RRosternomics
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Nationals WSN

‹ ›

GM: Michael Rizzo

Overview

CONTEND ↗ rising
expensive & winning · year 4 in this regime · payroll 1.38× league · TAB +8.0
+8.0TAB — talent above budget7th/30
+11.0WAB — realized wins (TAB + luck)6th/30
10.0depth — 2+ WAR regulars4th/30
-6.1dead WAR — sub-replacement drag19th/30
33%dead money %13th/30
0.599win %4th/30
46.1roster fWAR5th/30
-25surplus $M (value vs cost)18th/30
$181Mpayroll $M4th/30

2017: made playoffs · 97–65. Ranks are vs the 30 teams that season.

Roster

CFMichael A. Taylor 111GBrian Goodwin 34GAdam Eaton 20G
LFHowie Kendrick 62GJayson Werth 51GBrian Goodwin 31G
RFBryce Harper 110GJayson Werth 16GAlejandro De Aza 14G
SSTrea Turner 95GWilmer Difo 57GStephen Drew 13G
2BDaniel Murphy 139GWilmer Difo 25GHowie Kendrick 15G
3BAnthony Rendon 145GStephen Drew 11GAdrián Sanchez 7G
1BRyan Zimmerman 143GAdam Lind 39GHowie Kendrick 4G
STARTERSMax Scherzer 6.7WARStephen Strasburg 6.0WARGio Gonzalez 3.5WARTanner Roark 2.5WARJoe Ross 0.7WAR
CMatt Wieters 118GJose Lobatón 50GPedro Severino 10G
DHAdam Lind 7GJayson Werth 2GPedro Severino 1G
BULLPEN★ Brandon Kintzler 29svRyan Madson 25hMatt Albers 14hOliver Pérez 12hEnny Romero 10hSean Doolittle 9hJoe Blanton 7hMatt Grace 4h
CMatt Wieters 118 · Jose Lobatón 50 · Pedro Severino 10
1BRyan Zimmerman 143 · Adam Lind 39 · Howie Kendrick 4
2BDaniel Murphy 139 · Wilmer Difo 25 · Howie Kendrick 15
3BAnthony Rendon 145 · Stephen Drew 11 · Adrián Sanchez 7
SSTrea Turner 95 · Wilmer Difo 57 · Stephen Drew 13
LFHowie Kendrick 62 · Jayson Werth 51 · Brian Goodwin 31
CFMichael A. Taylor 111 · Brian Goodwin 34 · Adam Eaton 20
RFBryce Harper 110 · Jayson Werth 16 · Alejandro De Aza 14
DHAdam Lind 7 · Jayson Werth 2 · Pedro Severino 1
SPMax Scherzer 6.7 · Stephen Strasburg 6.0 · Gio Gonzalez 3.5 · Tanner Roark 2.5 · Joe Ross 0.7
BP★ Brandon Kintzler 29 · Ryan Madson 25 · Matt Albers 14 · Oliver Pérez 12 · Enny Romero 10 · Sean Doolittle 9 · Joe Blanton 7 · Matt Grace 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.

2017 roster — value & surplus

PlayerAgeServiceGfWARSalary $MSurplus $M
Max Scherzer 32 FA-elig 316.7 22.1 +0.4
Stephen Strasburg 28 FA-elig 286.0 18.3 +1.9
Anthony Rendon 27 arb 1475.9 5.8 +14.1
Bryce Harper 24 arb 1114.1 13.6 +0.3
Daniel Murphy 32 FA-elig 1443.6 12.0 +0.3
Gio Gonzalez 31 FA-elig 323.5 12.0 -0.1
Ryan Zimmerman 32 FA-elig 1443.5 14.0 -2.2
Trea Turner 24 pre-arb 983.1 0.6 +9.9
Michael A. Taylor 26 arb 1182.9 0.6 +9.2
Tanner Roark 30 arb 322.5 4.3 +4.0
Wilmer Difo 25 pre-arb 1241.2 0.5 +3.5
Sean Doolittle↔ OAK 30 arb 301.1 1.5 +2.1
Matt Albers 34 FA-elig 631.0 1.1 +2.1
Ryan Madson↔ OAK 36 FA-elig 200.9 2.6 +0.6
Adam Lind 33 FA-elig 1160.9 1.0 +2.0
Adam Eaton 28 arb 230.8 4.0 -1.4
Joe Ross 24 pre-arb 200.7 0.4 +1.9
Koda Glover 24 pre-arb 230.6 0.5 +1.6
Howie Kendrick↔ PHI 33 FA-elig 520.6 5.7 -3.7
Brian Goodwin 26 pre-arb 740.5 0.4 +1.3
Enny Romero 26 arb 530.4 0.6 +1.0
Oliver Pérez 35 FA-elig 500.4 4.0 -2.7
Blake Treinen↔ OAK 29 arb 370.4 0.3 +1.0
Brandon Kintzler↔ MIN 32 FA-elig 270.3 1.1 -0.1
Matt Grace 28 pre-arb 400.3 0.4 +0.6
A.J. Cole 25 pre-arb 110.2 0.2 +0.6
Adrián Sanchez 26 – 340.1 0.2 -0.1
Sammy Solís 28 pre-arb 300.1 0.5 -0.4
Victor Robles 20 – 13-0.0 0.1 -0.1
Austin Adams 26 – 6-0.0 0.1 -0.1
Ryan Raburn 36 FA-elig 25-0.0 0.3 -0.4
Stephen Drew 34 FA-elig 46-0.1 3.5 -3.7
Raudy Read 23 – 8-0.1 0.1 -0.3
Grant Green 29 – 2-0.1 0.0 -0.3
Trevor Gott 24 pre-arb 4-0.1 0.0 -0.3
Jeremy Guthrie 38 – 1-0.1 0.0 -0.3
Edwin Jackson↔ BAL 33 FA-elig 19-0.1 2.1 -2.6
Jayson Werth 38 FA-elig 70-0.1 21.0 -21.5
Joe Blanton 36 FA-elig 51-0.2 4.0 -4.6
Pedro Severino 23 pre-arb 17-0.3 0.1 -1.0
Rafael Bautista 24 – 17-0.3 0.1 -1.0
Alejandro De Aza 33 – 28-0.3 0.1 -1.1
Andrew Stevenson 23 – 37-0.3 0.2 -1.2
Erick Fedde 24 – 3-0.3 0.1 -1.1
Jacob Turner 26 FA-elig 18-0.4 1.5 -3.0
Chris Heisey 32 FA-elig 38-0.5 1.4 -3.2
Jose Lobatón 32 FA-elig 51-0.6 1.6 -3.6
Shawn Kelley 33 FA-elig 33-1.1 5.5 -9.3
Matt Wieters 31 FA-elig 123-1.2 10.5 -14.4

Key additions (new vs 2016)

PlayerfWAR
Sean Doolittle1.1
Matt Albers1.0
Ryan Madson0.9
Adam Lind0.9
Adam Eaton0.8
Howie Kendrick0.6

Key subtractions (gone from 2016)

Player2016 fWAR
Wilson Ramos4.1
Danny Espinosa1.0
Mark Melancon1.0
Felipe Vázquez0.7
Matt Belisle0.7
Reynaldo López0.5

Current & Historical Payroll

2017 payroll
$180.9M
2018 guaranteed
$0M

What the front office was committed to as of 2017, 2017–2023. Guaranteed $ are contract commitments signed by 2017; 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 (20)

PlayerAgeSvc2017201820192020202120222023
Max Scherzer328.079$22.1MFREE AGENT
Jayson Werth3813.102$21.0MFREE AGENT
Stephen Strasburg286.118$18.3MFREE AGENT
Ryan Zimmerman3211.032$14.0MFREE AGENT
Gio Gonzalez317.162$12.0MFREE AGENT
Daniel Murphy327.109$12.0MFREE AGENT
Matt Wieters317.129$10.5MFREE AGENT
Howie Kendrick3310.091$5.7MFREE AGENT
Shawn Kelley337.128$5.5MFREE AGENT
Oliver Pérez3512.144$4.0MFREE AGENT
Joe Blanton3610.158$4.0MFREE AGENT
Stephen Drew3410.038$3.5MFREE AGENT
Ryan Madson3611.155$2.6MFREE AGENT
Edwin Jackson3311.031$2.1MFREE AGENT
Chris Heisey327.000$1.4MFREE AGENT
Matt Albers349.141$1.1MFREE AGENT
Adam Lind339.058$1.0MFREE AGENT
Ryan Raburn369.109$348kFREE AGENT
Alejandro De Aza3310.000$137kFREE AGENT
Jeremy Guthrie3810.130$3kFREE AGENT

Arbitration-eligible (9)

PlayerAgeSvc2017201820192020202120222023
Bryce Harper244.159$13.6MARB 3FREE AGENT
Anthony Rendon273.130$5.8MARB 2ARB 3FREE AGENT
Tanner Roark303.055$4.3MARB 2ARB 3FREE AGENT
Adam Eaton284.030$4.0MARB 3FREE AGENT
Jose Lobatón325.138$1.6MFREE AGENT
Jacob Turner263.111$1.5MARB 2ARB 3FREE AGENT
Sean Doolittle304.122$1.5MARB 3FREE AGENT
Brandon Kintzler325.003$1.1MFREE AGENT
Michael A. Taylor263.000$558kARB 2ARB 3FREE AGENT

Pre-arbitration (20)

PlayerAgeSvc2017201820192020202120222023
Trea Turner240.135$555kPre-ArbPre-ArbARB 1ARB 2ARB 3FREE AGENT
Enny Romero261.072$551kPre-ArbARB 1ARB 2ARB 3FREE AGENT
Sammy Solís281.084$546kPre-ArbARB 1ARB 2ARB 3FREE AGENT
Koda Glover240.051$538kPre-ArbPre-ArbARB 1ARB 2ARB 3FREE AGENT
Wilmer Difo250.110$538kPre-ArbPre-ArbARB 1ARB 2ARB 3FREE AGENT
Joe Ross241.094$434kPre-ArbARB 1ARB 2ARB 3FREE AGENT
Brian Goodwin260.044$427kPre-ArbPre-ArbARB 1ARB 2ARB 3FREE AGENT
Matt Grace280.145$377kPre-ArbPre-ArbARB 1ARB 2ARB 3FREE AGENT
Blake Treinen292.065$290kARB 1ARB 2ARB 3FREE AGENT
Adrián Sanchez260.000$246kPre-ArbPre-ArbARB 1ARB 2ARB 3FREE AGENT
Andrew Stevenson230.000$175kPre-ArbPre-ArbARB 1ARB 2ARB 3FREE AGENT
A.J. Cole250.092$167kPre-ArbPre-ArbARB 1ARB 2ARB 3FREE AGENT
Pedro Severino230.094$137kPre-ArbPre-ArbARB 1ARB 2ARB 3FREE AGENT
Erick Fedde240.000$105kPre-ArbPre-ArbARB 1ARB 2ARB 3FREE AGENT
Rafael Bautista240.000$102kPre-ArbPre-ArbARB 1ARB 2ARB 3FREE AGENT
Austin Adams262.002$102kARB 1ARB 2ARB 3FREE AGENT
Raudy Read230.000$91kPre-ArbPre-ArbARB 1ARB 2ARB 3FREE AGENT
Victor Robles200.000$73kPre-ArbPre-ArbARB 1ARB 2ARB 3FREE AGENT
Grant Green292.033$26kARB 1ARB 2ARB 3FREE AGENT
Trevor Gott240.145$20kPre-ArbPre-ArbARB 1ARB 2ARB 3FREE AGENT

Graphs

Every roster slot ranked best→worst by WAR. Bars = Nationals 2017; 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.

'; return; } const f=+document.getElementById('yfrom').value, t=+document.getElementById('yto').value, w=+document.getElementById('win').value; document.getElementById('yflab').textContent=f; document.getElementById('ytlab').textContent=t; document.getElementById('winlab').textContent = w===1?'raw':(w+'-yr'); const dark=document.documentElement.getAttribute('data-theme')==='dark'; const ink=dark?'#cdd4dc':'#1d2630', grid=dark?'#2c313a':'#d6dbe2', refc=dark?'#5a636d':'#9aa3ad', dirc=dark?'#ffffff':'#1d2630'; const col=contrastColor(TEAMCOL,dark); function sm(a,w){const h=(w-1)/2,o=[];for(let i=0;id[0]>=f&&d[0]<=t); if(raw.length<2){ Plotly.purge('orbit'); orbEl.innerHTML='

Pick a wider year range.

'; return; } const s=sm(raw,w),n=s.length,X=s.map(d=>Math.round(d[1]*100)/100),Y=s.map(d=>Math.round(d[2]*10)/10),yr=s.map(d=>d[0]); let xa=Math.min(1,...X),xb=Math.max(1,...X),ya=Math.min(0,...Y),yb=Math.max(0,...Y); const px=(xb-xa)*.12+.04,py=(yb-ya)*.12+1.5;xa-=px;xb+=px;ya-=py;yb+=py; const k=Math.max(0,n-3), ann=[]; [['WINDOW','#15b6a0',xa<1&&yb>0,xa,yb,'left','top'],['CONTEND','#2f7ed8',xb>1&&yb>0,xb,yb,'right','top'], ['FORCED-SPEND','#ec5a3c',xb>1&&ya<0,xb,ya,'right','bottom'],['REBUILD','#f0a91c',xa<1&&ya<0,xa,ya,'left','bottom']].forEach(q=>{ if(q[2]) ann.push({x:q[3],y:q[4],xref:'x',yref:'y',text:q[0],showarrow:false,xanchor:q[5],yanchor:q[6],font:{size:10,color:q[1]},opacity:.85});}); ann.push({x:X[n-1],y:Y[n-1],ax:X[n-1]-0.5*(X[n-1]-X[k]),ay:Y[n-1]-0.5*(Y[n-1]-Y[k]),xref:'x',yref:'y',axref:'x',ayref:'y',showarrow:true,arrowhead:2,arrowsize:1.3,arrowwidth:1.7,arrowcolor:dirc,text:''}); Plotly.newPlot('orbit',[{x:X,y:Y,mode:'lines+markers',line:{color:col,width:2.6,shape:'spline',smoothing:0.7}, marker:{color:col,size:s.map((d,i)=>5+7*(i/Math.max(1,n-1))),line:{color:dark?'#1b1e23':'#fff',width:0.6}}, text:yr,hovertemplate:'%{text}
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:'WSN',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);});