RBs vs San Francisco 49ers
As of Week 13 · through 2 games · PPR
Showing every RB who had a role in each game.
| Wk | Team | Player | Slot | Car | RuYd | RuTD | Tgt | Rec | ReYd | ReTD | FPts |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 |  LA | Kyren Williams | RB1 | 11 | 41 | 1 | 3 | 3 | 24 | 0 | 15.5 |
| Blake Corum | RB2 | 10 | 54 | 0 | 0 | 0 | 0 | 0 | 5.4 | ||
| Ronnie Rivers | RB3 | 5 | 19 | 0 | 1 | 1 | 5 | 0 | 3.4 | ||
| 2 |  MIA | De'Von Achane | RB1 | 20 | 74 | 0 | 6 | 3 | 19 | 0 | 12.3 |
| DJ Herman | RB2 | 0 | 0 | 0 | 3 | 1 | 18 | 0 | 2.8 | ||
| Jaylen Wright | RB3 | 2 | 11 | 0 | 0 | 0 | 0 | 0 | 1.1 | ||
| Ollie Gordon II | RB4 | 3 | 7 | 0 | 0 | 0 | 0 | 0 | 0.7 | ||
| Average | 7.3 | 29.4 | 0.1 | 1.9 | 1.1 | 9.4 | 0.0 | 5.9 | |||
| Median | 5.0 | 19.0 | 0.0 | 1.0 | 1.0 | 5.0 | 0.0 | 3.4 | |||
| High | 20 | 74 | 1 | 6 | 3 | 24 | 0 | 15.5 | |||
| Low | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.7 | |||
Averages are raw, outliers are never removed.
How Patrick Ricard should do vs the 49ersSeason log, the group you pick, and a projection
Season so far, compared with what the group you pick below has done against the 49ers, plus a projection for this game.
What is this table?
Rows at the top are every game Patrick Ricard has played this season, using the same stat columns as the table above.
Compare against picks which group of 49ers opponents to line them up with: the best RB they faced in each game (1), the second best (2), the third best (3), or all of the top three. Nobody knows which slot Patrick Ricard will land in this week, so this is your call, not a guess.
49ers avg is the average line of that group. Difference is that minus Patrick Ricard's own average: green means the defense gives that slot more than Patrick Ricard usually produces.
Projected is Patrick Ricard's recent-weighted average scaled by how generous the 49ers 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 | Car | RuYd | RuTD | Tgt | Rec | ReYd | ReTD | FPts |
|---|---|---|---|---|---|---|---|---|---|
| 1 | DAL | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0.0 |
| Ricard avg | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
| 49ers All avg | 7.3 | 29.4 | 0.1 | 1.9 | 1.1 | 9.4 | 0.0 | 5.9 | |
| Difference | +7.3 | +29.4 | +0.1 | +0.9 | +1.1 | +9.4 | +0.0 | +5.9 | |
| Projected | 0.0 | 0.0 | 0.0 | 0.9 | 0.0 | 0.0 | 0.0 | 0.0 | |
Difference is what the defense allows minus what Ricard 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 · Patrick RicardLow confidence · 0.0 proj ptsSit
Patrick Ricard usually plays as the team's RB2, so the verdict uses the RB2 numbers, not the slot selected above.
- Patrick Ricard averages 0.0 PPR points over 1 game (recent-weighted 0.0) and has played as the team's RB2.
- The 49ers have allowed 4.1 points to RB2s over 2 games (-14% vs league). The model applies 40% of that gap because the sample is small, giving a -5% adjustment.
- Projection: 0.0 points.
- For reference, a typical weekly starter-level RB scores about 12.2 and a top-tier one about 20.0.
- Confidence is low: too few games for either the player or the defense. Use this as a rough lean, not a lock.
- A statistical model from box scores, Vegas lines, weather and injury tags. It cannot see role changes or in-game events.
Prediction & chance to scorePatrick Ricard vs the 49ers
Prediction for Patrick Ricard
Nobody knows which slot Patrick Ricard will land in this week, so pick the one you expect. The projection changes because each slot faces a different average from the 49ers.
I predict about 0.0 points for Patrick Ricard if playing as a RB2. Patrick Ricard has averaged 0.0 over 1 game, and the 49ers have given up 4.1 to RB2s (-14% vs the league average of 4.8).
How this projection is built
1. The player. Patrick Ricard scored: Wk 1 0.0. Average 0.0; weighted toward recent games it is 0.0.
2. The defense. Over 2 games, the 49ers allowed 4.1 points to their opponent's RB2. The league average for that slot is 4.8, so that is -14%.
3. Trusting small samples less. With 2 defensive games, only 40% of the gap is applied, capped at +/-30%. That gives a -5% adjustment (x0.95).
4. Result. 0.0 x 0.95 = 0.0. 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 Patrick Ricard is to reach it as a RB2.
Why this percentage?
The projection (0.0) 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 0.0 points, leaning on Patrick Ricard's own game-to-game swings once there are several games (and on typical RB 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 0.
With only 1 game 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
- all RBs have averaged 7.3 carries, 29.4 rushing yards and 1.1 receptions per player-game against the 49ers across 2 games.
- The 49ers allow 20.6 PPR points to the position per game, -2% versus the league average of 21.0 (ranked 15 of 32, where 1 is most generous). That is a near-average matchup.
- Outlier: Week 2, De'Von Achane (12.3 pts, 20 car, 74 rush yds) sits far above the other games and pulls the averages up. Average with it vs without it: pts 5.9 vs 4.8; car 7.3 vs 5.2; rush yds 29.4 vs 22.0. The table above keeps the raw averages.
- Outlier: Week 1, Kyren Williams (15.5 pts) sits far above the other games and pulls the averages up. Average with it vs without it: pts 5.9 vs 4.3. The table above keeps the raw averages.
- 2 of 7 player-games reached 10+ PPR points. Scores range from 0.7 to 15.5 (median 3.4).
- all RBs scored a touchdown in 1 of 7 player-games (14%).
- 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.