanyyears–hewastheonlyone!–butevenhecouldn'tescapein2016.Still,therearealwaysseveralarmswhodoearntop15value;it'sjustmostlyadifferentgroupeachyear.Volatilepitchingstatsandthechangingcompositionofthetalentpooldrivethatphenomenon.Butguaranteedthatsomeoflastyear'sdominantarmsarestillgoingtogetdraftedaheadofotherswhohavebeenmorestableandconsistentyearinandyearout.AndassureasCarlosCorreawasoverdraftedin2016,therearealwaysahandfulofsecondhalfsurgerswhowillgetpushedfarforwardintherankingseachyear.AdalbertoMondesiwasoverdraftedin2019;YordanAlvarezlikelyin2020.Thishappenstimeandtimeagain.Whydopeoplekeepdoingthis? Maybewedon'twanttomissout.

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Wemakedecisionsbasedonthefearofmissingout.Igetitthatyoudon'twanttobetheguywhomissesoutonthenextHall-of-Famer.Butareyouabsolutelycertainenoughtoriskthoseall-importantearlypicksthatarealreadysaddledwithinflatedfailurerates?EveryyearbringsanotherexampleofwhathappenswhenyoubuyintotheFearofMissingOut.Evenifaplayerperformsasexpected–likeKrisBryantdidin2015andFranciscoLindorin2016–over-draftingthemofferednobenefit.TheteamsthatwonleaguesthatyearwerenotthosethatownedBryantorLindor,becausetheywerepurchasedatnearlyfullvalue.Therewasnoadvantagetopayingthatmuch;therewasonlytheriskthatanunprovenplayerwouldfail.Whenyoudraftaplayerlikethatasafoundationpiecetoyourroster,thereisfarmoredownsidethanupside.Ifheisfullyproductive,you'vesetaveryhighbarforhimtoreturnparvalue.Perhapshehasahigherfloorthanothers,soyourdownsideismitigated.Butwesimplydon'tknowwhatthatrangeis.Hereismycompletelyunscientifictakeontheoddsforthattypeofplayerasatoppick:

Profit 1%Parvalue 20%Someloss 60%Majorloss 19%

Youcanquibblewiththepercentages,butthegeneralconclusionhastobethesame:whatareyouchasing?Ifyou'reoverpayingforaspeculationatthedraft,you'realsopotentiallypassingupprofitopportunitieslateron,especiallyinauctionleagues.Asmuchasyouthinkyoucanfindprofitineveryplayer,youonlyget23chances,andthereareatleast11otherguysinyourleaguewhoarethinkingthesameway.Thisisparticularlydangerousintheearlyroundswherewe'veshownthatouroveralltrackrecordisterrible.Hereareafewinterestingplayersofnote:

#yearsdraftedin1stRd #yearsearnedPlayer forFearofMissingOut 1stRdvalueTroyTulowitzki 4 0EvanLongoria 3 0CarlosGonzalez 4 1PrinceFielder 4 1BryceHarper 4 1GiancarloStanton 3 1

Talkaboutdoingthesamethingoverandoveragain,andexpectingdifferentresults.Isn'tthatthedefinitionofinsanity?

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WebasedecisionsonNOW.Thereisasubconsciouspartofusthatactuallyagreeswiththefactthatyoucan'tpredictthefuture.Ifourdecision-makingprocesswasfullyconsciousanddeliberate,wemighttakeanobjectivelookateachsituationwithaneyetowardstomorrow.Instead,wetendtotaketheeasywayoutandjustviewwhatishappeningrightnowasafixedreality.Butrealityisnotfixed.Itisfluid.Onedecisionbegetsuncertainoutcomes,whichbegetotherdecisions. English,please.Atleastgivemeanexample.Okay.Here'sanotherfairytale:"Onceuponatime(early2015),therewasacloserfortheSeattleMarinersnamedFernandoRodney.Hehadavolatilecareer–someverygoodyearsandsomeverybadones–anddespitesomequestionabouthisabilitytoholddownacloser'srole,RonShandlerspentfull-pricecloserdollarsforhiminToutWars($16).Shandlerreasonedthat,despiteRodney'serratictrackrecord,hewasthecloserNOW.Asitwouldturnout,itdidn'ttakelongforRodneytoturnintoapumpkin,wipingoutShandler'sinvestment(andrelegatinghimtolastplaceinsavesfortherestoftheseason).WhenCarsonSmithinnocuouslyslidintothecloser'srole,heimmediatelybecametheNOWguy,andfantasyleaguersaroundtheworldproceededtoexhaustasignificantpartoftheirfreeagentacquisitionresourcesonapitcherwithfarbetterskillsthanthedeposedRodney.Because,betterskillsandNOW.TheseNOWinvestmentsalsocomewithanintrinsicexpectationoflongevity–weexpectthepitcherwillholdtherolefortherestoftheyear.Butwhenitcomestoclosers,theyholdthatroleuntiltheydon't,andsometimesthein-seasonshelflifeforthatroleisweeks,ordays.Smith'sninthinning"BestifUsedBy"dateexpiredafterabouttwoandahalfmonths.HestartedlosinggamesandblowingsavesinlateJuly,andwassupplantedbyTomWilhelmsonbymid-August.Wilhelmson'sskillsetpaledincomparisontoSmith's(andonceSmithlosttherole,hedidnotgiveuparunfortherestoftheseason)butthat'snotwhatrealityisabout.WilhelmsonwasnowtheNOWguydrawingwhatevermeagerfreeagentresourceswerestillleft.Aftertheseasonwasover,theMarinersrespondedtoallthisbytossinglastyear'sNOWguystothecurbandstartingoverwithabunchofnewNOWguys.Andtheyalllivedhappilyeverafter.ExceptforShandler."

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Thesestoriesdon'tseemtohavehappyendings. Nicestory.Iassumeyoudidn'twinToutWars.Um,no.Buttheexperienceisrepresentative.Hereareotherwaysthatourdecision-makingprocessesareinfluencedbyNOW:Therearesomeplayerswholockdownrolesattheveryendofspringtraining.Theserosterdecisionsaresometimesbasedonjustoneortwogamesoflateperformance,goingintothatlastMarchweekendwithtwoplayersfightingforonespot.WetreatthoseNOWguysasfixedrealities,biddingthemuptofullvalueonDraftDayasif"winningajob"istheonlyprerequisitetofull-seasonsuccess.Thisalsogoesbacktothesmallsamplesizediscussion.YourNo.4startingpitchergetsofftoaridiculouslygoodstart.Despitethefactthathisskillshavenotchangedsubstantiallyandhisrecentsuccessisagainstweakcompetition,yourefusetoentertaintradeoffers,becauseheisdoingwellNOW.Whatifhekeepsitup?AreyoucontractinganacutecaseofFearofMissingOut?Manyofthesepsychologicalpotholesareinterrelated.Theyareallobstaclestosuccess. I'vehadit.Ifyoucan'ttrustthenumbers,themarketplaceorourowndecision-

making,wheredoesthatleaveus?Thereisanotherwayoflookingatit,anotherplacewherewecanputourtrust.Theonlytruthisskill.Wemaynotbeabletotrustprojections,orthemarketplace,orourowncognitivebiases,butwecanstilltrustaplayer'sdemonstratedskills.Fortunatelyforus,theindustry'stopanalystshaveputgreateffortintocreatingaccuratemetricstomeasurethoseskills.Theymaybedescriptivemorethanpredictive,butthat'sjustfine.Wewantdatathatwecancounton.Thenextsteps–thebirthofanewidea–starthere.