The NFFC Playoff Hold 'Em is a different kind of fantasy contest. It's not just about who scores the most points this week. It's about committing to the right players early and letting the scoring multiplier do the work as the playoffs unfold.
To help cut through the noise, I ran thousands of playoff simulations and asked a very specific question:
Which players most often turn out to be optimal Week 1 roster choices once the entire postseason plays out?
Below are the results of those optimization runs. I'll start by looking at the players who most often showed up in optimal Week 1 rosters, grouped by position. After that, I'll walk through each playoff team and highlight the best Round 1 options on a team-by-team basis.
Teams are ordered by power rating (based on PowerRankings.com), since advancing deeper into the playoffs is the single biggest driver of value in this format.
If you're mostly here for actionable takeaways, the position and team sections will get you what you need. If you want to dig into how the simulation works and what went into it, I've included a full explanation at the end.
Positional Breakdown
Quarterback
| Player | Team | Position | Opto |
|---|---|---|---|
| Drake Maye | NE | QB | 37.1% |
| Trevor Lawrence | Jac | QB | 36.7% |
| Bo Nix | Den | QB | 29.0% |
| Josh Allen | Buf | QB | 24.2% |
| C.J. Stroud | Hou | QB | 17.0% |
| Justin Herbert | LAC | QB | 13.9% |
| Matthew Stafford | LAR | QB | 10.6% |
| Jalen Hurts | Phi | QB | 9.6% |
| Brock Purdy | SF | QB | 8.8% |
| Jordan Love | GB | QB | 6.0% |
| Sam Darnold | Sea | QB | 3.9% |
| Caleb Williams | Chi | QB | 2.9% |
| Aaron Rodgers | Pit | QB | 0.3% |
| Bryce Young | Car | QB | 0.1% |
The first big takeaway for me was a bit surprising: the quarterbacks on some of the teams with the best odds of making a deep run did not sim out as well as I expected. In particular, Matthew Stafford, Sam Darnold, and Jalen Hurts graded out as worse bets to be strong Week 1 plays than I would have anticipated. On the other hand, it does make sense that quarterbacks who really spread the ball around to a number of different receivers (the top four in the optimals) might be better plays than the quarterbacks with narrow target trees and elite WR1s, given that the gap between quarterback and wide receiver fantasy points is larger.
Running Back
| Player | Team | Position | Opto |
|---|---|---|---|
| Christian McCaffrey | SF | RB | 70.88% |
| James Cook | Buf | RB | 55.06% |
| RJ Harvey | Den | RB | 38.88% |
| Josh Jacobs | GB | RB | 37.10% |
| D'Andre Swift | Chi | RB | 35.84% |
| Travis Etienne Jr. | Jac | RB | 26.20% |
| Saquon Barkley | Phi | RB | 24.98% |
| Omarion Hampton | LAC | RB | 21.26% |
| Jaylen Warren | Pit | RB | 14.84% |
| Rhamondre Stevenson | NE | RB | 13.04% |
| TreVeyon Henderson | NE | RB | 12.56% |
| Kenneth Gainwell | Pit | RB | 8.42% |
| Woody Marks | Hou | RB | 5.50% |
| Kyren Williams | LAR | RB | 4.08% |
| Ken Walker III | Sea | RB | 2.90% |
| Zach Charbonnet | Sea | RB | 2.64% |
| Rico Dowdle | Car | RB | 1.96% |
| Kyle Monangai | Chi | RB | 1.90% |
Unsurprisingly, true workhorse RB1s sim out much better than backs stuck in committees. I also suspect that the lack of concentrated targets in the passing game plays a role here. For example, Buffalo doesn't have a pass catcher who is likely to string together multiple big games in a row, which only adds to the appeal of James Cook.
Wide Receiver
| Player | Team | Position | Opto |
|---|---|---|---|
| Puka Nacua | LAR | WR | 83.72% |
| Jaxon Smith-Njigba | Sea | WR | 72.98% |
| Nico Collins | Hou | WR | 59.96% |
| A.J. Brown | Phi | WR | 40.30% |
| Christian Watson | GB | WR | 39.16% |
| Courtland Sutton | Den | WR | 26.40% |
| Quentin Johnston | LAC | WR | 9.94% |
| DK Metcalf | Pit | WR | 8.56% |
| Tetairoa McMillan | Car | WR | 7.72% |
| Luther Burden III | Chi | WR | 7.58% |
| Stefon Diggs | NE | WR | 6.24% |
| DeVonta Smith | Phi | WR | 4.74% |
| Jauan Jennings | SF | WR | 3.92% |
| Ladd McConkey | LAC | WR | 3.64% |
| Romeo Doubs | GB | WR | 3.40% |
| Parker Washington | Jac | WR | 3.32% |
| DJ Moore | Chi | WR | 2.76% |
| Troy Franklin | Den | WR | 2.16% |
| Jakobi Meyers | Jac | WR | 2.16% |
| Jalen Coker | Car | WR | 1.76% |
| Davante Adams | LAR | WR | 1.54% |
| Brian Thomas Jr. | Jac | WR | 1.44% |
| Kayshon Boutte | NE | WR | 0.40% |
| Jayden Reed | GB | WR | 0.14% |
| Khalil Shakir | Buf | WR | 0.04% |
| Rome Odunze | Chi | WR | 0.02% |
The top wide receiver plays are largely what you would expect. What stood out was the size of the gap in optimal percentage between some WR1s and other wide receivers on the same teams, particularly how much more often Puka Nacua simmed out as the top Rams option compared to Davante Adams. That gap reflects both the compounding difficulty of Adams outproducing Nacua across multiple games and the small amount of health-related risk baked into Adams' projection.
Tight End
| Player | Team | Position | Opto |
|---|---|---|---|
| George Kittle | SF | TE | 11.00% |
| Dallas Goedert | Phi | TE | 7.16% |
| Colston Loveland | Chi | TE | 3.62% |
| Dalton Schultz | Hou | TE | 2.86% |
| Hunter Henry | NE | TE | 1.46% |
| Dalton Kincaid | Buf | TE | 0.50% |
With wide receiver and tight end combined into a single position, you do not need to roster any tight ends. In fact, a tight end appeared in our optimal sim for Week 1 just 27% of the time.
Kicker
| Player | Team | Position | Opto |
|---|---|---|---|
| Cameron Dicker | LAC | PK | 25.98% |
| Andy Borregales | NE | PK | 11.80% |
| Cam Little | Jac | PK | 11.18% |
| Ka'imi Fairbairn | Hou | PK | 10.88% |
| Jason Myers | Sea | PK | 9.20% |
| Cairo Santos | Chi | PK | 8.10% |
| Chris Boswell | Pit | PK | 6.20% |
| Ryan Fitzgerald | Car | PK | 5.84% |
| Brandon McManus | GB | PK | 4.90% |
| Wil Lutz | Den | PK | 2.24% |
| Eddy Piñeiro | SF | PK | 1.68% |
| Jake Elliott | Phi | PK | 1.26% |
| Matt Prater | Buf | PK | 0.70% |
| Harrison Mevis | LAR | PK | 0.04% |
Defense
| Player | Team | Position | Opto |
|---|---|---|---|
| Carolina Panthers | Car | TD | 24.58% |
| Pittsburgh Steelers | Pit | TD | 16.34% |
| Chicago Bears | Chi | TD | 14.42% |
| Los Angeles Chargers | LAC | TD | 9.00% |
| Jacksonville Jaguars | Jac | TD | 8.80% |
| Seattle Seahawks | Sea | TD | 8.14% |
| Buffalo Bills | Buf | TD | 7.16% |
| New England Patriots | NE | TD | 3.96% |
| Philadelphia Eagles | Phi | TD | 3.82% |
| Houston Texans | Hou | TD | 1.96% |
| Denver Broncos | Den | TD | 1.32% |
| San Francisco 49ers | SF | TD | 0.50% |
| Los Angeles Rams | LAR | TD | 0.00% |