RRosternomics
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Mets NYM

‹ ›

GM: Billy Eppler

Overview

CONTEND → steady
expensive & winning · year 1 in this regime · payroll 1.83× league · TAB +11.1
+11.1TAB — talent above budget8th/30
+11.5WAB — realized wins (TAB + luck)6th/30
12.0depth — 2+ WAR regulars2nd/30
-4.0dead WAR — sub-replacement drag10th/30
17%dead money %1st/30
0.623win %3rd/30
52.6roster fWAR4th/30
-69surplus $M (value vs cost)25th/30
$262Mpayroll $M2nd/30

2022: made playoffs · 101–61. Ranks are vs the 30 teams that season.

Roster

CFBrandon Nimmo 151GMark Canha 11GTerrance Gore 3G
LFMark Canha 123GJeff McNeil 34GDarin Ruf 29G
RFStarling Marte 116GTyler Naquin 68GJeff McNeil 13G
SSFrancisco Lindor 159GLuis Guillorme 15GDeven Marrero 3G
2BJeff McNeil 106GLuis Guillorme 67GEduardo Escobar 2G
3BEduardo Escobar 130GLuis Guillorme 22GBrett Baty 11G
1BPete Alonso 134GDarin Ruf 45GDominic Smith 37G
STARTERSMax Scherzer 4.5WARChris Bassitt 2.8WARTaijuan Walker 2.7WARCarlos Carrasco 2.5WARJacob deGrom 2.2WAR
CTomás Nido 96GJames McCann 60GMichael Pérez 44G
DHDaniel Vogelbach 116GDarin Ruf 36GPete Alonso 27G
BULLPEN★ Edwin Díaz 32svAdam Ottavino 19hSeth Lugo 16hDrew Smith 14hJoely Rodríguez 9hMychal Givens 7hTrevor May 6hChasen Shreve 4h
CTomás Nido 96 · James McCann 60 · Michael Pérez 44
1BPete Alonso 134 · Darin Ruf 45 · Dominic Smith 37
2BJeff McNeil 106 · Luis Guillorme 67 · Eduardo Escobar 2
3BEduardo Escobar 130 · Luis Guillorme 22 · Brett Baty 11
SSFrancisco Lindor 159 · Luis Guillorme 15 · Deven Marrero 3
LFMark Canha 123 · Jeff McNeil 34 · Darin Ruf 29
CFBrandon Nimmo 151 · Mark Canha 11 · Terrance Gore 3
RFStarling Marte 116 · Tyler Naquin 68 · Jeff McNeil 13
DHDaniel Vogelbach 116 · Darin Ruf 36 · Pete Alonso 27
SPMax Scherzer 4.5 · Chris Bassitt 2.8 · Taijuan Walker 2.7 · Carlos Carrasco 2.5 · Jacob deGrom 2.2
BP★ Edwin Díaz 32 · Adam Ottavino 19 · Seth Lugo 16 · Drew Smith 14 · Joely Rodríguez 9 · Mychal Givens 7 · Trevor May 6 · Chasen Shreve 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.

2022 roster — value & surplus

PlayerAgeServiceGfWARSalary $MSurplus $M
Francisco Lindor 28 FA-elig 1616.4 34.1 -10.8
Jeff McNeil 30 arb 1485.5 3.0 +17.2
Brandon Nimmo 29 FA-elig 1515.5 7.0 +13.1
Max Scherzer 37 FA-elig 234.5 43.3 -26.9
Pete Alonso 27 arb 1603.8 7.4 +6.6
Starling Marte 33 FA-elig 1183.5 15.8 -2.9
Edwin Díaz 28 FA-elig 613.0 10.2 +0.8
Chris Bassitt 33 FA-elig 302.8 8.7 +1.7
Taijuan Walker 29 FA-elig 292.7 7.0 +2.8
Mark Canha 33 FA-elig 1402.5 13.0 -3.8
Carlos Carrasco 35 FA-elig 292.5 12.0 -2.8
Jacob deGrom 34 FA-elig 112.2 35.5 -27.3
Eduardo Escobar 33 FA-elig 1361.9 10.0 -3.1
Luis Guillorme 27 arb 1021.8 0.9 +5.6
David Peterson 26 pre-arb 281.5 0.5 +5.1
Tomás Nido 28 arb 981.4 0.9 +4.1
Adam Ottavino 36 FA-elig 661.1 4.0 +0.2
Daniel Vogelbach↔ PIT 29 FA-elig 550.9 0.3 +3.1
Trevor Williams 30 FA-elig 300.7 3.9 -1.4
Tylor Megill 26 pre-arb 150.7 0.7 +1.7
Joely Rodríguez 30 pre-arb 550.4 2.6 -1.1
Colin Holderman↔ PIT 26 – 150.4 0.2 +1.3
Seth Lugo 32 FA-elig 620.3 2.9 -2.0
James McCann 32 FA-elig 610.1 8.2 -7.7
J.D. Davis↔ SFG 29 arb 660.1 1.6 -1.2
Trevor May 32 FA-elig 260.1 7.8 -7.4
Francisco Alvarez 20 – 50.1 0.0 +0.3
Bryce Montes de Oca 26 – 30.1 0.1 +0.1
Tyler Naquin↔ CIN 31 FA-elig 490.1 1.9 -1.7
Khalil Lee 24 pre-arb 20.0 0.0 +0.1
Rob Zastryzny↔ ANA 30 – 10.0 0.0 +0.1
Patrick Mazeika 28 – 240.0 0.2 -0.1
Adonis Medina 25 pre-arb 140.0 0.2 -0.2
Sam Clay↔ WSN 29 pre-arb 10.0 0.0 +0.0
Terrance Gore 31 pre-arb 100.0 0.1 -0.1
Alex Claudio 30 FA-elig 30.0 0.1 -0.1
Michael Pérez↔ PIT 29 arb 60.0 0.0 -0.0
Nate Fisher 26 – 1-0.0 0.0 -0.0
Tommy Hunter 35 FA-elig 18-0.0 0.7 -0.7
Drew Smith 28 arb 44-0.0 0.8 -0.8
Matt Reynolds↔ CIN 31 – 1-0.0 0.0 -0.1
Yolmer Sánchez↔ BOS 30 arb 3-0.0 0.0 -0.1
Mychal Givens↔ CHC 32 FA-elig 19-0.0 1.1 -1.3
José Buttó 24 – 1-0.1 0.0 -0.2
Sean Reid-Foley 26 pre-arb 7-0.1 0.7 -1.0
Stephen Nogosek 27 pre-arb 12-0.1 0.3 -0.5
Travis Blankenhorn 25 pre-arb 1-0.1 0.0 -0.3
Deven Marrero 31 pre-arb 5-0.1 0.1 -0.4
Yoan López 29 pre-arb 8-0.1 0.1 -0.4
Ender Inciarte 31 – 11-0.1 0.1 -0.5
Travis Jankowski↔ SEA 31 FA-elig 43-0.1 1.2 -1.6
Brett Baty 22 – 11-0.1 0.2 -0.6
Nick Plummer 25 – 14-0.1 0.1 -0.6
Jake Reed↔ BAL 29 – 5-0.2 0.0 -0.8
Mark Vientos 22 – 16-0.2 0.1 -0.9
Dominic Smith 27 arb 58-0.2 4.0 -4.8
Chasen Shreve 31 FA-elig 25-0.3 0.7 -1.6
R.J. Alvarez 31 pre-arb 1-0.3 0.0 -1.0
Thomas Szapucki↔ SFG 26 – 1-0.4 0.0 -1.6
Robinson Canó↔ ATL 39 FA-elig 12-0.5 7.2 -8.9
Darin Ruf↔ SFG 35 FA-elig 29-0.9 0.7 -3.9

Key additions (new vs 2021)

PlayerfWAR
Max Scherzer4.5
Starling Marte3.5
Chris Bassitt2.8
Mark Canha2.5
Eduardo Escobar1.9
Adam Ottavino1.1

Key subtractions (gone from 2021)

Player2021 fWAR
Marcus Stroman3.6
Javier Báez2.0
Jonathan Villar2.0
Aaron Loup1.6
Michael Conforto1.5
Rich Hill1.0

Current & Historical Payroll

2022 payroll
$262.2M
2023 guaranteed
$34.1M

What the front office was committed to as of 2022, 2022–2028. Guaranteed $ are contract commitments signed by 2022; 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 (19)

PlayerAgeSvc2022202320242025202620272028
Max Scherzer3713.079$43.3MFREE AGENT
Jacob deGrom347.139$35.5MFREE AGENT
Francisco Lindor286.113$34.1M$34.1M$34.2M$34.1M$32.5M$32.5M$32.5M
Starling Marte338.162$15.8MFREE AGENT
Mark Canha336.092$13.0MFREE AGENT
Carlos Carrasco3510.147$12.0MFREE AGENT
Eduardo Escobar339.128$10.0MFREE AGENT
James McCann327.028$8.2MFREE AGENT
Trevor May327.012$7.8MFREE AGENT
Robinson Canó3917.000$7.2MFREE AGENT
Taijuan Walker297.142$7.0MFREE AGENT
Adam Ottavino3610.087$4.0MFREE AGENT
Travis Jankowski317.000$1.2MFREE AGENT
Mychal Givens326.069$1.1MFREE AGENT
Tommy Hunter3512.045$700kFREE AGENT
Chasen Shreve318.000$700kFREE AGENT
Daniel Vogelbach296.000$338kFREE AGENT
Alex Claudio306.063$100kFREE AGENT
Ender Inciarte318.000$97kFREE AGENT

Arbitration-eligible (15)

PlayerAgeSvc2022202320242025202620272028
Edwin Díaz285.121$10.2MFREE AGENT
Chris Bassitt335.130$8.7MFREE AGENT
Pete Alonso273.000$7.4MARB 2ARB 3FREE AGENT
Brandon Nimmo295.042$7.0MFREE AGENT
Dominic Smith273.146$4.0MARB 2ARB 3FREE AGENT
Trevor Williams305.027$3.9MFREE AGENT
Jeff McNeil303.069$3.0MARB 2ARB 3FREE AGENT
Seth Lugo325.082$2.9MFREE AGENT
Tyler Naquin315.032$1.9MFREE AGENT
J.D. Davis293.137$1.6MARB 2ARB 3FREE AGENT
Tomás Nido283.089$890kARB 2ARB 3FREE AGENT
Drew Smith283.034$750kARB 2ARB 3FREE AGENT
Darin Ruf354.138$731kARB 3FREE AGENT
Michael Pérez293.000$35kARB 2ARB 3FREE AGENT
Yolmer Sánchez305.040$20kFREE AGENT

Pre-arbitration (27)

PlayerAgeSvc2022202320242025202620272028
Joely Rodríguez302.096$2.6MARB 1ARB 2ARB 3FREE AGENT
Luis Guillorme272.167$875kARB 1ARB 2ARB 3FREE AGENT
Sean Reid-Foley261.093$718kPre-ArbARB 1ARB 2ARB 3FREE AGENT
Tylor Megill260.103$708kPre-ArbPre-ArbARB 1ARB 2ARB 3FREE AGENT
David Peterson262.000$477kARB 1ARB 2ARB 3FREE AGENT
Stephen Nogosek270.080$262kPre-ArbPre-ArbARB 1ARB 2ARB 3FREE AGENT
Patrick Mazeika280.080$219kPre-ArbPre-ArbARB 1ARB 2ARB 3FREE AGENT
Adonis Medina250.027$212kPre-ArbPre-ArbARB 1ARB 2ARB 3FREE AGENT
Brett Baty220.000$188kPre-ArbPre-ArbARB 1ARB 2ARB 3FREE AGENT
Colin Holderman260.000$156kPre-ArbPre-ArbARB 1ARB 2ARB 3FREE AGENT
Nick Plummer25–$135k
Terrance Gore312.013$135kARB 1ARB 2ARB 3FREE AGENT
Bryce Montes de Oca26–$123k
Yoan López292.058$108kARB 1ARB 2ARB 3FREE AGENT
Mark Vientos220.000$96kPre-ArbPre-ArbARB 1ARB 2ARB 3FREE AGENT
Deven Marrero312.067$62kARB 1ARB 2ARB 3FREE AGENT
Jake Reed290.051$34kPre-ArbPre-ArbARB 1ARB 2ARB 3FREE AGENT
Khalil Lee240.019$27kPre-ArbPre-ArbARB 1ARB 2ARB 3FREE AGENT
R.J. Alvarez310.091$23kPre-ArbPre-ArbARB 1ARB 2ARB 3FREE AGENT
Francisco Alvarez200.000$19kPre-ArbPre-ArbARB 1ARB 2ARB 3FREE AGENT
Rob Zastryzny300.100$10kPre-ArbPre-ArbARB 1ARB 2ARB 3FREE AGENT
Sam Clay290.161$9kPre-ArbPre-ArbARB 1ARB 2ARB 3FREE AGENT
Thomas Szapucki260.022$8kPre-ArbPre-ArbARB 1ARB 2ARB 3FREE AGENT
Matt Reynolds311.093$7kPre-ArbARB 1ARB 2ARB 3FREE AGENT
Travis Blankenhorn250.054$4kPre-ArbPre-ArbARB 1ARB 2ARB 3FREE AGENT
José Buttó240.000$4kPre-ArbPre-ArbARB 1ARB 2ARB 3FREE AGENT
Nate Fisher26–$4k

Graphs

Every roster slot ranked best→worst by WAR. Bars = Mets 2022; 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);});