RRosternomics
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Cardinals STL

‹ ›

President of baseball ops: John Mozeliak · GM: Mike Girsch

Overview

FORCED-SPEND ↘ cooling
expensive & losing · year 1 in this regime · payroll 1.13× league · TAB -6.2
-6.2TAB — talent above budget
+0.4WAB — realized wins (TAB + luck)
1.0depth — 2+ WAR regulars11th/30
-2.4dead WAR — sub-replacement drag8th/30
50%dead money %17th/30
0.517win %12th/30
10.6roster fWAR19th/30
-56surplus $M (value vs cost)22nd/30
$133Mpayroll $M12th/30

2020: made playoffs · 30–28. Ranks are vs the 30 teams that season.

Roster

CFHarrison Bader 49GDylan Carlson 17GLane Thomas 7G
LFTyler O'Neill 48GDylan Carlson 10GTommy Edman 8G
RFDexter Fowler 27GDylan Carlson 18GLane Thomas 14G
SSPaul DeJong 45GTommy Edman 13GBrad Miller 2G
2BKolten Wong 53GTommy Edman 8GMax Schrock 5G
3BTommy Edman 31GMatt Carpenter 30GBrad Miller 15G
1BPaul Goldschmidt 52GMatt Carpenter 6GRangel Ravelo 3G
STARTERSAdam Wainwright 1.0WARKwang Hyun Kim 0.6WARJack Flaherty 0.6WARDakota Hudson 0.4WARJohan Oviedo 0.1WAR
CYadier Molina 42GMatt Wieters 18GAndrew Knizner 7G
DHBrad Miller 32GMatt Carpenter 14GRangel Ravelo 6G
BULLPEN★ Andrew Miller 4svJohn Gant 7hGénesis Cabrera 3hAlex Reyes 3hTyler Webb 2hGiovanny Gallegos 1hAustin Gomber 1hJake Woodford 0h
CYadier Molina 42 · Matt Wieters 18 · Andrew Knizner 7
1BPaul Goldschmidt 52 · Matt Carpenter 6 · Rangel Ravelo 3
2BKolten Wong 53 · Tommy Edman 8 · Max Schrock 5
3BTommy Edman 31 · Matt Carpenter 30 · Brad Miller 15
SSPaul DeJong 45 · Tommy Edman 13 · Brad Miller 2
LFTyler O'Neill 48 · Dylan Carlson 10 · Tommy Edman 8
CFHarrison Bader 49 · Dylan Carlson 17 · Lane Thomas 7
RFDexter Fowler 27 · Dylan Carlson 18 · Lane Thomas 14
DHBrad Miller 32 · Matt Carpenter 14 · Rangel Ravelo 6
SPAdam Wainwright 1.0 · Kwang Hyun Kim 0.6 · Jack Flaherty 0.6 · Dakota Hudson 0.4 · Johan Oviedo 0.1
BP★ Andrew Miller 4 · John Gant 7 · Génesis Cabrera 3 · Alex Reyes 3 · Tyler Webb 2 · Giovanny Gallegos 1 · Austin Gomber 1 · Jake Woodford 0

Each position lists its starter then backups by games (so platoons & bench show). Starters (mound) & bullpen (left, foul territory) are ranked by WAR; ★ marks the closer (most save chances). MLB Stats API.

2020 roster — value & surplus

PlayerAgeServiceGfWARSalary $MSurplus $M
Paul Goldschmidt 32 FA-elig 582.1 26.0 -10.9
Kolten Wong 29 FA-elig 531.1 10.2 -2.2
Adam Wainwright 38 FA-elig 101.0 5.0 +2.5
Harrison Bader 26 pre-arb 501.0 0.2 +7.1
Tommy Edman 25 pre-arb 551.0 0.2 +6.8
Yadier Molina 37 FA-elig 420.7 20.0 -14.8
Brad Miller 30 FA-elig 480.7 2.0 +3.0
Kwang Hyun Kim 31 – 80.6 1.5 +3.2
Jack Flaherty 24 arb 90.6 0.6 +3.7
Giovanny Gallegos 28 pre-arb 160.6 0.2 +3.9
Austin Gomber 26 pre-arb 140.5 0.2 +3.5
Alex Reyes 25 pre-arb 150.5 0.2 +3.3
John Gant 27 arb 170.5 1.3 +2.1
Dakota Hudson 25 pre-arb 80.4 0.2 +2.6
Matt Carpenter 34 FA-elig 500.3 18.5 -16.1
Andrew Miller 35 FA-elig 160.3 11.5 -9.2
Paul DeJong 26 arb 450.3 1.7 +0.4
Tyler Webb 29 pre-arb 210.3 0.2 +1.7
Tyler O'Neill 25 pre-arb 500.3 0.2 +1.7
Dexter Fowler 34 FA-elig 310.2 16.5 -15.3
Austin Dean 26 pre-arb 30.1 0.2 +0.2
Johan Oviedo 22 – 50.1 0.1 +0.3
Rob Kaminsky 25 – 50.0 0.1 +0.2
Jesus Cruz 25 – 10.0 0.0 +0.2
Justin Williams 24 pre-arb 30.0 0.0 +0.0
Kodi Whitley 25 – 4-0.0 0.2 -0.2
John Nogowski 27 – 1-0.0 0.0 -0.1
Nabil Crismatt 25 – 6-0.0 0.1 -0.2
Ryan Meisinger 26 pre-arb 2-0.0 0.0 -0.3
Daniel Ponce de Leon 28 – 9-0.0 0.1 -0.4
Max Schrock 25 – 11-0.0 0.1 -0.3
Seth Elledge 24 – 12-0.1 0.1 -0.5
Andrew Knizner 25 pre-arb 8-0.1 0.1 -0.5
Junior Fernández 23 pre-arb 3-0.1 0.1 -0.5
Génesis Cabrera 23 pre-arb 20-0.1 0.2 -0.6
Matt Wieters 34 FA-elig 19-0.1 2.0 -2.5
Dylan Carlson 21 – 35-0.1 0.1 -0.7
Ricardo Sánchez 23 – 3-0.1 0.1 -0.9
Lane Thomas 24 pre-arb 18-0.2 0.2 -1.9
Carlos Martinez 28 FA-elig 5-0.2 11.7 -13.5
Rangel Ravelo 28 pre-arb 13-0.2 0.2 -2.0
Jake Woodford 23 – 12-0.3 0.2 -2.5
Ryan Helsley 25 pre-arb 12-0.4 0.2 -2.9
Roel Ramírez 25 – 1-0.4 0.1 -2.8

Key additions (new vs 2019)

PlayerfWAR
Brad Miller0.7
Kwang Hyun Kim0.6
Austin Gomber0.5
Austin Dean0.1
Johan Oviedo0.1
Rob Kaminsky0.0

Key subtractions (gone from 2019)

Player2019 fWAR
Marcell Ozuna2.1
Randy Arozarena0.2
Luke Gregerson0.1
Jedd Gyorko0.1
Chasen Shreve0.1
Adalberto Mejía0.0

Current & Historical Payroll

2020 payroll
$132.8M
2021 guaranteed
$0M

What the front office was committed to as of 2020, 2020–2026. Guaranteed $ are contract commitments signed by 2020; arbitration & free-agent years are projected from service time. Hover a figure for its luxury-tax (CBT) & actual-cash values.

current $ guaranteed $ arbitration (proj) pre-arb (proj) free agent club option player option mutual option vesting option

Guaranteed / signed (10)

PlayerAgeSvc2020202120222023202420252026
Paul Goldschmidt328.059$26.0MFREE AGENT
Yadier Molina3715.123$20.0MFREE AGENT
Matt Carpenter348.012$18.5MFREE AGENT
Dexter Fowler3410.168$16.5MFREE AGENT
Carlos Martinez286.073$11.7MFREE AGENT
Andrew Miller3511.062$11.5MFREE AGENT
Kolten Wong296.045$10.2MFREE AGENT
Adam Wainwright3814.027$5.0MFREE AGENT
Matt Wieters3410.129$2.0MFREE AGENT
Brad Miller306.004$2.0MFREE AGENT

Arbitration-eligible (1)

PlayerAgeSvc2020202120222023202420252026
John Gant273.004$1.3MARB 2ARB 3FREE AGENT

Pre-arbitration (33)

PlayerAgeSvc2020202120222023202420252026
Paul DeJong262.127$1.7MARB 1ARB 2ARB 3FREE AGENT
Kwang Hyun Kim310.000$1.5MPre-ArbPre-ArbARB 1ARB 2ARB 3FREE AGENT
Jack Flaherty242.006$604kARB 1ARB 2ARB 3FREE AGENT
Harrison Bader262.030$219kARB 1ARB 2ARB 3FREE AGENT
Giovanny Gallegos281.085$216kPre-ArbARB 1ARB 2ARB 3FREE AGENT
Tommy Edman250.114$215kPre-ArbPre-ArbARB 1ARB 2ARB 3FREE AGENT
Dakota Hudson251.066$215kPre-ArbARB 1ARB 2ARB 3FREE AGENT
Tyler Webb291.076$213kPre-ArbARB 1ARB 2ARB 3FREE AGENT
Tyler O'Neill251.059$212kPre-ArbARB 1ARB 2ARB 3FREE AGENT
Austin Gomber260.111$211kPre-ArbPre-ArbARB 1ARB 2ARB 3FREE AGENT
Ryan Helsley250.105$211kPre-ArbPre-ArbARB 1ARB 2ARB 3FREE AGENT
Rangel Ravelo280.054$210kPre-ArbPre-ArbARB 1ARB 2ARB 3FREE AGENT
Kodi Whitley250.000$209kPre-ArbPre-ArbARB 1ARB 2ARB 3FREE AGENT
Austin Dean260.124$209kPre-ArbPre-ArbARB 1ARB 2ARB 3FREE AGENT
Jake Woodford230.000$187kPre-ArbPre-ArbARB 1ARB 2ARB 3FREE AGENT
Lane Thomas240.085$173kPre-ArbPre-ArbARB 1ARB 2ARB 3FREE AGENT
Alex Reyes252.064$172kARB 1ARB 2ARB 3FREE AGENT
Génesis Cabrera230.049$168kPre-ArbPre-ArbARB 1ARB 2ARB 3FREE AGENT
Dylan Carlson210.000$140kPre-ArbPre-ArbARB 1ARB 2ARB 3FREE AGENT
Rob Kaminsky25–$137k
Ricardo Sánchez231.122$137kPre-ArbARB 1ARB 2ARB 3FREE AGENT
Andrew Knizner250.071$134kPre-ArbPre-ArbARB 1ARB 2ARB 3FREE AGENT
Junior Fernández230.045$134kPre-ArbPre-ArbARB 1ARB 2ARB 3FREE AGENT
Daniel Ponce de Leon28–$133k
Seth Elledge240.000$121kPre-ArbPre-ArbARB 1ARB 2ARB 3FREE AGENT
Johan Oviedo220.000$103kPre-ArbPre-ArbARB 1ARB 2ARB 3FREE AGENT
Max Schrock250.000$81kPre-ArbPre-ArbARB 1ARB 2ARB 3FREE AGENT
Roel Ramírez250.000$78kPre-ArbPre-ArbARB 1ARB 2ARB 3FREE AGENT
Nabil Crismatt250.000$56kPre-ArbPre-ArbARB 1ARB 2ARB 3FREE AGENT
Ryan Meisinger260.057$22kPre-ArbPre-ArbARB 1ARB 2ARB 3FREE AGENT
Justin Williams240.041$16kPre-ArbPre-ArbARB 1ARB 2ARB 3FREE AGENT
John Nogowski27–$12k
Jesus Cruz250.000$3kPre-ArbPre-ArbARB 1ARB 2ARB 3FREE AGENT

Graphs

Every roster slot ranked best→worst by WAR. Bars = Cardinals 2020; the black line = the league-average player at each slot that season. Staying above the line deep into the roster is the depth edge; dropping below it = holes & dead weight.

What each regime is worth — every settled team-season since 1985

RegimeSeasonsWin %Playoff %Pennant %WS %
WINDOW 28952.230.14.81.0
CONTEND 31156.863.019.310.3
FORCED-SPEND 26047.98.81.21.2
REBUILD 32843.31.20.30.3
Rosternomics — quantifying front-office skill, attribution-clean. Follow @rosternomics on X. Decision-makers on record back to 1933; resource-controlled metrics (WAR & payroll) cover 1985–2026.
Data: FanGraphs (WAR), Baseball-Reference & the Chadwick Bureau register (rosters, IDs), the Lahman Database, Baseball America prospect rankings (via The Baseball Cube), and public payroll records. Transaction and trade data was obtained free of charge from and is copyrighted by Retrosheet. Executive birth/death data via Wikidata (CC0); bios are original. Emoji graphics by OpenMoji (CC BY-SA 4.0).
All figures are franchise-level outcomes credited to the decision-maker in the acquisition year — not solely attributable to one executive.
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Not enough history to chart.

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Pick a wider year range.

'; return; } const s=sm(raw,w),n=s.length,X=s.map(d=>Math.round(d[1]*100)/100),Y=s.map(d=>Math.round(d[2]*10)/10),yr=s.map(d=>d[0]); let xa=Math.min(1,...X),xb=Math.max(1,...X),ya=Math.min(0,...Y),yb=Math.max(0,...Y); const px=(xb-xa)*.12+.04,py=(yb-ya)*.12+1.5;xa-=px;xb+=px;ya-=py;yb+=py; const k=Math.max(0,n-3), ann=[]; [['WINDOW','#15b6a0',xa<1&&yb>0,xa,yb,'left','top'],['CONTEND','#2f7ed8',xb>1&&yb>0,xb,yb,'right','top'], ['FORCED-SPEND','#ec5a3c',xb>1&&ya<0,xb,ya,'right','bottom'],['REBUILD','#f0a91c',xa<1&&ya<0,xa,ya,'left','bottom']].forEach(q=>{ if(q[2]) ann.push({x:q[3],y:q[4],xref:'x',yref:'y',text:q[0],showarrow:false,xanchor:q[5],yanchor:q[6],font:{size:10,color:q[1]},opacity:.85});}); ann.push({x:X[n-1],y:Y[n-1],ax:X[n-1]-0.5*(X[n-1]-X[k]),ay:Y[n-1]-0.5*(Y[n-1]-Y[k]),xref:'x',yref:'y',axref:'x',ayref:'y',showarrow:true,arrowhead:2,arrowsize:1.3,arrowwidth:1.7,arrowcolor:dirc,text:''}); Plotly.newPlot('orbit',[{x:X,y:Y,mode:'lines+markers',line:{color:col,width:2.6,shape:'spline',smoothing:0.7}, marker:{color:col,size:s.map((d,i)=>5+7*(i/Math.max(1,n-1))),line:{color:dark?'#1b1e23':'#fff',width:0.6}}, text:yr,hovertemplate:'%{text}
payroll %{x:.2f}× lg · TAB %{y:+.1f}
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slot %{x} · %{customdata[1]:.1f} WAR
%{y:.1%} of roster WAR' : '%{customdata[0]}'+posbit+'
slot %{x} · %{y:.1f} WAR'; buildPosLegend(); const _div=document.getElementById('wardist'); const traces=[ {type:'bar',x:WARDIST.ranks,y:team,name:'STL',marker:{color:barcol},customdata:cd,hovertemplate:htmpl}, {type:'scatter',x:WARDIST.ranks,y:league,name:'league avg',mode:'lines',line:{color:line,width:2,shape:'spline',smoothing:0.6},hovertemplate:'league slot %{x}: %{y:'+fmt+'}'} ]; const layout={margin:{l:48,r:12,t:6,b:38},paper_bgcolor:'rgba(0,0,0,0)',plot_bgcolor:'rgba(0,0,0,0)',font:FONT, transition:{duration:360,easing:'cubic-in-out'}, xaxis:{title:{text:'roster slot (ranked by WAR)',font:{size:11}},gridcolor:grid,zeroline:false,color:ink}, yaxis:{title:{text:WD_MODE==='prop'?'share of roster WAR':'WAR',font:{size:11}},gridcolor:grid,zeroline:true,zerolinecolor:grid,color:ink,tickformat:WD_MODE==='prop'?'.0%':undefined}, showlegend:true,legend:{orientation:'h',y:1.13,x:0,font:{size:11}},bargap:0.14}; if(_div.data&&_div.data.length){ Plotly.react(_div,traces,layout,{displayModeBar:false,responsive:true}); } else { Plotly.newPlot(_div,traces,layout,{displayModeBar:false,responsive:true}); } } window.wdMode=function(m){WD_MODE=m;document.getElementById('wd-raw').classList.toggle('on',m==='raw');document.getElementById('wd-prop').classList.toggle('on',m==='prop');drawWarDist();}; window.wcToggle=function(){WC_MODE=WC_MODE==='pos'?'team':'pos';const b=document.getElementById('wc-btn');b.classList.toggle('on',WC_MODE==='pos');b.textContent=WC_MODE==='pos'?'Show team color':'Color by position';drawWarDist();}; // ---- Graphs dropdown switcher (orbit ⇄ roster value distribution) ---- let _wdRendered=false; window.showTeamGraph=function(g){ document.querySelectorAll('.gpane').forEach(p=>{ p.style.display=(p.dataset.g===g)?'':'none'; }); if(g==='orbit'){ drawOrbit(); } else if(g==='roster'){ if(!_wdRendered){ drawWarDist(); _wdRendered=true; } else { try{ Plotly.Plots.resize('wardist'); }catch(e){ drawWarDist(); } } } }; { const _ts=document.getElementById('tgsel'); if(_ts) _ts.addEventListener('change',()=>showTeamGraph(_ts.value)); } // initial paint of the default pane (roster when the team has roster data, else orbit already drawn above) if(WARDIST){ drawWarDist(); _wdRendered=true; } // redraw the roster pane on theme change only if it's been rendered and is visible if(WARDIST){ new MutationObserver(()=>{ const p=document.querySelector('.gpane[data-g="roster"]'); if(_wdRendered && p && p.style.display!=='none') drawWarDist(); }).observe(document.documentElement,{attributes:true,attributeFilter:['data-theme']}); } // ---- TOC scroll-spy ---- (function(){ const links=[...document.querySelectorAll('.toc a')]; const secs=links.map(a=>document.querySelector(a.getAttribute('href'))).filter(Boolean); links.forEach(a=>a.addEventListener('click',e=>{e.preventDefault();document.querySelector(a.getAttribute('href')).scrollIntoView({behavior:'smooth'});})); if('IntersectionObserver' in window && secs.length){ const obs=new IntersectionObserver(es=>{es.forEach(e=>{if(e.isIntersecting) links.forEach(l=>l.classList.toggle('on',l.getAttribute('href')==='#'+e.target.id));});},{rootMargin:'-15% 0px -75% 0px'}); secs.forEach(s=>obs.observe(s)); } })(); // ---- sortable roster table ---- const SVC_RANK={'pre-arb':0,'arb':1,'FA-elig':2,'?':3}; function cellNum(td){const n=parseFloat(td.textContent.replace(/[^0-9.\-]/g,''));return isNaN(n)?null:n;} function scale(v,mn,mx,g){ if(g==='diverge'){ if(v>=0){const t=mx>0?v/mx:0;return `rgba(26,125,90,${(0.10+0.55*t).toFixed(2)})`;} const t=mn<0?v/mn:0;return `rgba(192,73,43,${(0.10+0.55*t).toFixed(2)})`; } if(g==='salmag'){const t=mx>mn?(v-mn)/(mx-mn):0;return `rgba(128,135,143,${(0.05+0.45*t).toFixed(2)})`;} const t=mx>mn?(v-mn)/(mx-mn):0;return `rgba(26,125,90,${(0.05+0.55*t).toFixed(2)})`; } function applyGradients(table){ [...table.tHead.rows[0].cells].forEach((th,ci)=>{ if(!th.dataset.grad) return; const rows=[...table.tBodies[0].rows], vals=rows.map(r=>cellNum(r.cells[ci])).filter(v=>v!==null); if(!vals.length) return; const mn=Math.min(...vals),mx=Math.max(...vals); rows.forEach(r=>{const v=cellNum(r.cells[ci]);if(v!==null)r.cells[ci].style.background=scale(v,mn,mx,th.dataset.grad);}); }); } function makeSortable(table){ const ths=[...table.tHead.rows[0].cells]; ths.forEach((th,ci)=>{ th.dataset.label=th.textContent.trim(); th.addEventListener('click',()=>{ th._dir=(th._dir===-1)?1:-1; const dir=th._dir, tb=table.tBodies[0], svc=th.dataset.sortType==='service'; [...tb.rows].sort((a,b)=>{ let va,vb; if(svc){va=SVC_RANK[a.cells[ci].textContent.trim()]??9;vb=SVC_RANK[b.cells[ci].textContent.trim()]??9;} else{va=cellNum(a.cells[ci]);vb=cellNum(b.cells[ci]); if(va===null||vb===null){va=a.cells[ci].textContent.trim().toLowerCase();vb=b.cells[ci].textContent.trim().toLowerCase();}} return vavb?dir:0; }).forEach(r=>tb.appendChild(r)); ths.forEach(h=>h.innerHTML=h.dataset.label); th.innerHTML=th.dataset.label+' '+(dir===1?'▲':'▼')+''; }); }); } document.querySelectorAll('table.sortable').forEach(t=>{applyGradients(t);makeSortable(t);});