RRosternomics
𝕏

Yankees NYY

‹ ›

GM: Bob Watson

Overview

CONTEND ↗ rising
expensive & winning · year 2 in this regime · payroll 1.61× league · TAB +6.4
+6.4TAB — talent above budget5th/28
+8.1WAB — realized wins (TAB + luck)4th/28
7.0depth — 2+ WAR regulars10th/28
-2.9dead WAR — sub-replacement drag4th/28
16%dead money %4th/28
0.593win %3rd/28
46.3roster fWAR4th/28
-15surplus $M (value vs cost)22nd/28
$63Mpayroll $M1st/28

1997: made playoffs · 96–66. Ranks are vs the 28 teams that season.

Roster

CFBernie Williams 128GChad Curtis 55GScott Pose 3G
LFTim Raines Sr. 57GChad Curtis 56GMark Whiten 44G
RFPaul O'Neill 146GScott Pose 17GMark Whiten 16G
SSDerek Jeter 159GRey Sanchez 69GLuis Sojo 4G
2BLuis Sojo 72GRey Sanchez 69GPat Kelly 48G
3BCharlie Hayes 98GWade Boggs 76GAndy Fox 11G
1BTino Martinez 150GMike Stanley 43GCecil Fielder 8G
STARTERSAndy Pettitte 7.2WARDavid Cone 4.9WARDavid Wells 4.3WARRamiro Mendoza 1.7WARKenny Rogers 0.6WAR
CJoe Girardi 111GJorge Posada 60GMike Figga 1G
DHCecil Fielder 88GMike Stanley 43GPete Incaviglia 27G
BULLPEN★ Mariano Rivera 43svJeff Nelson 0hMike Stanton 0hGraeme Lloyd 0hBrian Boehringer 0hJim Mecir 0hJoe Borowski 0hWillie Banks 0h
CJoe Girardi 111 · Jorge Posada 60 · Mike Figga 1
1BTino Martinez 150 · Mike Stanley 43 · Cecil Fielder 8
2BLuis Sojo 72 · Rey Sanchez 69 · Pat Kelly 48
3BCharlie Hayes 98 · Wade Boggs 76 · Andy Fox 11
SSDerek Jeter 159 · Rey Sanchez 69 · Luis Sojo 4
LFTim Raines Sr. 57 · Chad Curtis 56 · Mark Whiten 44
CFBernie Williams 128 · Chad Curtis 55 · Scott Pose 3
RFPaul O'Neill 146 · Scott Pose 17 · Mark Whiten 16
DHCecil Fielder 88 · Mike Stanley 43 · Pete Incaviglia 27
SPAndy Pettitte 7.2 · David Cone 4.9 · David Wells 4.3 · Ramiro Mendoza 1.7 · Kenny Rogers 0.6
BP★ Mariano Rivera 43 · Jeff Nelson 0 · Mike Stanton 0 · Graeme Lloyd 0 · Brian Boehringer 0 · Jim Mecir 0 · Joe Borowski 0 · Willie Banks 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.

1997 roster — value & surplus

PlayerAgeServiceGfWARSalary $MSurplus $M
Andy Pettitte 25 pre-arb 357.2 0.6 +6.8
Tino Martinez 29 FA-elig 1585.3 4.4 +1.0
Bernie Williams 28 FA-elig 1295.1 5.3 -0.1
David Cone 34 FA-elig 294.9 6.7 -1.7
David Wells 34 FA-elig 324.3 3.8 +0.6
Derek Jeter 23 pre-arb 1594.0 0.6 +3.6
Paul O'Neill 34 FA-elig 1492.8 5.5 -2.6
Mariano Rivera 27 pre-arb 662.0 0.6 +1.5
Wade Boggs 39 FA-elig 1042.0 2.0 +0.0
Ramiro Mendoza 25 pre-arb 391.7 0.2 +1.6
Mike Stanton 30 FA-elig 641.4 1.6 -0.2
Charlie Hayes 32 FA-elig 1001.1 1.7 -0.6
Chad Curtis↔ CLE 28 arb 931.0 0.7 +0.3
Jeff Nelson 30 arb 771.0 1.1 -0.1
Tim Raines Sr. 37 FA-elig 741.0 1.7 -0.7
Cecil Fielder 33 FA-elig 980.9 9.2 -8.4
Jorge Posada 26 pre-arb 600.6 0.2 +0.4
Kenny Rogers 32 FA-elig 310.6 5.0 -4.4
Joe Girardi 32 FA-elig 1120.5 2.2 -1.7
Brian Boehringer 28 pre-arb 340.5 0.2 +0.3
Dwight Gooden 32 FA-elig 200.4 2.0 -1.6
Mike Stanley↔ BOS 34 FA-elig 280.3 0.5 -0.1
Willie Banks 28 – 50.3 – –
Rey Sanchez↔ CHC 29 FA-elig 380.2 0.4 -0.1
Luis Sojo 32 FA-elig 770.2 0.4 -0.2
Andy Fox 26 – 220.1 – –
Pat Kelly 29 FA-elig 670.0 1.1 -1.1
Jim Mecir 27 – 250.0 – –
Mark Whiten 30 FA-elig 690.0 1.0 -1.0
Ivan Cruz 29 – 11-0.1 – –
Homer Bush 24 – 10-0.1 – –
Joe Borowski↔ ATL 26 pre-arb 1-0.1 0.0 -0.1
Mike Figga 26 – 2-0.1 – –
Graeme Lloyd 30 arb 46-0.1 0.8 -0.9
Pete Incaviglia↔ BAL 33 FA-elig 5-0.1 0.1 -0.2
David Weathers↔ CLE 27 FA-elig 10-0.1 0.2 -0.4
Hideki Irabu 28 pre-arb 13-0.2 2.3 -2.5
Danny Rios 24 – 2-0.3 – –
Scott Pose 30 – 54-0.3 – –
Darryl Strawberry 35 FA-elig 11-0.4 0.8 -1.2
Mariano Duncan↔ TOR 34 FA-elig 50-1.1 0.5 -1.6

Key additions (new vs 1996)

PlayerfWAR
David Wells4.3
Mike Stanton1.4
Chad Curtis1.0
Mike Stanley0.3
Willie Banks0.3
Rey Sanchez0.2

Key subtractions (gone from 1996)

Player1996 fWAR
Jimmy Key2.7
John Wetteland1.2
Ruben Rivera1.0
Jim Leyritz0.8
Bob Wickman0.7
Dave Pavlas0.6

Current & Historical Payroll

1997 payroll
$63.1M

What the front office was committed to as of 1997, 1997–2003. 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 (23)

PlayerAgeSvc1997199819992000200120022003
Cecil Fielder3312.000$9.2MFREE AGENT
David Cone3411.000$6.7M$6.7M$9.5M$12.0MFREE AGENT
Paul O'Neill3412.000$5.5M$5.5M$6.2M$6.5M$7.2MFREE AGENT
Bernie Williams286.000$5.3M$8.3M$9.9M$12.4M$12.4M$12.4M$12.4M
Kenny Rogers328.000$5.0MFREE AGENT
Tino Martinez297.000$4.4M$4.3M$4.3M$4.8M$6.3MFREE AGENT
David Wells3410.000$3.8M$4.7MFREE AGENT$2.2M$3.2M
Joe Girardi328.000$2.2M$2.9M$3.4MFREE AGENT
Dwight Gooden3213.000$2.0MFREE AGENT$333k
Wade Boggs3915.000$2.0MFREE AGENT
Tim Raines Sr.3718.000$1.7M$1.3MFREE AGENT
Charlie Hayes329.000$1.7MFREE AGENT
Mike Stanton308.000$1.6M$1.9M$2.0M$2.4M$2.5M$2.5MFREE AGENT
Pat Kelly296.000$1.1MFREE AGENT
Mark Whiten307.000$1.0MFREE AGENT
Darryl Strawberry3514.000$750k$875kFREE AGENT
Mariano Duncan3412.000$489kFREE AGENT
Mike Stanley3411.000$470kFREE AGENT
Luis Sojo327.000$425k$800k$800k$289k$500kFREE AGENT
Rey Sanchez296.000$362kFREE AGENT
David Weathers276.000$229kFREE AGENT
Pete Incaviglia3311.000$61kFREE AGENT
Willie Banks286.000—$269kFREE AGENT

Arbitration-eligible (4)

PlayerAgeSvc1997199819992000200120022003
Jeff Nelson305.000$1.1MFREE AGENT
Graeme Lloyd304.000$770kARB 3FREE AGENT
Chad Curtis285.000$728kFREE AGENT
Scott Pose304.000—ARB 3FREE AGENT

Pre-arbitration (14)

PlayerAgeSvc1997199819992000200120022003
Hideki Irabu280.000$2.3MPre-ArbPre-ArbARB 1ARB 2ARB 3FREE AGENT
Andy Pettitte252.000$600kARB 1ARB 2ARB 3FREE AGENT
Mariano Rivera272.000$550kARB 1ARB 2ARB 3FREE AGENT
Derek Jeter232.000$550kARB 1ARB 2ARB 3FREE AGENT
Brian Boehringer282.000$161kARB 1ARB 2ARB 3FREE AGENT
Jorge Posada262.000$158kARB 1ARB 2ARB 3FREE AGENT
Ramiro Mendoza251.000$157kPre-ArbARB 1ARB 2ARB 3FREE AGENT
Joe Borowski262.000$8kARB 1ARB 2ARB 3FREE AGENT
Homer Bush240.000—Pre-ArbPre-ArbARB 1ARB 2ARB 3FREE AGENT
Ivan Cruz290.000—Pre-ArbPre-ArbARB 1ARB 2ARB 3FREE AGENT
Mike Figga260.000—Pre-ArbPre-ArbARB 1ARB 2ARB 3FREE AGENT
Andy Fox261.000—Pre-ArbARB 1ARB 2ARB 3FREE AGENT
Jim Mecir272.000—ARB 1ARB 2ARB 3FREE AGENT
Danny Rios24–—

Graphs

Every roster slot ranked best→worst by WAR. Bars = Yankees 1997; 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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Pick a wider year range.

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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:'NYY',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);});