WRs vs Las Vegas Raiders
As of Week 10 · through 2 games · PPR
Showing the three highest-scoring WRs from each game.
| Wk | Team | Player | Slot | Tgt | Rec | ReYd | ReTD | FPts |
|---|---|---|---|---|---|---|---|---|
| 1 |  MIA | Caleb Douglas | WR1 | 7 | 5 | 94 | 0 | 14.4 |
| Malik Washington | WR2 | 8 | 3 | 53 | 0 | 6.3 | ||
| Chris Bell | WR3 | 2 | 1 | 25 | 0 | 3.5 | ||
| 2 |  LAC | Ladd McConkey | WR1 | 3 | 3 | 35 | 0 | 6.5 |
| Tre Harris | WR2 | 3 | 1 | 53 | 0 | 6.3 | ||
| Quentin Johnston | WR3 | 5 | 1 | 7 | 0 | 2.4 | ||
| Average | 4.7 | 2.3 | 44.5 | 0.0 | 6.6 | |||
| Median | 4.0 | 2.0 | 44.0 | 0.0 | 6.3 | |||
| High | 8 | 5 | 94 | 0 | 14.4 | |||
| Low | 2 | 1 | 7 | 0 | 2.4 | |||
Averages are raw, outliers are never removed.
How Jaxon Smith-Njigba should do vs the RaidersSeason log, the group you pick, and a projection
Season so far, compared with what the group you pick below has done against the Raiders, plus a projection for this game.
What is this table?
Rows at the top are every game Jaxon Smith-Njigba has played this season, using the same stat columns as the table above.
Compare against picks which group of Raiders opponents to line them up with: the best WR they faced in each game (1), the second best (2), the third best (3), or all of the top three. Nobody knows which slot Jaxon Smith-Njigba will land in this week, so this is your call, not a guess.
Raiders avg is the average line of that group. Difference is that minus Jaxon Smith-Njigba's own average: green means the defense gives that slot more than Jaxon Smith-Njigba usually produces.
Projected is Jaxon Smith-Njigba's recent-weighted average scaled by how generous the Raiders were to the slot you picked. Change the slot and the projected points change, because each slot has a different matchup adjustment. Picking Top 3 uses the usual-role projection.
| Wk | Opp | Tgt | Rec | ReYd | ReTD | FPts |
|---|---|---|---|---|---|---|
| 1 | NE | 11 | 8 | 122 | 1 | 26.2 |
| 2 | ARI | 11 | 9 | 155 | 3 | 42.5 |
| Smith-Njigba avg | 11.0 | 8.5 | 138.5 | 2.0 | 34.4 | |
| Raiders Top 3 avg | 4.7 | 2.3 | 44.5 | 0.0 | 6.6 | |
| Difference | -6.3 | -6.2 | -94.0 | -2.0 | -27.8 | |
| Projected | 9.3 | 7.2 | 117.2 | 1.7 | 23.9 | |
Difference is what the defense allows minus what Smith-Njigba averages (green = defense gives up more). Projected stats scale the player's averages by the matchup adjustment, so they are a rough guide.
Start / Sit · Jaxon Smith-NjigbaMedium confidence · 23.9 proj ptsMust Start
Jaxon Smith-Njigba usually plays as the team's WR1, so the verdict uses the WR1 numbers, not the slot selected above.
- Jaxon Smith-Njigba averages 34.4 PPR points over 2 games (recent-weighted 35.3) and has played as the team's WR1.
- The Raiders have allowed 10.4 points to WR1s over 2 games (-38% vs league). The model applies 40% of that gap because the sample is small, giving a -15% adjustment.
- Last season's average (21.2) is blended in at 50% weight because this season's sample is small.
- Projection: 23.9 points.
- For reference, a typical weekly starter-level WR scores about 11.8 and a top-tier one about 20.8.
- A statistical model from box scores, Vegas lines, weather and injury tags. It cannot see role changes or in-game events.
Prediction & chance to scoreJaxon Smith-Njigba vs the Raiders
Prediction for Jaxon Smith-Njigba
Nobody knows which slot Jaxon Smith-Njigba will land in this week, so pick the one you expect. The projection changes because each slot faces a different average from the Raiders.
I predict about 23.9 points for Jaxon Smith-Njigba if playing as a WR1. Jaxon Smith-Njigba has averaged 34.4 over 2 games, and the Raiders have given up 10.4 to WR1s (-38% vs the league average of 17.0).
How this projection is built
1. The player. Jaxon Smith-Njigba scored: Wk 1 26.2, Wk 2 42.5. Average 34.4; weighted toward recent games it is 28.2.
2. The defense. Over 2 games, the Raiders allowed 10.4 points to their opponent's WR1. The league average for that slot is 17.0, so that is -38%.
3. Trusting small samples less. With 2 defensive games, only 40% of the gap is applied, capped at +/-30%. That gives a -15% adjustment (x0.85).
4. Result. 28.2 x 0.85 = 23.9. Switching slots only changes step 2 and 3: the player's own numbers stay the same, but each slot faces a different defensive average.
It is a statistical model, not knowledge of injuries, game script or weather.
Chance to score
Type a point total to see how likely Jaxon Smith-Njigba is to reach it as a WR1.
Why this percentage?
The projection (23.9) is the middle of the range. Fantasy scores swing a lot from game to game, so the model spreads possible scores around it by about 14.3 points, leaning on Jaxon Smith-Njigba's own game-to-game swings once there are several games (and on typical WR swings before that).
Scores are modelled as right-skewed, since a big game is possible but a very negative one is not. The percentage is the share of that spread at or above 24.
With only 2 games of history, treat this as a rough gauge. It gets sharper as the season goes on. It is never lower than 1% or higher than 99%.
InsightsPlain-English takeaways from the table
- top-3 WRs have averaged 2.3 receptions, 44.5 receiving yards and 0.0 receiving TDs per player-game against the Raiders across 2 games.
- The Raiders allow 19.7 PPR points to the position per game, -34% versus the league average of 29.8 (ranked 29 of 32, where 1 is most generous). That is a tough matchup.
- Outlier: Week 1, Caleb Douglas (14.4 pts, 5 rec, 94 yds) sits far above the other games and pulls the averages up. Average with it vs without it: pts 6.6 vs 5.0; rec 2.3 vs 1.8; yds 44.5 vs 34.6. The table above keeps the raw averages.
- Outlier: Week 2, Quentin Johnston (7 yds) sits far below the other games and drags the averages down. Average with it vs without it: yds 44.5 vs 52.0. The table above keeps the raw averages.
- 1 of 6 player-games reached 10+ PPR points. Scores range from 2.4 to 14.4 (median 6.3).
- top-3 WRs scored a touchdown in 0 of 6 player-games (0%).
- Small sample: only 2 games so far. Treat these numbers as directional, not settled.
Insights are generated by rules from the table above and recalculate every week.