WEEK 7 · Sun, Oct 25, 3:25 PM CDT

Green Bay Packers @ Detroit Lions

12 qualified model plays · 7 modeled lines did not qualify · 6-6-0
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MODEL OVERVIEW

What the board is seeing

Qualified plays 12 Published sides that cleared the current model thresholds.
Avg model win 70.9% Average estimated win probability across this game's qualified plays.
Avg no-vig edge +21.0% Model probability minus the market's no-vig implied probability.
Avg model-implied EV +33.8% Average modeled return using the published side price.

Projection gap is the raw difference between PDR's projection and the sportsbook line. No-vig edge is the probability advantage after removing sportsbook hold. They answer different questions.

How the model works →
QUALIFIED PLAYS

Game prop board

Ranked by the frozen published model board.

#1 MODEL PLAY

Jordan Love

Passing yards
WIN
UNDER 277.5
fanduel -114
Projection 194.4
Proj. gap -83.1
Model win 86.8%
No-vig market 50.0%
No-vig edge +36.8%
Model-implied EV +63.0%
WHY THIS PLAY
Projection 194.4 is 83.1 below the 277.5 line.
Model win probability 86.8% vs 50.0% no-vig market probability creates a +36.8% edge.
Qualified with 516 residual samples, 86.8% model win, +36.8% no-vig edge, and +63.0% model-implied EV; publication floors are 500 samples, 57.5% win, +5.0% edge, and +5.0% EV.
Historical residual sample: 516
Final: 274 passing yards
#2 MODEL PLAY

Christian Watson

Receiving yards
WIN
UNDER 75.5
fanduel -114
Projection 54.6
Proj. gap -20.9
Model win 83.9%
No-vig market 50.0%
No-vig edge +33.9%
Model-implied EV +57.5%
WHY THIS PLAY
Projection 54.6 is 20.9 below the 75.5 line.
Model win probability 83.9% vs 50.0% no-vig market probability creates a +33.9% edge.
Qualified with 2154 residual samples, 83.9% model win, +33.9% no-vig edge, and +57.5% model-implied EV; publication floors are 500 samples, 57.5% win, +5.0% edge, and +5.0% EV.
Historical residual sample: 2154
Final: 57 receiving yards
#3 MODEL PLAY

Jahmyr Gibbs

Rushing yards
LOSS
UNDER 93.5
fanduel -114
Projection 75.6
Proj. gap -17.9
Model win 78.9%
No-vig market 50.0%
No-vig edge +28.9%
Model-implied EV +48.1%
WHY THIS PLAY
Projection 75.6 is 17.9 below the 93.5 line.
Model win probability 78.9% vs 50.0% no-vig market probability creates a +28.9% edge.
Qualified with 796 residual samples, 78.9% model win, +28.9% no-vig edge, and +48.1% model-implied EV; publication floors are 500 samples, 57.5% win, +5.0% edge, and +5.0% EV.
Historical residual sample: 796
Final: 116 rushing yards
#4 MODEL PLAY

Christian Watson

Receptions
LOSS
UNDER 4.5
fanduel -122
Projection 3.6
Proj. gap -0.9
Model win 77.5%
No-vig market 51.4%
No-vig edge +26.1%
Model-implied EV +41.0%
WHY THIS PLAY
Projection 3.6 is 0.9 below the 4.5 line.
Model win probability 77.5% vs 51.4% no-vig market probability creates a +26.1% edge.
Qualified with 2154 residual samples, 77.5% model win, +26.1% no-vig edge, and +41.0% model-implied EV; publication floors are 500 samples, 57.5% win, +5.0% edge, and +5.0% EV.
Historical residual sample: 2154
Final: 5 receptions
#5 MODEL PLAY

Jahmyr Gibbs

Receiving yards
WIN
UNDER 38.5
fanduel -114
Projection 36.2
Proj. gap -2.3
Model win 69.1%
No-vig market 50.0%
No-vig edge +19.1%
Model-implied EV +29.7%
WHY THIS PLAY
Projection 36.2 is 2.3 below the 38.5 line.
Model win probability 69.1% vs 50.0% no-vig market probability creates a +19.1% edge.
Qualified with 2154 residual samples, 69.1% model win, +19.1% no-vig edge, and +29.7% model-implied EV; publication floors are 500 samples, 57.5% win, +5.0% edge, and +5.0% EV.
Historical residual sample: 2154
Final: 27 receiving yards
#6 MODEL PLAY

Jameson Williams

Receptions
WIN
OVER 3.5
fanduel -138
Projection 5.2
Proj. gap +1.7
Model win 66.4%
No-vig market 54.2%
No-vig edge +12.2%
Model-implied EV +14.6%
WHY THIS PLAY
Projection 5.2 is 1.7 above the 3.5 line.
Model win probability 66.4% vs 54.2% no-vig market probability creates a +12.2% edge.
Qualified with 2154 residual samples, 66.4% model win, +12.2% no-vig edge, and +14.6% model-implied EV; publication floors are 500 samples, 57.5% win, +5.0% edge, and +5.0% EV.
Historical residual sample: 2154
Final: 5 receptions
#7 MODEL PLAY

Sam LaPorta

Receptions
WIN
UNDER 4.5
fanduel +112
Projection 4.3
Proj. gap -0.2
Model win 66.3%
No-vig market 44.1%
No-vig edge +22.2%
Model-implied EV +40.7%
WHY THIS PLAY
Projection 4.3 is 0.2 below the 4.5 line.
Model win probability 66.3% vs 44.1% no-vig market probability creates a +22.2% edge.
Qualified with 2154 residual samples, 66.3% model win, +22.2% no-vig edge, and +40.7% model-implied EV; publication floors are 500 samples, 57.5% win, +5.0% edge, and +5.0% EV.
Historical residual sample: 2154
Final: 1 reception
#8 MODEL PLAY

Jameson Williams

Receiving yards
WIN
OVER 54.5
fanduel -114
Projection 76.8
Proj. gap +22.3
Model win 66.3%
No-vig market 50.0%
No-vig edge +16.3%
Model-implied EV +24.4%
WHY THIS PLAY
Projection 76.8 is 22.3 above the 54.5 line.
Model win probability 66.3% vs 50.0% no-vig market probability creates a +16.3% edge.
Qualified with 2154 residual samples, 66.3% model win, +16.3% no-vig edge, and +24.4% model-implied EV; publication floors are 500 samples, 57.5% win, +5.0% edge, and +5.0% EV.
Historical residual sample: 2154
Final: 91 receiving yards
#9 MODEL PLAY

Isaac TeSlaa

Receptions
LOSS
OVER 1.5
fanduel -144
Projection 3.1
Proj. gap +1.6
Model win 65.5%
No-vig market 55.1%
No-vig edge +10.4%
Model-implied EV +11.0%
WHY THIS PLAY
Projection 3.1 is 1.6 above the 1.5 line.
Model win probability 65.5% vs 55.1% no-vig market probability creates a +10.4% edge.
Qualified with 2154 residual samples, 65.5% model win, +10.4% no-vig edge, and +11.0% model-implied EV; publication floors are 500 samples, 57.5% win, +5.0% edge, and +5.0% EV.
Historical residual sample: 2154
Final: 1 reception
#10 MODEL PLAY

Jahmyr Gibbs

Receptions
LOSS
UNDER 4.5
fanduel +128
Projection 4.4
Proj. gap -0.1
Model win 64.5%
No-vig market 41.0%
No-vig edge +23.6%
Model-implied EV +47.1%
WHY THIS PLAY
Projection 4.4 is 0.1 below the 4.5 line.
Model win probability 64.5% vs 41.0% no-vig market probability creates a +23.6% edge.
Qualified with 2154 residual samples, 64.5% model win, +23.6% no-vig edge, and +47.1% model-implied EV; publication floors are 500 samples, 57.5% win, +5.0% edge, and +5.0% EV.
Historical residual sample: 2154
Final: 5 receptions
#11 MODEL PLAY

Amon-Ra St. Brown

Receptions
LOSS
UNDER 7.5
fanduel -132
Projection 7.4
Proj. gap -0.1
Model win 64.5%
No-vig market 53.2%
No-vig edge +11.3%
Model-implied EV +13.3%
WHY THIS PLAY
Projection 7.4 is 0.1 below the 7.5 line.
Model win probability 64.5% vs 53.2% no-vig market probability creates a +11.3% edge.
Qualified with 2154 residual samples, 64.5% model win, +11.3% no-vig edge, and +13.3% model-implied EV; publication floors are 500 samples, 57.5% win, +5.0% edge, and +5.0% EV.
Historical residual sample: 2154
Final: 9 receptions
#12 MODEL PLAY

Isaac TeSlaa

Receiving yards
LOSS
OVER 24.5
fanduel -114
Projection 43.3
Proj. gap +18.8
Model win 61.1%
No-vig market 50.0%
No-vig edge +11.1%
Model-implied EV +14.8%
WHY THIS PLAY
Projection 43.3 is 18.8 above the 24.5 line.
Model win probability 61.1% vs 50.0% no-vig market probability creates a +11.1% edge.
Qualified with 2154 residual samples, 61.1% model win, +11.1% no-vig edge, and +14.8% model-implied EV; publication floors are 500 samples, 57.5% win, +5.0% edge, and +5.0% EV.
Historical residual sample: 2154
Final: 10 receiving yards
MODELED - DID NOT QUALIFY

Other lines PDR reviewed

Context only. These are not published recommendations and are not graded.

MODELED - DID NOT QUALIFY

Amon-Ra St. Brown

Receiving yards
Did not qualify
Model side: OVER 78.5
fanduel -114
Projection92.0
Proj. gap+13.5
Model win52.7%
No-vig market50.0%
No-vig edge+2.7%
Model-implied EV-1.0%
Why it did not qualify: Model win probability did not clear the publication floor.
Historical residual sample: 2154
MODELED - DID NOT QUALIFY

Jared Goff

Passing TDs
Did not qualify
Model side: OVER 1.5
fanduel -230
Projection1.9
Proj. gap+0.4
Model win59.9%
No-vig market65.1%
No-vig edge-5.2%
Model-implied EV-14.1%
Why it did not qualify: No-vig market edge did not clear the publication floor.
Historical residual sample: 516
MODELED - DID NOT QUALIFY

Jared Goff

Passing yards
Did not qualify
Model side: UNDER 278.5
fanduel -114
Projection270.0
Proj. gap-8.5
Model win55.8%
No-vig market50.0%
No-vig edge+5.8%
Model-implied EV+4.8%
Why it did not qualify: Model win probability did not clear the publication floor.
Historical residual sample: 516
MODELED - DID NOT QUALIFY

Jordan Love

Passing TDs
Did not qualify
Model side: OVER 1.5
fanduel -178
Projection1.5
Proj. gap+0.0
Model win50.2%
No-vig market59.8%
No-vig edge-9.6%
Model-implied EV-21.6%
Why it did not qualify: Model win probability did not clear the publication floor.
Historical residual sample: 516
MODELED - DID NOT QUALIFY

Sam LaPorta

Receiving yards
Did not qualify
Model side: OVER 49.5
fanduel -114
Projection51.6
Proj. gap+2.1
Model win36.3%
No-vig market50.0%
No-vig edge-13.7%
Model-implied EV-31.9%
Why it did not qualify: Model win probability did not clear the publication floor.
Historical residual sample: 2154
MODELED - DID NOT QUALIFY

Tucker Kraft

Receptions
Did not qualify
Model side: OVER 3.5
fanduel -205
Projection4.5
Proj. gap+1.0
Model win52.1%
No-vig market62.9%
No-vig edge-10.8%
Model-implied EV-22.5%
Why it did not qualify: Model win probability did not clear the publication floor.
Historical residual sample: 2154
MODELED - DID NOT QUALIFY

Tucker Kraft

Receiving yards
Did not qualify
Model side: OVER 46.5
fanduel -114
Projection58.9
Proj. gap+12.4
Model win51.3%
No-vig market50.0%
No-vig edge+1.3%
Model-implied EV-3.8%
Why it did not qualify: Model win probability did not clear the publication floor.
Historical residual sample: 2154
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