RRosternomics
𝕏

White Sox CHW

‹ ›

GM: Ron Schueler

Overview

WINDOW ↗ rising
cheap & winning · year 1 in this regime · payroll 0.63× league · TAB +13.7
+13.7TAB — talent above budget2nd/30
+18.8WAB — realized wins (TAB + luck)1st/30
11.0depth — 2+ WAR regulars1st/30
-2.7dead WAR — sub-replacement drag6th/30
11%dead money %2nd/30
0.586win %2nd/30
42.5roster fWAR7th/30
+26surplus $M (value vs cost)1st/30
$34Mpayroll $M23rd/30

2000: made playoffs · 95–67. Ranks are vs the 30 teams that season.

Roster

CFChris Singleton 143GJeff Abbott 33GMcKay Christensen 29G
LFCarlos Lee 149GJeff Abbott 20GChris Singleton 19G
RFMagglio Ordonez 152GJeff Abbott 16GJeff Liefer 5G
SSJose Valentin 141GTony Graffanino 22GCraig Wilson 10G
2BRay Durham 151GTony Graffanino 25GCraig Wilson 4G
3BHerbert Perry Jr. 111GGreg Norton 47GTony Graffanino 15G
1BPaul Konerko 122GFrank Thomas 30GGreg Norton 17G
STARTERSMike Sirotka 3.5WARJim Parque 2.7WARCal Eldred 2.0WARJames Baldwin 1.3WARKip Wells 0.7WAR
CCharles Johnson 126GMark Johnson 74GJosh Paul 34G
DHFrank Thomas 127GHarold Baines 76GPaul Konerko 6G
BULLPEN★ Keith Foulke 34svKelly Wunsch 24hBob Howry 14hBill Simas 14hMark Buehrle 3hKevin Beirne 0hLorenzo Barcelo 0hScott Eyre 0h
CCharles Johnson 126 · Mark Johnson 74 · Josh Paul 34
1BPaul Konerko 122 · Frank Thomas 30 · Greg Norton 17
2BRay Durham 151 · Tony Graffanino 25 · Craig Wilson 4
3BHerbert Perry Jr. 111 · Greg Norton 47 · Tony Graffanino 15
SSJose Valentin 141 · Tony Graffanino 22 · Craig Wilson 10
LFCarlos Lee 149 · Jeff Abbott 20 · Chris Singleton 19
CFChris Singleton 143 · Jeff Abbott 33 · McKay Christensen 29
RFMagglio Ordonez 152 · Jeff Abbott 16 · Jeff Liefer 5
DHFrank Thomas 127 · Harold Baines 76 · Paul Konerko 6
SPMike Sirotka 3.5 · Jim Parque 2.7 · Cal Eldred 2.0 · James Baldwin 1.3 · Kip Wells 0.7
BP★ Keith Foulke 34 · Kelly Wunsch 24 · Bob Howry 14 · Bill Simas 14 · Mark Buehrle 3 · Kevin Beirne 0 · Lorenzo Barcelo 0 · Scott Eyre 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.

2000 roster — value & surplus

PlayerAgeServiceGfWARSalary $MSurplus $M
Frank Thomas 32 FA-elig 1595.9 7.1 +1.3
Jose Valentin 30 FA-elig 1444.5 1.3 +5.0
Mike Sirotka 29 arb 323.5 1.4 +3.6
Herbert Perry Jr.↔ TBR 30 FA-elig 1092.9 0.5 +3.6
Ray Durham 28 arb 1512.7 4.9 -1.1
Jim Parque 25 pre-arb 332.7 0.5 +3.3
Keith Foulke 27 arb 722.5 0.4 +3.2
Magglio Ordonez 26 arb 1532.3 0.4 +2.8
Charles Johnson↔ BAL 28 FA-elig 442.2 1.6 +1.5
Carlos Lee 24 pre-arb 1522.1 0.3 +2.7
Cal Eldred 32 FA-elig 202.0 5.4 -2.5
Paul Konerko 24 arb 1431.6 0.3 +2.0
James Baldwin 28 arb 291.3 3.3 -1.4
Bob Howry 26 pre-arb 651.2 0.3 +1.4
Kelly Wunsch 27 pre-arb 831.1 0.2 +1.4
Brook Fordyce↔ BAL 30 arb 400.8 0.3 +0.9
Tony Graffanino↔ TBR 28 arb 570.8 0.2 +0.9
Kip Wells 23 pre-arb 200.7 0.2 +0.8
Mark Buehrle 21 – 280.6 0.2 +0.7
Bill Simas 28 arb 600.6 1.4 -0.5
Josh Paul 25 pre-arb 360.6 0.2 +0.6
Mark Johnson 24 pre-arb 750.6 0.2 +0.5
Lorenzo Barcelo 22 pre-arb 220.4 0.2 +0.4
Chris Singleton 27 pre-arb 1470.4 0.3 +0.3
Jon Garland 20 pre-arb 150.4 0.2 +0.4
Chad Bradford 25 – 120.4 – –
Craig Wilson 29 pre-arb 280.2 0.2 +0.1
Sean Lowe 29 arb 500.1 0.3 -0.1
Joe Crede 22 – 70.0 – –
Kevin Beirne 26 – 29-0.0 – –
Scott Eyre 28 arb 13-0.0 0.2 -0.3
Rocky Biddle 24 – 4-0.0 – –
Aaron Myette 22 pre-arb 2-0.0 0.2 -0.2
Ken Hill↔ ANA 34 FA-elig 2-0.1 0.6 -0.7
Jeff Abbott 27 arb 80-0.2 0.3 -0.6
McKay Christensen 24 pre-arb 32-0.2 0.2 -0.5
Jeff Liefer 25 pre-arb 5-0.2 0.2 -0.6
Harold Baines↔ BAL 41 FA-elig 24-0.3 0.5 -0.9
Jesus Pena↔ BOS 25 – 20-0.3 – –
Matt Ginter 22 – 7-0.4 – –
Tanyon Sturtze↔ TBR 29 arb 10-0.4 0.1 -0.6
Greg Norton 27 arb 71-0.4 0.3 -0.9

Key additions (new vs 1999)

PlayerfWAR
Jose Valentin4.5
Herbert Perry Jr.2.9
Charles Johnson2.2
Cal Eldred2.0
Kelly Wunsch1.1
Tony Graffanino0.8

Key subtractions (gone from 1999)

Player1999 fWAR
Darrin Jackson0.4
Brian Simmons0.3
Pat Daneker0.1
John Snyder0.1
David Lundquist0.0
Todd Rizzo-0.0

Current & Historical Payroll

2000 payroll
$34.4M

What the front office was committed to as of 2000, 2000–2006. Pre-2015 has no contract-terms data — forward italic $ are realized actuals (hindsight, not commitments known then). Control labels (ARB/FA) are point-in-time.

current $ guaranteed $ actual $ (hindsight) arbitration (proj) pre-arb (proj) free agent

Guaranteed / signed (7)

PlayerAgeSvc2000200120022003200420052006
Frank Thomas3210.000$7.1M$9.9M$9.9M$5.0M$6.0M$8.0MFREE AGENT
Cal Eldred329.000$5.4M$750kFREE AGENT
Charles Johnson286.000$1.6MFREE AGENT
Jose Valentin308.000$1.3M$5.2M$5.0M$5.0M$5.0MFREE AGENT
Ken Hill3412.000$622kFREE AGENT
Harold Baines4120.000$500k$1.0MFREE AGENT
Herbert Perry Jr.306.000$470k$975kFREE AGENT

Arbitration-eligible (14)

PlayerAgeSvc2000200120022003200420052006
Ray Durham285.000$4.9MFREE AGENT
James Baldwin285.000$3.3MFREE AGENT
Mike Sirotka295.000$1.4MFREE AGENT
Bill Simas285.000$1.4MFREE AGENT
Magglio Ordonez263.000$425kARB 2ARB 3FREE AGENT
Keith Foulke273.000$375kARB 2ARB 3FREE AGENT
Paul Konerko243.000$305kARB 2ARB 3FREE AGENT
Brook Fordyce305.000$290kFREE AGENT
Greg Norton274.000$285kARB 3FREE AGENT
Jeff Abbott273.000$255kARB 2ARB 3FREE AGENT
Sean Lowe293.000$255kARB 2ARB 3FREE AGENT
Scott Eyre283.000$250kARB 2ARB 3FREE AGENT
Tony Graffanino284.000$220kARB 3FREE AGENT
Tanyon Sturtze295.000$71kFREE AGENT

Pre-arbitration (21)

PlayerAgeSvc2000200120022003200420052006
Jim Parque252.000$475kARB 1ARB 2ARB 3FREE AGENT
Bob Howry262.000$325kARB 1ARB 2ARB 3FREE AGENT
Chris Singleton271.000$285kPre-ArbARB 1ARB 2ARB 3FREE AGENT
Carlos Lee241.000$275kPre-ArbARB 1ARB 2ARB 3FREE AGENT
Mark Johnson242.000$250kARB 1ARB 2ARB 3FREE AGENT
Craig Wilson292.000$250kARB 1ARB 2ARB 3FREE AGENT
Jeff Liefer251.000$225kPre-ArbARB 1ARB 2ARB 3FREE AGENT
McKay Christensen241.000$212kPre-ArbARB 1ARB 2ARB 3FREE AGENT
Kip Wells231.000$210kPre-ArbARB 1ARB 2ARB 3FREE AGENT
Aaron Myette221.000$200kPre-ArbARB 1ARB 2ARB 3FREE AGENT
Lorenzo Barcelo220.000$200kPre-ArbPre-ArbARB 1ARB 2ARB 3FREE AGENT
Josh Paul251.000$200kPre-ArbARB 1ARB 2ARB 3FREE AGENT
Kelly Wunsch270.000$200kPre-ArbPre-ArbARB 1ARB 2ARB 3FREE AGENT
Jon Garland200.000$200kPre-ArbPre-ArbARB 1ARB 2ARB 3FREE AGENT
Mark Buehrle210.000$200kPre-ArbPre-ArbARB 1ARB 2ARB 3FREE AGENT
Chad Bradford252.000—ARB 1ARB 2ARB 3FREE AGENT
Kevin Beirne260.000—Pre-ArbPre-ArbARB 1ARB 2ARB 3FREE AGENT
Joe Crede220.000—Pre-ArbPre-ArbARB 1ARB 2ARB 3FREE AGENT
Matt Ginter220.000—Pre-ArbPre-ArbARB 1ARB 2ARB 3FREE AGENT
Jesus Pena251.000—Pre-ArbARB 1ARB 2ARB 3FREE AGENT
Rocky Biddle240.000—Pre-ArbPre-ArbARB 1ARB 2ARB 3FREE AGENT

Graphs

Every roster slot ranked best→worst by WAR. Bars = White Sox 2000; 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:'CHW',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);});