RRosternomics
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Mets NYM

‹ ›

GM: Steve Phillips

Overview

CONTEND ↗ rising
expensive & winning · year 2 in this regime · payroll 1.47× league · TAB +3.7
+3.7TAB — talent above budget10th/30
+7.2WAB — realized wins (TAB + luck)8th/30
9.0depth — 2+ WAR regulars3rd/30
-3.8dead WAR — sub-replacement drag13th/30
18%dead money %8th/30
0.580win %5th/30
42.6roster fWAR6th/30
-26surplus $M (value vs cost)25th/30
$80Mpayroll $M4th/30

2000: won pennant · 94–68. Ranks are vs the 30 teams that season.

Roster

CFJay Payton 143GMelvin Mora 16GDarryl Hamilton 11G
LFBenny Agbayani 102GJoe McEwing 43GBubba Trammell 37G
RFDerek Bell 142GBubba Trammell 40GBenny Agbayani 12G
SSMike Bordick 156GRey Ordonez 44GKurt Abbott 39G
2BEdgardo Alfonzo 146GKurt Abbott 23GJorge Velandia 21G
3BRobin Ventura 137GLenny Harris 36GMatt Franco 22G
1BTodd Zeile 151GMatt Franco 28GLenny Harris 10G
STARTERSMike Hampton 5.2WARAl Leiter 4.3WARGlendon Rusch 4.3WARRick Reed 2.7WARBobby Jones 0.7WAR
CMike Piazza 124GTodd Pratt 71GVance Wilson 3G
DHMike Piazza 5GEdgardo Alfonzo 2GLenny Harris 1G
BULLPEN★ Armando Benítez 41svJohn Franco 20hTurk Wendell 16hDennis Cook 10hRick White 4hRich Rodriguez 0hBobby Jones 0hEric Cammack 0h
CMike Piazza 124 · Todd Pratt 71 · Vance Wilson 3
1BTodd Zeile 151 · Matt Franco 28 · Lenny Harris 10
2BEdgardo Alfonzo 146 · Kurt Abbott 23 · Jorge Velandia 21
3BRobin Ventura 137 · Lenny Harris 36 · Matt Franco 22
SSMike Bordick 156 · Rey Ordonez 44 · Kurt Abbott 39
LFBenny Agbayani 102 · Joe McEwing 43 · Bubba Trammell 37
CFJay Payton 143 · Melvin Mora 16 · Darryl Hamilton 11
RFDerek Bell 142 · Bubba Trammell 40 · Benny Agbayani 12
DHMike Piazza 5 · Edgardo Alfonzo 2 · Lenny Harris 1
SPMike Hampton 5.2 · Al Leiter 4.3 · Glendon Rusch 4.3 · Rick Reed 2.7 · Bobby Jones 0.7
BP★ Armando Benítez 41 · John Franco 20 · Turk Wendell 16 · Dennis Cook 10 · Rick White 4 · Rich Rodriguez 0 · Bobby Jones 0 · Eric Cammack 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
Edgardo Alfonzo 26 arb 1506.4 4.2 +4.9
Mike Piazza 31 FA-elig 1365.8 12.1 -3.8
Mike Hampton 27 FA-elig 355.2 5.8 +1.6
Glendon Rusch 25 – 314.3 – –
Al Leiter 34 FA-elig 314.3 7.8 -1.6
Rick Reed 35 FA-elig 302.7 4.4 -0.5
Todd Zeile 34 FA-elig 1532.7 4.3 -0.5
Benny Agbayani 28 pre-arb 1192.1 0.2 +2.7
Jay Payton 27 pre-arb 1492.0 0.2 +2.7
Robin Ventura 32 FA-elig 1411.9 8.0 -5.3
Todd Pratt 33 FA-elig 801.7 0.5 +1.9
Armando Benitez 27 FA-elig 761.5 3.4 -1.3
Derek Bell 31 FA-elig 1441.4 5.0 -3.0
Lenny Harris↔ ARI 35 FA-elig 760.8 0.7 +0.4
Bobby Jones 30 FA-elig 270.7 5.4 -4.4
John Franco 39 FA-elig 620.6 3.4 -2.5
Turk Wendell 33 FA-elig 770.4 2.1 -1.5
Timo Perez 25 – 240.3 – –
Melvin Mora↔ BAL 28 pre-arb 790.3 0.1 +0.2
Jon Nunnally 28 arb 480.2 0.3 +0.0
Rick White↔ TBR 31 FA-elig 240.2 0.2 +0.1
Bubba Trammell↔ TBR 28 arb 360.2 0.1 +0.2
Mike Bordick↔ BAL 34 FA-elig 560.2 1.1 -0.9
Bobby Jones 28 – 110.1 – –
Ryan McGuire 28 – 10.1 – –
Grant Roberts 22 – 40.1 – –
Jorge Toca 29 – 80.1 – –
Eric Cammack 24 – 80.0 – –
Darryl Hamilton 35 FA-elig 430.0 3.6 -3.6
Jerrod Riggan 26 – 10.0 – –
David Lamb 25 – 7-0.0 – –
Mike Kinkade↔ BAL 27 – 2-0.0 – –
Bill Pulsipher 26 – 2-0.1 – –
Jim Mann 25 – 2-0.1 – –
Vance Wilson 27 – 4-0.1 – –
Dennis Springer 35 – 2-0.1 – –
Dennis Cook 37 FA-elig 68-0.1 2.2 -2.3
Mark Johnson 32 – 21-0.1 – –
Matt Franco 30 arb 101-0.2 0.5 -0.7
Jorge Velandia↔ OAK 25 arb 15-0.2 0.1 -0.4
Joe McEwing 27 – 87-0.2 – –
Kurt Abbott 31 FA-elig 79-0.3 0.5 -0.9
Jason Tyner↔ TBR 23 – 13-0.3 – –
Rich Rodriguez 37 FA-elig 32-0.4 0.6 -1.1
Rickey Henderson↔ SEA 41 FA-elig 31-0.5 0.5 -1.2
Pat Mahomes 29 FA-elig 53-0.5 0.8 -1.5
Rey Ordonez 29 arb 45-0.7 2.2 -3.3

Key additions (new vs 1999)

PlayerfWAR
Mike Hampton5.2
Todd Zeile2.7
Derek Bell1.4
Lenny Harris0.8
Timo Perez0.3
Jon Nunnally0.2

Key subtractions (gone from 1999)

Player1999 fWAR
John Olerud5.8
Orel Hershiser1.8
Roger Cedeno1.5
Masato Yoshii1.2
Kenny Rogers1.1
Octavio Dotel0.7

Current & Historical Payroll

2000 payroll
$80.2M

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 (21)

PlayerAgeSvc2000200120022003200420052006
Mike Piazza318.000$12.1M$13.6M$10.6M$15.6M$16.1M$16.1MFREE AGENT
Robin Ventura3211.000$8.0M$8.0MFREE AGENT
Al Leiter3413.000$7.8M$9.8M$9.2M$8.0M$10.3MFREE AGENT
Mike Hampton277.000$5.8MFREE AGENT
Bobby Jones307.000$5.4MFREE AGENT
Derek Bell319.000$5.0MFREE AGENT
Rick Reed3512.000$4.4M$4.2MFREE AGENT
Todd Zeile3411.000$4.3M$6.8MFREE AGENT$1.0M
Darryl Hamilton3512.000$3.6M$3.3MFREE AGENT
Armando Benitez276.000$3.4M$5.8M$5.8M$4.5MFREE AGENT
John Franco3916.000$3.4M$3.6MFREE AGENT$3.8M$1.0M
Dennis Cook3712.000$2.2M$1.7MFREE AGENT
Turk Wendell337.000$2.1M$2.2MFREE AGENT
Mike Bordick3410.000$1.1MFREE AGENT
Pat Mahomes298.000$750kFREE AGENT
Lenny Harris3512.000$746k$1.1MFREE AGENT
Rich Rodriguez3710.000$600kFREE AGENT
Rickey Henderson4121.000$504kFREE AGENT
Todd Pratt338.000$500k$338kFREE AGENT
Kurt Abbott317.000$500kFREE AGENT
Rick White316.000$215k$1.1MFREE AGENT

Arbitration-eligible (12)

PlayerAgeSvc2000200120022003200420052006
Edgardo Alfonzo265.000$4.2MFREE AGENT
Rey Ordonez294.000$2.2MARB 3FREE AGENT
Matt Franco305.000$462kFREE AGENT
Jon Nunnally285.000$260kFREE AGENT
Jorge Velandia253.000$100kARB 2ARB 3FREE AGENT
Bubba Trammell283.000$89kARB 2ARB 3FREE AGENT
Mark Johnson325.000—FREE AGENT
Bobby Jones283.000—ARB 2ARB 3FREE AGENT
Ryan McGuire283.000—ARB 2ARB 3FREE AGENT
Bill Pulsipher265.000—FREE AGENT
Glendon Rusch253.000—ARB 2ARB 3FREE AGENT
Dennis Springer355.000—FREE AGENT

Pre-arbitration (14)

PlayerAgeSvc2000200120022003200420052006
Benny Agbayani282.000$220kARB 1ARB 2ARB 3FREE AGENT
Jay Payton272.000$215kARB 1ARB 2ARB 3FREE AGENT
Melvin Mora281.000$126kPre-ArbARB 1ARB 2ARB 3FREE AGENT
Vance Wilson271.000—Pre-ArbARB 1ARB 2ARB 3FREE AGENT
Joe McEwing272.000—ARB 1ARB 2ARB 3FREE AGENT
Mike Kinkade272.000—ARB 1ARB 2ARB 3FREE AGENT
David Lamb251.000—Pre-ArbARB 1ARB 2ARB 3FREE AGENT
Grant Roberts220.000—Pre-ArbPre-ArbARB 1ARB 2ARB 3FREE AGENT
Jorge Toca29–—
Jason Tyner230.000—Pre-ArbPre-ArbARB 1ARB 2ARB 3FREE AGENT
Eric Cammack24–—
Jim Mann25–—
Jerrod Riggan260.000—Pre-ArbPre-ArbARB 1ARB 2ARB 3FREE AGENT
Timo Perez250.000—Pre-ArbPre-ArbARB 1ARB 2ARB 3FREE AGENT

Graphs

Every roster slot ranked best→worst by WAR. Bars = Mets 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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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:'NYM',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);});