Every NFL game this week with its spread, moneyline, game total and, most usefully for lineup building, the implied team total behind each side. The board is built from the consensus schedule feed and refreshed weekly, so it does not go stale between seasons.

Why implied team totals matter more than the spread. A game total tells you how many points the market expects on the field. The implied team total splits that between the two offenses, and that split is what actually drives fantasy scoring. A 27-point implied total on a road underdog is a better stacking spot than a 44-point game total on its own would suggest.

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How Our Projections Are Actually Doing

The board above is what we expect. Below is what happened. Every completed game carries its final score beside the projection, the actual DraftKings and FanDuel points every projected player scored, and a grade for how well the model ranked them.

Grades use the correlation between projected and actual points rather than raw error, because ranking players correctly is what matters for a lineup, and a game where everyone outscored expectations should not be marked down for it. A single game is a small sample, so the season figure is the number worth reading.

How the projections have actually done. Across 79 completed games and 1713 player scores this season, mean absolute error is 4.33 DraftKings points with a bias of -0.42, correlation between projected and actual is +0.709, and that is +36.4 percent better than simply projecting every player at the slate average. Season grade B. A positive bias means the projections run high. A single game is far too small a sample to judge, which is why the season figure leads.

Completed Games

6grade A
6grade B
1grade C
1grade D
1grade F
15games graded
Show
ABills 37, Rams 34MAE 4.65 · corr +0.917 · 24 players
Projected 26.3 to 29.8 for a total of 56.2, against a market total of 55.5. Actual total 71.
4.65Mean abs error
-1.99Bias
+0.917Correlation
+54.1 percentvs baseline
24Players graded
PlayerProj DKActual DKDiffActual FDOwn
Puka NacuaLA WR23.240.7+17.529.233.0%
Josh AllenBUF QB24.634.5+9.931.59.0%
Matthew StaffordLA QB21.830.3+8.627.310.1%
James Cook IIIBUF RB16.126.8+10.722.33.9%
Davante AdamsLA WR15.322.1+6.819.66.2%
Kyren WilliamsLA RB19.119.6+0.516.632.6%
Blake CorumLA RB7.316.2+8.914.70.1%
Tyler HigbeeLA TE7.413.3+5.910.80.4%
Ty JohnsonBUF RB5.511.2+5.79.20.0%
Khalil ShakirBUF WR12.111.0-1.19.59.8%
ALions 45, Cardinals 21MAE 5.08 · corr +0.81 · 22 players
Projected 30.3 to 24.7 for a total of 55.1, against a market total of 55.5. Actual total 66.
5.08Mean abs error
-0.79Bias
+0.81Correlation
+46.3 percentvs baseline
22Players graded
PlayerProj DKActual DKDiffActual FDOwn
Jahmyr GibbsDET RB27.940.7+12.835.229.0%
Jared GoffDET QB21.728.9+7.328.98.2%
Jacoby BrissettARI QB20.126.3+6.225.816.3%
Trey McBrideARI TE20.921.6+0.717.131.3%
Sam LaPortaDET TE13.319.8+6.517.314.8%
Jameson WilliamsDET WR12.218.7+6.517.71.7%
Teagan QuitorianoARI TE1.215.5+14.214.50.0%
Amon-Ra St. BrownDET WR21.212.9-8.39.913.5%
Kendrick BourneARI WR8.412.0+3.69.56.0%
Elijah HigginsARI TE3.58.7+5.27.20.1%
CBuccaneers 24, Cowboys 16MAE 4.86 · corr +0.607 · 21 players
Projected 19.7 to 29.8 for a total of 49.5, against a market total of 49.5. Actual total 40.
4.86Mean abs error
-0.78Bias
+0.607Correlation
+34.4 percentvs baseline
21Players graded
PlayerProj DKActual DKDiffActual FDOwn
Bucky IrvingTB RB12.434.5+22.130.51.2%
George PickensDAL WR15.731.0+15.323.511.2%
Dak PrescottDAL QB22.217.6-4.614.67.8%
Emeka EgbukaTB WR9.517.2+7.714.22.6%
Javonte WilliamsDAL RB18.214.2-4.013.29.5%
Jalon DanielsTB QB17.513.9-3.613.912.4%
Ryan FlournoyDAL WR8.412.0+3.610.57.6%
Tez JohnsonTB WR4.17.4+3.36.91.4%
Chris Godwin Jr.TB WR8.87.0-1.85.52.4%
Kenny GainwellTB RB6.35.8-0.54.30.1%
A49ers 32, Seahawks 29MAE 3.16 · corr +0.822 · 21 players
Projected 22.2 to 25.1 for a total of 47.3, against a market total of 46.5. Actual total 61.
3.16Mean abs error
+0.64Bias
+0.822Correlation
+52.7 percentvs baseline
21Players graded
PlayerProj DKActual DKDiffActual FDOwn
Mike EvansSF WR12.629.3+16.722.80.1%
Jaxon Smith-NjigbaSEA WR21.925.8+3.920.35.4%
Christian McCaffreySF RB19.317.3-2.015.83.4%
Brock PurdySF QB18.217.2-1.017.20.4%
Emanuel WilsonSEA RB15.114.2-0.812.211.5%
Sam DarnoldSEA QB17.310.3-7.010.31.2%
Brandin CooksSF WR1.97.7+5.87.20.0%
George KittleSF TE12.77.4-5.34.99.6%
George HolaniSEA RB7.46.1-1.33.10.1%
AJ BarnerSEA TE6.95.0-1.93.53.0%
BBears 7, Packers 31MAE 5.1 · corr +0.685 · 21 players
Projected 24.0 to 23.1 for a total of 47.1, against a market total of 46.5. Actual total 38.
5.1Mean abs error
-0.79Bias
+0.685Correlation
+32.9 percentvs baseline
21Players graded
PlayerProj DKActual DKDiffActual FDOwn
Christian WatsonGB WR13.835.3+21.429.31.1%
Jordan LoveGB QB17.328.3+11.025.31.0%
Matthew GoldenGB WR12.923.3+10.417.35.6%
D'Andre SwiftCHI RB19.417.3-2.115.32.8%
MarShawn LloydGB RB10.316.7+6.416.20.1%
Tucker KraftGB TE11.711.6-0.19.18.5%
Roschon JohnsonCHI RB4.39.0+4.76.50.0%
Luther Burden IIICHI WR11.88.9-2.96.912.3%
Rome OdunzeCHI WR9.66.0-3.63.50.7%
Bo MeltonGB WR1.55.0+3.53.50.0%
BRaiders 17, Patriots 45MAE 5.82 · corr +0.674 · 23 players
Projected 21.1 to 25.0 for a total of 46.1, against a market total of 45.5. Actual total 62.
5.82Mean abs error
-2.67Bias
+0.674Correlation
+23.4 percentvs baseline
23Players graded
PlayerProj DKActual DKDiffActual FDOwn
Drake MayeNE QB20.342.5+22.139.52.7%
Brock BowersLV TE18.227.0+8.819.013.2%
DeMario DouglasNE WR7.122.5+15.420.50.8%
Kyle WilliamsNE WR4.318.1+13.816.60.0%
Rhamondre StevensonNE RB12.817.5+4.716.09.9%
Kirk CousinsLV QB15.513.7-1.813.70.3%
Hunter HenryNE TE10.213.4+3.211.91.5%
Dylan LaubeLV RB1.011.5+10.510.00.0%
Efton Chism IIINE WR6.010.9+4.98.41.8%
Eli RaridonNE TE3.710.7+7.08.20.0%
BBengals 31, Dolphins 24MAE 3.98 · corr +0.724 · 21 players
Projected 26.8 to 18.5 for a total of 45.3, against a market total of 44.5. Actual total 55.
3.98Mean abs error
-0.76Bias
+0.724Correlation
+34.9 percentvs baseline
21Players graded
PlayerProj DKActual DKDiffActual FDOwn
Joe BurrowCIN QB20.424.6+4.224.60.5%
Malik WillisMIA QB15.721.9+6.220.90.8%
Ja'Marr ChaseCIN WR20.019.7-0.316.70.0%
Samaje PerineCIN RB5.515.8+10.314.80.0%
Ollie Gordon IIMIA RB10.714.8+4.114.80.2%
Malik WashingtonMIA WR11.912.1+0.29.14.6%
Kevin Coleman Jr.MIA WR4.812.0+7.210.50.0%
Tanner HudsonCIN TE2.210.4+8.28.90.0%
Greg DulcichMIA TE7.09.7+2.77.70.2%
Chase BrownCIN RB18.88.0-10.85.534.9%
ARavens 30, Falcons 23MAE 3.67 · corr +0.835 · 20 players
Projected 20.7 to 24.0 for a total of 44.7, against a market total of 44.5. Actual total 53.
3.67Mean abs error
-1.51Bias
+0.835Correlation
+45.7 percentvs baseline
20Players graded
PlayerProj DKActual DKDiffActual FDOwn
Tyler HuntleyBAL QB15.624.0+8.424.00.8%
Derrick HenryBAL RB16.024.0+8.020.51.4%
Drake LondonATL WR18.721.8+3.115.319.5%
Bijan RobinsonATL RB23.215.8-7.513.817.0%
Kyle Pitts Sr.ATL TE6.815.2+8.312.70.0%
Zay FlowersBAL WR15.214.6-0.610.61.3%
Michael Penix Jr.ATL QB15.214.4-0.814.41.0%
Rashod BatemanBAL WR5.311.2+5.98.70.2%
Justice HillBAL RB5.19.8+4.78.80.0%
Devontez WalkerBAL WR3.18.9+5.87.90.0%
BColts 22, Steelers 34MAE 5.22 · corr +0.7 · 20 players
Projected 20.2 to 22.6 for a total of 42.8, against a market total of 41.5. Actual total 56.
5.22Mean abs error
-1.08Bias
+0.7Correlation
+34.1 percentvs baseline
20Players graded
PlayerProj DKActual DKDiffActual FDOwn
Jaylen WarrenPIT RB18.339.8+21.533.80.3%
Aaron RodgersPIT QB15.822.0+6.222.01.2%
Pat FreiermuthPIT TE8.721.5+12.819.00.6%
Tyler WarrenIND TE12.121.4+9.317.910.3%
Germie BernardPIT WR5.914.4+8.511.40.1%
Jonathan TaylorIND RB19.311.2-8.19.713.5%
Daniel JonesIND QB13.911.1-2.911.12.6%
Keenan AllenIND WR8.39.5+1.27.00.7%
Josh DownsIND WR13.07.7-5.36.25.8%
Laquon TreadwellIND WR4.65.4+0.84.40.0%
AEagles 17, Jaguars 19MAE 3.38 · corr +0.819 · 24 players
Projected 17.0 to 25.7 for a total of 42.7, against a market total of 41.5. Actual total 36.
3.38Mean abs error
-0.75Bias
+0.819Correlation
+48.1 percentvs baseline
24Players graded
PlayerProj DKActual DKDiffActual FDOwn
Parker WashingtonJAX WR14.933.4+18.527.44.3%
Trevor LawrenceJAX QB18.625.7+7.122.73.4%
Darius CooperPHI WR6.115.1+9.014.15.8%
Brenton StrangeJAX TE8.613.8+5.210.34.8%
Jalen HurtsPHI QB16.013.0-3.013.00.2%
Bhayshul TutenJAX RB14.411.6-2.810.63.6%
Dontayvion WicksPHI WR9.811.3+1.58.80.7%
Dallas GoedertPHI TE10.39.8-0.56.80.0%
Makai LemonPHI WR8.39.3+0.96.83.3%
Will ShipleyPHI RB9.78.3-1.47.80.0%
FBroncos 23, Chargers 17MAE 4.48 · corr +0.332 · 21 players
Projected 23.3 to 19.4 for a total of 42.7, against a market total of 42.5. Actual total 40.
4.48Mean abs error
+1.75Bias
+0.332Correlation
-23.2 percentvs baseline
21Players graded
PlayerProj DKActual DKDiffActual FDOwn
J.K. DobbinsDEN RB9.515.4+5.914.40.4%
Kimani VidalLAC RB4.012.6+8.612.10.0%
Justin HerbertLAC QB15.712.2-3.511.21.3%
Courtland SuttonDEN WR10.09.8-0.28.81.6%
Evan EngramDEN TE5.69.5+3.97.50.4%
Bo NixDEN QB17.58.9-8.67.91.9%
Hayden RucciLAC TE0.67.7+7.17.20.0%
Keaton MitchellLAC RB8.65.9-2.74.40.4%
Charlie KolarLAC TE3.35.7+2.43.20.0%
Omarion HamptonLAC RB9.34.9-4.44.40.0%
AGiants 27, Commanders 27MAE 5.08 · corr +0.847 · 23 players
Projected 19.2 to 23.3 for a total of 42.5, against a market total of 41.5. Actual total 54.
5.08Mean abs error
-2.58Bias
+0.847Correlation
+42.2 percentvs baseline
23Players graded
PlayerProj DKActual DKDiffActual FDOwn
Jayden DanielsWAS QB18.335.3+16.932.33.8%
Isaiah LikelyNYG TE12.032.4+20.426.95.5%
Malik NabersNYG WR13.232.1+18.923.61.4%
Jameis WinstonNYG QB13.229.7+16.525.70.3%
Jacory Croskey-MerrittWAS RB10.114.2+4.114.26.3%
Terry McLaurinWAS WR9.612.2+2.610.20.0%
Chig OkonkwoWAS TE7.310.0+2.78.00.7%
Cam SkatteboNYG RB13.88.1-5.76.13.1%
Antonio WilliamsWAS WR9.16.1-3.04.69.0%
Theo JohnsonNYG TE2.55.5+3.04.50.0%
BVikings 23, Saints 13MAE 4.03 · corr +0.669 · 22 players
Projected 22.0 to 20.4 for a total of 42.4, against a market total of 41.5. Actual total 36.
4.03Mean abs error
+1.81Bias
+0.669Correlation
+15.3 percentvs baseline
22Players graded
PlayerProj DKActual DKDiffActual FDOwn
Aaron Jones Sr.MIN RB17.622.7+5.117.220.7%
Justin JeffersonMIN WR18.918.8-0.115.80.0%
Kyler MurrayMIN QB17.318.3+1.018.32.4%
Kendre MillerNO RB5.69.0+3.49.00.0%
Chris OlaveNO WR17.88.6-9.26.61.2%
Gavin BartholomewMIN TE1.58.3+6.85.80.0%
Devaughn VeleNO WR10.16.6-3.54.60.1%
Juwan JohnsonNO TE10.15.6-4.53.60.7%
Tai FeltonMIN WR3.74.7+1.03.70.2%
Jeshaun JonesMIN WR0.94.2+3.33.70.0%
BBrowns 12, Jets 17MAE 3.75 · corr +0.733 · 22 players
Projected 18.9 to 20.6 for a total of 39.5, against a market total of 38.5. Actual total 29.
3.75Mean abs error
+0.69Bias
+0.733Correlation
+33.9 percentvs baseline
22Players graded
PlayerProj DKActual DKDiffActual FDOwn
Garrett WilsonNYJ WR16.426.4+10.019.912.1%
Braelon AllenNYJ RB16.121.6+5.518.120.2%
Denzel BostonCLE WR10.513.6+3.112.11.1%
Deshaun WatsonCLE QB16.213.2-3.012.23.3%
Geno SmithNYJ QB14.911.0-3.910.01.2%
Isaiah BondCLE WR0.810.4+9.68.90.1%
Quinshon JudkinsCLE RB13.98.0-5.96.56.9%
Mason TaylorNYJ TE4.85.4+0.63.90.2%
Jerry JeudyCLE WR3.84.9+1.13.40.0%
Tim PatrickNYJ WR0.84.6+3.83.60.0%
DTexans 26, Titans 3MAE 4.12 · corr +0.545 · 22 players
Projected 23.1 to 15.9 for a total of 38.9, against a market total of 37.5. Actual total 29.
4.12Mean abs error
+0.69Bias
+0.545Correlation
+7.3 percentvs baseline
22Players graded
PlayerProj DKActual DKDiffActual FDOwn
C.J. StroudHOU QB17.420.9+3.520.90.4%
Jaylin NoelHOU WR5.515.2+9.712.70.2%
Woody MarksHOU RB8.812.5+3.710.50.0%
Wan'Dale RobinsonTEN WR9.011.3+2.38.30.5%
Tyjae SpearsTEN RB6.310.8+4.55.30.0%
Nico CollinsHOU WR17.510.6-6.98.17.3%
Xavier HutchinsonHOU WR4.310.5+6.28.50.0%
Kayshon BoutteHOU WR6.56.8+0.35.30.0%
Dalton SchultzHOU TE9.76.0-3.74.50.2%
Cam WardTEN QB12.36.0-6.36.00.1%

How to read the board

Games are grouped by day in kickoff order. The favorite on each card is picked out in gold, and the chip in the top right tags the game shape: a grind at 42 points or under, a shootout at 49 or over, average in between. Those are the same bands the FTA showdown research uses, so the language carries across the site.

Win probability is de-vigged from the two moneylines, so the pair adds to 100 rather than the 104 or so the raw prices imply. The second tab ranks all 32 implied team totals on the slate, which is the fastest way to find the offences the market likes before you start building.

What this pairs with

Once you have the spots, the NFL Strength of Schedule tool grades the matchups, the NFL Bacon Station carries defense-allowed and red zone usage, and the BaconLab optimizer builds the lineups. FTA+ members can export the whole board to CSV and drop it straight into their own model.