RRosternomics
𝕏

Giants SFG

‹ ›

GM: Al Rosen

Overview

CONTEND ↘ cooling
expensive & winning · year 2 in this regime · payroll 1.21× league · TAB +4.6
+4.6TAB — talent above budget9th/26
+7.6WAB — realized wins (TAB + luck)6th/26
7.0depth — 2+ WAR regulars14th/26
-3.6dead WAR — sub-replacement drag11th/26
28%dead money %11th/26
0.568win %3rd/26
41.1roster fWAR7th/26
-1surplus $M (value vs cost)12th/26
$16Mpayroll $M5th/26

1989: won pennant · 92–70. Ranks are vs the 26 teams that season.

Roster

CFBrett Butler 152GDonell Nixon 29GPat Sheridan 10G
LFKevin Mitchell 147GPat Sheridan 27GDonell Nixon 15G
RFCandy Maldonado 116GPat Sheridan 67GDonell Nixon 26G
SSJose Uribe 150GMatt Williams 30GGreg Litton 9G
2BRobby Thompson 148GErnest Riles 18GGreg Litton 15G
3BErnest Riles 83GMatt Williams 73GKen Oberkfell 38G
1BWill Clark 158GKen Oberkfell 16GMike Laga 4G
STARTERSScott Garrelts 3.9WARRick Reuschel 2.6WARDon Robinson 2.2WARMichael LaCoss 1.5WARAtlee Hammaker 0.8WAR
CTerry Kennedy 121GKirt Manwaring 81GBob Brenly 25G
BULLPEN★ Steve Bedrosian 23svCraig Lefferts 0hJeff Brantley 0hRandy McCament 0hTrevor Wilson 0hErnie Camacho 0hStu Tate 0hDave Dravecky 0h
CTerry Kennedy 121 · Kirt Manwaring 81 · Bob Brenly 25
1BWill Clark 158 · Ken Oberkfell 16 · Mike Laga 4
2BRobby Thompson 148 · Ernest Riles 18 · Greg Litton 15
3BErnest Riles 83 · Matt Williams 73 · Ken Oberkfell 38
SSJose Uribe 150 · Matt Williams 30 · Greg Litton 9
LFKevin Mitchell 147 · Pat Sheridan 27 · Donell Nixon 15
CFBrett Butler 152 · Donell Nixon 29 · Pat Sheridan 10
RFCandy Maldonado 116 · Pat Sheridan 67 · Donell Nixon 26
SPScott Garrelts 3.9 · Rick Reuschel 2.6 · Don Robinson 2.2 · Michael LaCoss 1.5 · Atlee Hammaker 0.8
BP★ Steve Bedrosian 23 · Craig Lefferts 0 · Jeff Brantley 0 · Randy McCament 0 · Trevor Wilson 0 · Ernie Camacho 0 · Stu Tate 0 · Dave Dravecky 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.

1989 roster — value & surplus

PlayerAgeServiceGfWARSalary $MSurplus $M
Will Clark 25 arb 1598.1 1.1 +1.8
Kevin Mitchell 27 arb 1546.9 0.6 +1.9
Robby Thompson 27 arb 1485.4 0.5 +1.4
Scott Garrelts 27 FA-elig 323.9 0.7 +0.7
Rick Reuschel 40 FA-elig 322.6 1.2 -0.2
Matt Williams 23 pre-arb 842.3 0.1 +0.7
Don Robinson 32 FA-elig 402.2 0.9 -0.1
Brett Butler 32 FA-elig 1542.0 0.9 -0.2
Terry Kennedy 33 FA-elig 1251.7 0.8 -0.2
Ernest Riles 28 arb 1221.6 0.5 +0.1
Michael LaCoss 33 FA-elig 451.5 1.1 -0.6
Greg Litton 24 pre-arb 711.0 0.1 +0.3
Ken Oberkfell↔ PIT 33 FA-elig 830.9 0.6 -0.3
Atlee Hammaker 31 FA-elig 280.8 1.0 -0.7
Candy Maldonado 28 FA-elig 1290.7 0.9 -0.6
Kelly Downs 28 arb 180.7 0.3 -0.1
Craig Lefferts 31 FA-elig 700.5 0.6 -0.4
Pat Sheridan↔ DET 31 FA-elig 700.3 0.3 -0.1
Bob Knepper↔ HOU 35 FA-elig 130.3 0.0 +0.1
Dennis Cook↔ PHI 26 – 20.3 – –
Donell Nixon 27 pre-arb 950.2 0.1 -0.0
Chris Speier 39 FA-elig 280.2 0.4 -0.4
Terry Mulholland↔ PHI 26 arb 50.1 0.0 +0.0
Jose Uribe 30 arb 1510.1 0.7 -0.6
Mike Laga 29 – 170.1 – –
Stu Tate 27 – 20.1 – –
Trevor Wilson 23 – 140.1 – –
Dave Dravecky 33 FA-elig 20.0 0.8 -0.7
Kirt Manwaring 23 pre-arb 850.0 0.1 -0.1
Bill Bathe 28 arb 30-0.0 0.1 -0.1
Charlie Hayes↔ PHI 24 pre-arb 3-0.0 0.0 -0.0
Ernie Camacho 34 – 13-0.0 – –
Mike Benjamin 23 – 14-0.0 – –
Joe Price↔ BOS 32 FA-elig 7-0.1 0.0 -0.0
Jim Weaver 29 – 12-0.1 – –
Jim Steels 28 – 13-0.2 – –
Ed Jurak 31 – 30-0.2 – –
Bob Brenly↔ TOR 35 FA-elig 12-0.2 0.1 -0.2
Steve Bedrosian↔ PHI 31 FA-elig 40-0.2 0.9 -0.9
Mike Krukow 37 FA-elig 8-0.2 0.9 -1.0
Rich Gossage↔ NYY 37 FA-elig 31-0.2 0.1 -0.1
Jeff Brantley 25 pre-arb 59-0.2 0.1 -0.2
Russ Swan 25 – 2-0.5 – –
Randy McCament 26 – 25-0.6 – –
Tracy Jones↔ DET 28 arb 40-0.8 0.1 -0.4

Key additions (new vs 1988)

PlayerfWAR
Terry Kennedy1.7
Greg Litton1.0
Ken Oberkfell0.9
Pat Sheridan0.3
Bob Knepper0.3
Mike Laga0.1

Key subtractions (gone from 1988)

Player1988 fWAR
Mike Aldrete1.6
Bob Melvin1.0
Lary Sorensen0.2
Rusty Tillman0.2
Joel Youngblood0.2
Angel Escobar0.0

Current & Historical Payroll

1989 payroll
$16.5M

What the front office was committed to as of 1989, 1989–1995. 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 (22)

PlayerAgeSvc1989199019911992199319941995
Rick Reuschel4017.000$1.2M$1.0M$1.4MFREE AGENT
Michael LaCoss3311.000$1.1M$1.1M$1.4MFREE AGENT
Atlee Hammaker318.000$983k$570kFREE AGENT
Candy Maldonado288.000$900kFREE AGENT
Don Robinson3211.000$900k$950k$2.5MFREE AGENT
Brett Butler328.000$900k$1.1MFREE AGENT
Mike Krukow3713.000$875kFREE AGENT
Steve Bedrosian318.000$853k$1.4MFREE AGENT
Terry Kennedy3311.000$850k$850k$500kFREE AGENT
Dave Dravecky337.000$750kFREE AGENT
Scott Garrelts277.000$706k$1.4M$2.4MFREE AGENT
Ken Oberkfell3312.000$620kFREE AGENT
Craig Lefferts316.000$600kFREE AGENT
Chris Speier3918.000$425kFREE AGENT
Pat Sheridan318.000$251kFREE AGENT
Bob Brenly358.000$136kFREE AGENT
Rich Gossage3717.000$50kFREE AGENT
Bob Knepper3513.000$25kFREE AGENT
Joe Price329.000$13kFREE AGENT
Ernie Camacho349.000—$86kFREE AGENT
Ed Jurak317.000—FREE AGENT
Mike Laga297.000—$155kFREE AGENT

Arbitration-eligible (9)

PlayerAgeSvc1989199019911992199319941995
Will Clark253.000$1.1MARB 2ARB 3FREE AGENT
Jose Uribe305.000$688kFREE AGENT
Kevin Mitchell275.000$610kFREE AGENT
Robby Thompson273.000$536kARB 2ARB 3FREE AGENT
Ernest Riles284.000$470kARB 3FREE AGENT
Kelly Downs283.000$315kARB 2ARB 3FREE AGENT
Tracy Jones283.000$140kARB 2ARB 3FREE AGENT
Bill Bathe283.000$76kARB 2ARB 3FREE AGENT
Terry Mulholland263.000$19kARB 2ARB 3FREE AGENT

Pre-arbitration (14)

PlayerAgeSvc1989199019911992199319941995
Donell Nixon272.000$102kARB 1ARB 2ARB 3FREE AGENT
Matt Williams232.000$95kARB 1ARB 2ARB 3FREE AGENT
Kirt Manwaring232.000$78kARB 1ARB 2ARB 3FREE AGENT
Jeff Brantley251.000$78kPre-ArbARB 1ARB 2ARB 3FREE AGENT
Greg Litton240.000$68kPre-ArbPre-ArbARB 1ARB 2ARB 3FREE AGENT
Charlie Hayes241.000$2kPre-ArbARB 1ARB 2ARB 3FREE AGENT
Mike Benjamin230.000—Pre-ArbPre-ArbARB 1ARB 2ARB 3FREE AGENT
Dennis Cook261.000—Pre-ArbARB 1ARB 2ARB 3FREE AGENT
Randy McCament26–—
Jim Steels28–—
Russ Swan250.000—Pre-ArbPre-ArbARB 1ARB 2ARB 3FREE AGENT
Stu Tate27–—
Jim Weaver29–—
Trevor Wilson231.000—Pre-ArbARB 1ARB 2ARB 3FREE AGENT

Graphs

Every roster slot ranked best→worst by WAR. Bars = Giants 1989; 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:'SFG',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);});