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Home/NFL WR Advanced Stats: Target Share, EPA & Separation

NFL WR Advanced Stats: Target Share, EPA & Separation

Receiving yards are an output. The inputs are target share (role), EPA per target (what the offense gets when the ball goes his way), and the tracking-data layer underneath — separation at the catch point, YAC over expected, and drop rate. This board ranks every qualifying NFL wide receiver on all of it, updated every morning in season.

The chart plots role against efficiency: how much of the offense runs through a receiver versus what he does with it. Elite is the top-right — heavy usage, high per-target value. The bottom-right quadrant is the one that costs bettors money: volume-dependent receivers whose counting stats are a product of target hoarding rather than efficiency, priced by the market like the numbers were earned. The regression flags run the same audit at the player level — a receiver producing well ahead of his separation and YAC profile gets a red triangle before the market notices.

WR Efficiency Lab — 2025 season
EPA/target · target share · separation & ball skills — min 50 targets · updated 10.9h ago
6.0-0.5214.1-0.1922.30.1530.40.4838.50.81efficient in small doseselitestrugglingvolume-dependentPuka Nacua (LA): 0.70 EPA/tgt, 28.6 TgtSh%Stefon Diggs (NE): 0.69 EPA/tgt, 21.2 TgtSh%Alec Pierce (IND): 0.66 EPA/tgt, 15.9 TgtSh%George Pickens (DAL): 0.65 EPA/tgt, 22.6 TgtSh%Christian Watson (GB): 0.59 EPA/tgt, 12.0 TgtSh%Jaxon Smith-Njigba (SEA): 0.56 EPA/tgt, 35.8 TgtSh%Jameson Williams (DET): 0.55 EPA/tgt, 18.6 TgtSh%Terry McLaurin (WAS): 0.53 EPA/tgt, 13.9 TgtSh%Ryan Flournoy (DAL): 0.51 EPA/tgt, 9.2 TgtSh%Ricky Pearsall (SF): 0.50 EPA/tgt, 9.6 TgtSh%Luther Burden III (CHI): 0.50 EPA/tgt, 11.3 TgtSh%DeVonta Smith (PHI): 0.48 EPA/tgt, 24.4 TgtSh%Marvin Harrison Jr. (ARI): 0.43 EPA/tgt, 11.8 TgtSh%Mack Hollins (NE): 0.42 EPA/tgt, 13.5 TgtSh%Romeo Doubs (GB): 0.41 EPA/tgt, 18.5 TgtSh%Zay Flowers (BAL): 0.39 EPA/tgt, 29.0 TgtSh%Kendrick Bourne (SF): 0.39 EPA/tgt, 9.6 TgtSh%Courtland Sutton (DEN): 0.37 EPA/tgt, 21.2 TgtSh%Tee Higgins (CIN): 0.37 EPA/tgt, 16.1 TgtSh%Jaylen Waddle (MIA): 0.35 EPA/tgt, 21.7 TgtSh%DK Metcalf (PIT): 0.33 EPA/tgt, 19.0 TgtSh%Nico Collins (HOU): 0.33 EPA/tgt, 21.7 TgtSh%Amon-Ra St. Brown (DET): 0.32 EPA/tgt, 31.3 TgtSh%Parker Washington (JAX): 0.31 EPA/tgt, 17.4 TgtSh%Marquise Brown (KC): 0.30 EPA/tgt, 13.5 TgtSh%Chris Godwin Jr. (TB): 0.29 EPA/tgt, 9.4 TgtSh%Keenan Allen (LAC): 0.29 EPA/tgt, 22.4 TgtSh%Darius Slayton (NYG): 0.29 EPA/tgt, 12.5 TgtSh%Quentin Johnston (LAC): 0.29 EPA/tgt, 15.4 TgtSh%A.J. Brown (PHI): 0.28 EPA/tgt, 26.1 TgtSh%CeeDee Lamb (DAL): 0.25 EPA/tgt, 19.3 TgtSh%Jayden Higgins (HOU): 0.25 EPA/tgt, 12.3 TgtSh%Davante Adams (LA): 0.24 EPA/tgt, 19.6 TgtSh%Tre Tucker (LV): 0.24 EPA/tgt, 18.6 TgtSh%Rome Odunze (CHI): 0.23 EPA/tgt, 16.9 TgtSh%Chris Olave (NO): 0.23 EPA/tgt, 27.6 TgtSh%Xavier Hutchinson (HOU): 0.23 EPA/tgt, 10.3 TgtSh%Ja'Marr Chase (CIN): 0.22 EPA/tgt, 30.4 TgtSh%Drake London (ATL): 0.22 EPA/tgt, 21.6 TgtSh%Jalen Nailor (MIN): 0.22 EPA/tgt, 11.3 TgtSh%Keon Coleman (BUF): 0.21 EPA/tgt, 12.3 TgtSh%Tetairoa McMillan (CAR): 0.21 EPA/tgt, 25.4 TgtSh%Rashee Rice (KC): 0.21 EPA/tgt, 14.2 TgtSh%Michael Wilson (ARI): 0.20 EPA/tgt, 20.4 TgtSh%Xavier Worthy (KC): 0.20 EPA/tgt, 13.3 TgtSh%Michael Pittman (IND): 0.20 EPA/tgt, 20.9 TgtSh%Andrei Iosivas (CIN): 0.20 EPA/tgt, 9.5 TgtSh%Brian Thomas Jr. (JAX): 0.19 EPA/tgt, 16.6 TgtSh%Deebo Samuel Sr. (WAS): 0.18 EPA/tgt, 22.9 TgtSh%Jordan Addison (MIN): 0.18 EPA/tgt, 16.9 TgtSh%Van Jefferson (TEN): 0.17 EPA/tgt, 9.8 TgtSh%DJ Moore (CHI): 0.16 EPA/tgt, 16.0 TgtSh%Wan'Dale Robinson (NYG): 0.14 EPA/tgt, 27.8 TgtSh%Cooper Kupp (SEA): 0.11 EPA/tgt, 15.4 TgtSh%Josh Downs (IND): 0.10 EPA/tgt, 16.6 TgtSh%Troy Franklin (DEN): 0.09 EPA/tgt, 17.8 TgtSh%Jakobi Meyers (JAX): 0.09 EPA/tgt, 22.3 TgtSh%Mike Evans (TB): 0.09 EPA/tgt, 11.5 TgtSh%Khalil Shakir (BUF): 0.08 EPA/tgt, 19.8 TgtSh%Marvin Mims Jr. (DEN): 0.07 EPA/tgt, 8.7 TgtSh%Ladd McConkey (LAC): 0.07 EPA/tgt, 19.5 TgtSh%Emeka Egbuka (TB): 0.06 EPA/tgt, 23.5 TgtSh%Darnell Mooney (ATL): 0.05 EPA/tgt, 13.9 TgtSh%Chimere Dike (TEN): 0.02 EPA/tgt, 14.0 TgtSh%Jauan Jennings (SF): -0.03 EPA/tgt, 16.4 TgtSh%Garrett Wilson (NYJ): -0.04 EPA/tgt, 12.5 TgtSh%Rashid Shaheed (SEA): -0.05 EPA/tgt, 16.3 TgtSh%Sterling Shepard (TB): -0.05 EPA/tgt, 9.8 TgtSh%Olamide Zaccheaus (CHI): -0.06 EPA/tgt, 12.2 TgtSh%Xavier Legette (CAR): -0.06 EPA/tgt, 13.3 TgtSh%Calvin Austin III (PIT): -0.08 EPA/tgt, 10.5 TgtSh%Justin Jefferson (MIN): -0.10 EPA/tgt, 30.1 TgtSh%Elic Ayomanor (TEN): -0.11 EPA/tgt, 16.8 TgtSh%Malik Washington (MIA): -0.15 EPA/tgt, 14.1 TgtSh%Tyler Lockett (LV): -0.16 EPA/tgt, 10.4 TgtSh%Adonai Mitchell (NYJ): -0.22 EPA/tgt, 14.0 TgtSh%Jerry Jeudy (CLE): -0.31 EPA/tgt, 20.3 TgtSh%Christian Kirk (HOU): -0.41 EPA/tgt, 9.4 TgtSh%NacuaDiggsPiercePickensWatsonSmith-NjigbaWilliamsMcLaurinFlournoyPearsallSmithHarrisonHollinsDoubsSuttonHigginsWaddleBrownBrownAllenHigginsAdamsChaseRiceSamuelMooreRobinsonKuppShakirMimsMcConkeyEgbukaDikeWilsonShepardZaccheausAustinJeffersonWashingtonLockettMitchellJeudyKirkTarget share (%) →EPA / target →dashed = league avg · ring = regression flag
WRTgtTgtSh%EPA/tgtY/TgtaDOTSepYAC+/-Drop%RatTDReg
Puka Nacua LA16628.6+0.7010.339.42.88+1.342.4127.310▼
Stefon Diggs NE10221.2+0.699.938.53.02+0.852.9112.94▼
Alec Pierce IND8415.9+0.6611.9419.02.08+1.281.2112.46▼
George Pickens DAL13722.6+0.6510.4311.32.31+2.162.9114.99▼
Christian Watson GB5512.0+0.5911.1117.82.00+0.741.8122.66▼
Jaxon Smith-Njigba SEA16335.8+0.5611.0011.33.02+0.793.1116.410—
Jameson Williams DET10218.6+0.5510.9512.63.18+1.8411.8119.67—
Terry McLaurin WAS6013.9+0.539.7014.02.38+0.081.7105.03▼
Ryan Flournoy DAL569.2+0.518.488.33.04+0.653.6113.34—
Ricky Pearsall SF539.6+0.509.9614.12.34-0.741.968.70▼
Luther Burden III CHI6011.3+0.5010.877.74.63+0.936.7123.12—
DeVonta Smith PHI11324.4+0.488.9212.02.82-0.122.7104.14▼
Marvin Harrison Jr. ARI7311.8+0.438.3313.02.42+0.645.590.44▼
Mack Hollins NE6513.5+0.428.4613.12.67-0.260.093.72▼
Romeo Doubs GB8518.5+0.418.5212.82.27+0.363.5110.16▼
Zay Flowers BAL11829.0+0.3910.2610.23.58+0.205.9112.65—
Kendrick Bourne SF539.6+0.3910.4011.02.88+1.6811.387.90—
Courtland Sutton DEN12421.2+0.378.2012.42.28+0.126.594.77▼
Tee Higgins CIN9816.1+0.378.6313.41.83+0.382.0117.111▼
Jaylen Waddle MIA10021.7+0.359.1013.12.73+0.154.084.26▼
DK Metcalf PIT9919.0+0.338.5910.62.63+2.815.190.96—
Nico Collins HOU12021.7+0.339.3112.72.31+1.690.8103.46—
Amon-Ra St. Brown DET17231.3+0.328.158.12.95+0.345.8101.911—
Parker Washington JAX9517.4+0.318.9212.52.39+1.737.494.55—
Marquise Brown KC7413.5+0.307.9311.33.21-0.604.1101.65▼
Chris Godwin Jr. TB519.4+0.297.067.12.82+2.202.090.32—
Keenan Allen LAC12222.4+0.296.378.42.56+0.314.988.04▼
Darius Slayton NYG6312.5+0.298.5413.42.71+0.787.991.91—
Quentin Johnston LAC8415.4+0.298.7511.82.36+0.752.4111.08—
A.J. Brown PHI12126.1+0.288.2911.82.24+1.060.899.37—
CeeDee Lamb DAL11719.3+0.259.2112.02.78+0.506.891.73—
Jayden Higgins HOU6812.3+0.257.7212.32.70-0.094.4101.76▼
Davante Adams LA11419.6+0.246.9212.72.17-0.614.4110.714▼
Tre Tucker LV9218.6+0.247.5710.23.62+0.234.398.85—
Rome Odunze CHI9016.9+0.237.3413.92.98+0.972.281.86—
Chris Olave NO15627.6+0.237.4611.82.95-0.523.295.19—
Xavier Hutchinson HOU5710.3+0.237.5110.33.05+0.553.594.83—
Ja'Marr Chase CIN18530.4+0.227.638.53.17+1.312.293.38▲
Drake London ATL11221.6+0.228.2110.92.66+0.640.9100.37—
Jalen Nailor MIN5311.3+0.228.3812.42.43+1.381.968.44—
Keon Coleman BUF5912.3+0.216.8511.22.78-0.405.192.84—
Tetairoa McMillan CAR12225.4+0.218.3111.62.69+0.106.683.27—
Rashee Rice KC7814.2+0.217.324.33.60+0.626.4105.25▲
Michael Wilson ARI12620.4+0.207.9811.92.44+0.570.888.97—
Xavier Worthy KC7313.3+0.207.2912.93.46-0.461.479.31—
Michael Pittman IND11120.9+0.207.068.23.03+0.425.493.87—
Andrei Iosivas CIN589.5+0.207.5010.52.46-0.108.677.92—
Brian Thomas Jr. JAX9116.6+0.197.7714.52.66+0.2511.081.22—
Deebo Samuel Sr. WAS9922.9+0.187.345.33.54+1.096.197.55▲
Jordan Addison MIN7916.9+0.187.7213.72.87+0.637.670.13—
Van Jefferson TEN529.8+0.176.7312.02.63+0.560.083.01—
DJ Moore CHI8516.0+0.168.0211.63.27+0.613.5103.26▲
Wan'Dale Robinson NYG14027.8+0.147.248.53.37+0.342.990.64▲
Cooper Kupp SEA7015.4+0.118.477.53.02+2.074.385.02▲
Josh Downs IND8816.6+0.106.437.52.68+0.134.589.54—
Troy Franklin DEN10417.8+0.096.8212.73.01+0.303.885.86—
Jakobi Meyers JAX11022.3+0.097.599.22.73+0.341.876.93—
Mike Evans TB6211.5+0.095.9413.31.92-0.623.269.83—
Khalil Shakir BUF9519.8+0.087.573.73.80+1.883.2102.04▲
Marvin Mims Jr. DEN518.7+0.076.319.44.53+0.472.095.41▲
Ladd McConkey LAC10619.5+0.077.449.93.26+1.015.784.26▲
Emeka Egbuka TB12723.5+0.067.3912.42.58+0.687.180.16▲
Darnell Mooney ATL7213.9+0.056.1514.23.02-0.236.969.41—
Chimere Dike TEN7414.0+0.025.728.13.80-0.232.786.74▲
Jauan Jennings SF9016.4-0.037.1410.12.21+0.713.383.79—
Garrett Wilson NYJ5912.5-0.046.699.13.06-0.035.189.34▲
Rashid Shaheed SEA9216.3-0.057.4711.52.76-0.250.075.82—
Sterling Shepard TB539.8-0.057.008.63.21+0.220.098.91▲
Olamide Zaccheaus CHI6512.2-0.064.827.13.46-0.617.776.02▲
Xavier Legette CAR6413.3-0.065.679.92.60-0.573.167.43—
Calvin Austin III PIT5510.5-0.086.7611.02.82+0.673.672.73▲
Justin Jefferson MIN14130.1-0.107.4310.23.23+0.782.157.92▲
Elic Ayomanor TEN8916.8-0.115.7912.72.66-0.135.665.54—
Malik Washington MIA6514.1-0.154.885.23.65+0.901.583.93▲
Tyler Lockett LV5510.4-0.165.297.82.78-1.045.571.11—
Adonai Mitchell NYJ7414.0-0.226.1214.92.76+0.842.745.62▲
Jerry Jeudy CLE10620.3-0.315.6812.22.47-0.029.443.82—
Christian Kirk HOU529.4-0.414.607.02.54-0.253.840.51—
Data: nflverse (nflfastR) · NGS · Pro-Football-Reference via nflverse · ▲/▼ = percentile gap between production and open-field profile

How to Read the Board

  • The chart — each dot is a qualifying receiver, placed by target share (usage, left to right) and EPA per target (efficiency, bottom to top). Dashed lines are league averages among qualifiers. “Efficient in small doses” (top-left) is the breakout-watch quadrant — the role hasn’t caught up to the play yet.
  • Green and red chips — shading appears only on top- and bottom-decile values. Direction is handled: a green Drop% is a low drop rate.
  • The Reg column — ▼ means production is running ahead of the open-field profile (separation + YAC over expected); ▲ means the receiver is getting open and creating without the results to match yet. aDOT carries no shading because depth is a style, not a grade.

The Metrics, Defined

Target share is the percentage of his team’s targets a receiver commands. It’s the most predictive single stat in receiving because opportunity is sticky: coordinators keep feeding the players they trust. Shares above 25% are true alpha usage.

EPA per target is expected points added every time the ball goes his way — completions, incompletions, and interceptions on those throws all count. It bakes in the quarterback and the scheme, which is exactly why the tracking columns sit next to it: they tell you how much of the number belongs to the receiver.

Y/Tgt (yards per target) is the simpler efficiency cousin — total receiving yards over total targets. Useful as a sanity check on EPA per target, since EPA rewards situation and yardage differently.

aDOT (average depth of target) is the role descriptor. A 14-yard aDOT receiver and a 6-yard aDOT receiver can both be great; they’re just different jobs, and their prop lines behave completely differently week to week.

Sep (average separation, from Next Gen Stats tracking) is the distance in yards between the receiver and the nearest defender when the ball arrives. It’s the closest public number to “gets open.” Low-separation receivers can absolutely produce — but they’re living on contested catches and quarterback precision, which is the least stable way to produce.

YAC+/- (YAC above expectation) compares actual yards after catch to what tracking data expects given where and how he caught it. It isolates the receiver’s creation from the scheme’s manufactured space.

Drop% and Rat come from Pro-Football-Reference charting: drop rate on catchable targets, and the passer rating quarterbacks post when throwing his way — a compact summary of what targeting this receiver has actually been worth.

How Bettors Use WR Advanced Stats

  • Receiving props. Target share sets the ceiling on every receiving yards line — efficiency swings week to week, role doesn’t. Read this board next to the receiving props board: a high-share receiver whose line is priced off a slow stretch, or a ▼-flagged name the market still prices at peak, is where the value hides.
  • Touchdown props. aDOT and target share together are TD equity — deep targets and red-zone volume drive scores far more than raw yardage. The TD props board is where that read gets a price.
  • Breakout hunting. The top-left quadrant plus a green ▲ is the season-long and futures watchlist: efficiency waiting on opportunity. Role changes — an injury ahead of him, a trade — turn those profiles into league-winners.

Related boards: QB advanced stats · RB advanced stats · TE advanced stats

Where the Data Comes From

Targets, EPA, and share data are built on open-source nflverse (nflfastR) play-by-play, separation and YAC-over-expected come from NFL Next Gen Stats tracking, and drop and targeted-rating charting comes from Pro-Football-Reference via nflverse. The board refreshes every morning; receivers qualify at 50 targets.

Frequently Asked Questions

What is a good target share for a wide receiver?
20% is a solid starter, 25%+ is alpha territory, and shares approaching 30% are rare, offense-defining roles. Because coordinators feed the same players week after week, target share is the most stable receiving stat there is — which makes it the foundation for pricing receiving props.

What does EPA per target measure?
The expected points a team adds, on average, every time it throws to that receiver — including the incompletions and interceptions on those targets. It captures per-opportunity value rather than raw totals, so a receiver can lead the league in yards and still be mid-pack here.

What counts as good separation?
Around 3.0 yards at the catch point is a healthy mark for a wide receiver; below roughly 2.3 means he’s winning contested, which is the hardest style to sustain. Context matters — deep routes naturally produce less separation than option routes underneath.

Why does a productive receiver have a red regression flag?
His EPA-per-target percentile is at least 25 points above his separation and YAC-over-expected percentiles — the production is real, but it’s been built on tight-window catches and quarterback accuracy rather than getting open. That style of production is the least stable, which is what the flag marks.

How many targets does a receiver need to appear?
50. Below that, per-target rates swing too hard on a handful of plays to rank honestly.


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