RRosternomics
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Cubs CHC

‹ ›

President of baseball ops: Theo Epstein · GM: Jed Hoyer

Overview

CONTEND ↗ rising
expensive & winning · year 2 in this regime · payroll 1.32× league · TAB +16.5
+16.5TAB — talent above budget1st/30
+18.1WAB — realized wins (TAB + luck)1st/30
11.0depth — 2+ WAR regulars1st/30
-2.6dead WAR — sub-replacement drag3rd/30
15%dead money %4th/30
0.640win %1st/30
53.7roster fWAR1st/30
+7surplus $M (value vs cost)7th/30
$166Mpayroll $M7th/30

2016: World Series champions · 103–58. Ranks are vs the 30 teams that season.

Roster

CFDexter Fowler 121GAlbert Almora Jr. 33GJason Heyward 24G
LFKris Bryant 60GJorge Soler 53GMatt Szczur 50G
RFJason Heyward 131GBen Zobrist 24GChris Coghlan 18G
SSAddison Russell 148GJavier Báez 25GKris Bryant 1G
2BBen Zobrist 119GJavier Báez 59GMunenori Kawasaki 10G
3BKris Bryant 107GJavier Báez 62GTommy La Stella 33G
1BAnthony Rizzo 154GKris Bryant 9GJavier Báez 6G
STARTERSJon Lester 4.2WARJake Arrieta 4.2WARKyle Hendricks 4.0WARJohn Lackey 2.6WARJason Hammel 1.8WAR
CMiguel Montero 71GDavid Ross 58GWillson Contreras 57G
DHJorge Soler 7GKris Bryant 1GDexter Fowler 1G
BULLPEN★ Aroldis Chapman 36svPedro Strop 21hTravis Wood 12hJustin Grimm 10hHéctor Rondón 7hJoe Smith 7hCarl Edwards Jr. 6hTrevor Cahill 4h
CMiguel Montero 71 · David Ross 58 · Willson Contreras 57
1BAnthony Rizzo 154 · Kris Bryant 9 · Javier Báez 6
2BBen Zobrist 119 · Javier Báez 59 · Munenori Kawasaki 10
3BKris Bryant 107 · Javier Báez 62 · Tommy La Stella 33
SSAddison Russell 148 · Javier Báez 25 · Kris Bryant 1
LFKris Bryant 60 · Jorge Soler 53 · Matt Szczur 50
CFDexter Fowler 121 · Albert Almora Jr. 33 · Jason Heyward 24
RFJason Heyward 131 · Ben Zobrist 24 · Chris Coghlan 18
DHJorge Soler 7 · Kris Bryant 1 · Dexter Fowler 1
SPJon Lester 4.2 · Jake Arrieta 4.2 · Kyle Hendricks 4.0 · John Lackey 2.6 · Jason Hammel 1.8
BP★ Aroldis Chapman 36 · Pedro Strop 21 · Travis Wood 12 · Justin Grimm 10 · Héctor Rondón 7 · Joe Smith 7 · Carl Edwards Jr. 6 · Trevor Cahill 4

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.

2016 roster — value & surplus

PlayerAgeServiceGfWARSalary $MSurplus $M
Kris Bryant 24 pre-arb 1557.5 0.7 +23.8
Anthony Rizzo 26 arb 1554.8 5.0 +10.7
Dexter Fowler 30 FA-elig 1254.3 8.0 +6.0
Jon Lester 32 FA-elig 334.2 25.0 -11.2
Jake Arrieta 30 FA-elig 314.2 10.7 +2.8
Kyle Hendricks 26 pre-arb 324.0 0.5 +12.4
Ben Zobrist 35 FA-elig 1473.6 10.5 +1.1
Addison Russell 22 pre-arb 1513.6 0.5 +11.1
John Lackey 37 FA-elig 292.6 16.0 -7.5
Javier Báez 23 pre-arb 1422.6 0.5 +7.8
Willson Contreras 24 – 762.5 0.3 +7.8
Jason Hammel 33 FA-elig 351.8 9.0 -3.3
David Ross 39 FA-elig 671.5 2.5 +2.3
Miguel Montero 32 FA-elig 861.4 14.0 -9.3
Aroldis Chapman↔ NYY 28 FA-elig 281.3 5.4 -1.0
Pedro Strop 31 FA-elig 550.7 4.4 -2.1
Chris Coghlan↔ OAK 31 FA-elig 480.6 2.3 -0.2
Jason Heyward 26 FA-elig 1420.6 21.7 -19.7
Héctor Rondón 28 arb 540.6 4.2 -2.3
Carl Edwards Jr. 24 – 370.6 – –
Albert Almora Jr. 22 – 470.5 0.2 +1.5
Justin Grimm 27 arb 680.5 1.3 +0.3
Tommy La Stella 27 pre-arb 740.5 0.5 +1.0
Rob Zastryzny 24 – 80.4 0.1 +1.3
Jorge Soler 24 pre-arb 860.4 3.7 -2.3
Munenori Kawasaki 35 pre-arb 140.3 0.1 +1.0
Matt Szczur 26 pre-arb 1070.3 0.5 +0.4
Félix Peña 26 – 110.2 0.1 +0.5
Jake Buchanan 26 pre-arb 20.1 0.1 +0.1
Gerardo Concepción 24 – 30.1 1.2 -1.0
Joe Nathan↔ SFG 41 – 30.0 0.3 -0.2
Ryan Kalish 28 pre-arb 70.0 0.0 -0.0
Clayton Richard↔ SDP 32 FA-elig 26-0.0 1.4 -1.4
Neil Ramírez↔ MIL 27 pre-arb 8-0.0 0.2 -0.4
Trevor Cahill 28 FA-elig 51-0.1 4.2 -4.5
Travis Wood 29 FA-elig 81-0.1 6.2 -6.5
Mike Montgomery↔ SEA 26 pre-arb 17-0.1 0.2 -0.5
Kyle Schwarber 23 pre-arb 2-0.1 0.5 -0.8
Spencer Patton 28 pre-arb 16-0.2 0.2 -0.9
Jeimer Candelario 22 – 5-0.2 0.0 -0.8
Tim Federowicz 28 pre-arb 17-0.2 0.2 -1.0
Joe Smith↔ ANA 32 FA-elig 16-0.2 1.6 -2.4
Joel Peralta↔ SEA 40 FA-elig 5-0.3 0.2 -1.0
Brian Matusz↔ BAL 29 arb 1-0.3 0.5 -1.5
Adam Warren↔ NYY 28 arb 29-0.7 0.8 -3.2

Key additions (new vs 2015)

PlayerfWAR
Ben Zobrist3.6
John Lackey2.6
Willson Contreras2.5
Aroldis Chapman1.3
Jason Heyward0.6
Albert Almora Jr.0.5

Key subtractions (gone from 2015)

Player2015 fWAR
Starlin Castro0.6
Chris Denorfia0.4
Jason Motte0.4
Dan Haren0.2
Tsuyoshi Wada0.2
Donn Roach0.1

Current & Historical Payroll

2016 payroll
$165.7M
2017 guaranteed
$0M

What the front office was committed to as of 2016, 2016–2022. Guaranteed $ are contract commitments signed by 2016; 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 (12)

PlayerAgeSvc2016201720182019202020212022
Jon Lester329.075$25.0MFREE AGENT
Jason Heyward266.000$21.7MFREE AGENT
John Lackey3713.095$16.0MFREE AGENT
Miguel Montero329.031$14.0MFREE AGENT
Ben Zobrist358.134$10.5MFREE AGENT
Jason Hammel338.153$9.0MFREE AGENT
Dexter Fowler306.168$8.0MFREE AGENT
Trevor Cahill286.098$4.2MFREE AGENT
David Ross3913.001$2.5MFREE AGENT
Joe Smith328.091$1.6MFREE AGENT
Joe Nathan4114.120$300kFREE AGENT
Joel Peralta409.132$202kFREE AGENT

Arbitration-eligible (10)

PlayerAgeSvc2016201720182019202020212022
Jake Arrieta304.145$10.7MARB 3FREE AGENT
Travis Wood295.004$6.2MFREE AGENT
Aroldis Chapman285.034$5.4MFREE AGENT
Anthony Rizzo263.168$5.0MARB 2ARB 3FREE AGENT
Pedro Strop314.156$4.4MARB 3FREE AGENT
Héctor Rondón283.000$4.2MARB 2ARB 3FREE AGENT
Chris Coghlan315.148$2.3MFREE AGENT
Clayton Richard325.163$1.4MFREE AGENT
Adam Warren283.036$850kARB 2ARB 3FREE AGENT
Brian Matusz295.156$488kFREE AGENT

Pre-arbitration (23)

PlayerAgeSvc2016201720182019202020212022
Jorge Soler241.032$3.7MPre-ArbARB 1ARB 2ARB 3FREE AGENT
Justin Grimm272.170$1.3MARB 1ARB 2ARB 3FREE AGENT
Gerardo Concepción24–$1.2M
Kris Bryant240.171$652kPre-ArbPre-ArbARB 1ARB 2ARB 3FREE AGENT
Kyle Hendricks261.080$541kPre-ArbARB 1ARB 2ARB 3FREE AGENT
Tommy La Stella272.000$532kARB 1ARB 2ARB 3FREE AGENT
Addison Russell220.167$527kPre-ArbPre-ArbARB 1ARB 2ARB 3FREE AGENT
Kyle Schwarber230.086$522kPre-ArbPre-ArbARB 1ARB 2ARB 3FREE AGENT
Javier Báez230.089$521kPre-ArbPre-ArbARB 1ARB 2ARB 3FREE AGENT
Matt Szczur260.134$511kPre-ArbPre-ArbARB 1ARB 2ARB 3FREE AGENT
Willson Contreras240.000$299kPre-ArbPre-ArbARB 1ARB 2ARB 3FREE AGENT
Neil Ramírez271.158$233kPre-ArbARB 1ARB 2ARB 3FREE AGENT
Tim Federowicz281.107$214kPre-ArbARB 1ARB 2ARB 3FREE AGENT
Spencer Patton280.106$211kPre-ArbPre-ArbARB 1ARB 2ARB 3FREE AGENT
Albert Almora Jr.220.000$202kPre-ArbPre-ArbARB 1ARB 2ARB 3FREE AGENT
Mike Montgomery260.089$179kPre-ArbPre-ArbARB 1ARB 2ARB 3FREE AGENT
Rob Zastryzny240.000$125kPre-ArbPre-ArbARB 1ARB 2ARB 3FREE AGENT
Félix Peña260.000$125kPre-ArbPre-ArbARB 1ARB 2ARB 3FREE AGENT
Munenori Kawasaki352.138$100kARB 1ARB 2ARB 3FREE AGENT
Jake Buchanan260.105$89kPre-ArbPre-ArbARB 1ARB 2ARB 3FREE AGENT
Ryan Kalish282.117$31kARB 1ARB 2ARB 3FREE AGENT
Jeimer Candelario220.000$17kPre-ArbPre-ArbARB 1ARB 2ARB 3FREE AGENT
Carl Edwards Jr.241.000—Pre-ArbARB 1ARB 2ARB 3FREE AGENT

Graphs

Every roster slot ranked best→worst by WAR. Bars = Cubs 2016; 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.

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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:'CHC',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);});