With the better part of the NFL offseason behind us, I figured I’d take a look at NFL season win totals and see where there may be value. I’ve created a model that runs through every NFL game and predicts the win probabilities of each team. Here are the factors the model takes into account when assigning these probabilities:
- Last season success
- Free agent acquisitions/departures
- Acquisitions/departures via trade
- Total team draft capital (post draft day trades)
Using a modified version of each team’s final 2018-2019 SRS metric, I added or subtracted from each team’s final number based on value added over the offseason. For free agency and trades, I used the 2018-2019 AV of each player as a baseline. For the draft, I used the total draft capital of each team after all draft day trades were completed. After adding or subtracting based on these parameters, I arrived at a new modified SRS score for each team.
Using the new SRS scores, I simulated every regular season game to get a projected win total for each team. Here are the results:
|
Team |
Model Total | O/U | Difference |
| New England Patriots | 11.002 | 11 |
+0.002 |
| Los Angeles Rams | 13.105 | 10.5 | +2.605 |
| New Orleans Saints | 12.740 | 10.5 | +2.240 |
| Kansas City Chiefs | 12.402 | 10.5 | +1.902 |
| Philadelphia Eagles | 11.749 | 9.5 | +2.249 |
| Chicago Bears | 11.690 | 9.5 | +2.190 |
| Los Angeles Chargers | 11.267 | 9.5 | +1.767 |
| Cleveland Browns | 10.580 | 9.5 | +1.080 |
| Indianapolis Colts | 10.192 | 9.5 | +0.692 |
| Pittsburgh Steelers | 10.232 | 9 | +1.232 |
| Dallas Cowboys | 9.397 | 9 | +0.397 |
| Green Bay Packers | 6.157 | 9 | -2.843 |
| Baltimore Ravens | 10.131 | 8.5 | +1.631 |
| Houston Texans | 9.939 | 8.5 | +1.439 |
| Seattle Seahawks | 9.470 | 8.5 | +0.970 |
| Minnesota Vikings | 6.764 | 8.5 | -1.736 |
| Atlanta Falcons | 6.344 | 8.5 | -2.156 |
| Tennessee Titans | 7.632 | 8 | -0.368 |
| Jacksonville Jaguars | 3.191 | 8 | -4.809 |
| San Francisco 49ers | 6.684 | 7.5 | -0.816 |
| New York Jets | 4.663 | 7.5 | -2.837 |
| Carolina Panthers | 8.647 | 7 | +1.647 |
| Buffalo Bills | 7.822 | 6.5 | +1.322 |
| Denver Broncos | 5.133 | 6.5 | -1.367 |
| Washington Redskins | 4.346 | 6.5 | -2.154 |
| Tampa Bay Buccaneers | 4.186 | 6.5 | -2.314 |
| Detroit Lions | 7.529 | 6 | +1.529 |
| Oakland Raiders | 6.059 | 6 | +0.059 |
| New York Giants | 8.658 | 5.5 | +3.158 |
| Arizona Cardinals | 1.816 | 5 | -3.184 |
| Miami Dolphins | 0.006 | 4.5 | -4.494 |
| Cincinnati Bengals | 6.463 | 4 | +2.463 |
Given these projections, there are a few totals that seem to have value. Here are the picks that have a model-total difference of more than one standard deviation:
LAR o10.5
NO o10.5
PHI o9.5
GB u9
JAX u8
NYJ u7.5
TB u6.5
NYG o5.5
ARI u5
MIA u4.5
CIN o4
While I tried to include as many factors as I could, there are a lot of non-quantifiable factors that will have a big impact on how the seasons unfold. Things like coaching changes, player progression/regression, and draft class impact are all things that cannot have a number put on them, so it will be interesting to see how the picks turn out.
