RBs vs Chicago Bears
As of Week 15 · through 2 games · PPR
RB1 = the highest-scoring RB against Bears in each game, not a fixed depth-chart spot.
| Wk | Team | Player | Car | RuYd | RuTD | Tgt | Rec | ReYd | ReTD | FPts |
|---|---|---|---|---|---|---|---|---|---|---|
| 1 |  CAR | Chuba Hubbard | 10 | 49 | 1 | 3 | 3 | 38 | 1 | 23.7 |
| 2 |  MIN | Aaron Jones | 23 | 105 | 0 | 0 | 0 | 0 | 0 | 10.5 |
| Average | 16.5 | 77.0 | 0.5 | 1.5 | 1.5 | 19.0 | 0.5 | 17.1 | ||
| Median | 16.5 | 77.0 | 0.5 | 1.5 | 1.5 | 19.0 | 0.5 | 17.1 | ||
| High | 23 | 105 | 1 | 3 | 3 | 38 | 1 | 23.7 | ||
| Low | 10 | 49 | 0 | 0 | 0 | 0 | 0 | 10.5 | ||
Averages are raw, outliers are never removed.
Prediction for James Cook
Nobody knows which slot James Cook will land in this week, so pick the one you expect. The projection changes because each slot faces a different average from the Bears.
I predict about 17.5 points for James Cook if playing as a RB1. James Cook has averaged 15.4 over 2 games, and the Bears have given up 17.1 to RB1s (+9% vs the league average of 15.7).
How this projection is built
1. The player. James Cook scored: Wk 1 9.9, Wk 2 20.9. Average 15.4; weighted toward recent games it is 16.9.
2. The defense. Over 2 games, the Bears allowed 17.1 points to their opponent's RB1. The league average for that slot is 15.7, so that is +9%.
3. Trusting small samples less. With 2 defensive games, only 40% of the gap is applied, capped at +/-30%. That gives a +4% adjustment (x1.04).
4. Result. 16.9 x 1.04 = 17.5. 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 James Cook is to reach it as a RB1.
Why this percentage?
The projection (17.5) 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 10.5 points, leaning on James Cook'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 18.
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%.
Insights
- RB1s have averaged 16.5 carries, 77.0 rushing yards and 1.5 receptions against the Bears across 2 games.
- The Bears allow 17.1 PPR points to RB1s, +9% versus the league average of 15.7 (ranked 11 of 32, where 1 is most generous). That is a near-average matchup.
- 2 of 2 games reached 10+ PPR points. Scores range from 10.5 to 23.7 (median 17.1).
- Every RB1 in the sample cleared 40 rushing yards.
- RB1s scored a touchdown in 1 of 2 games (50%).
- 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.
What do these columns mean?
- Wk
- Week of the season
- Tgt
- Targets (passes thrown to the player)
- Rec
- Receptions
- ReYd
- Receiving yards
- ReTD
- Receiving touchdowns
- Car
- Carries (rushing attempts)
- RuYd
- Rushing yards
- RuTD
- Rushing touchdowns
- Cmp / Att
- Completions and pass attempts
- PaYd / PaTD
- Passing yards and touchdowns
- INT
- Interceptions thrown
- FGM / FGA
- Field goals made and attempted
- FPts
- Fantasy points in your scoring format
- Sck / TO
- Defense: sacks and takeaways
- PA
- Points allowed by a defense
- G
- Games in the sample
- vs Lg
- Percent above or below the league average
- James Cook averages 15.4 PPR points over 2 games (recent-weighted 16.0) and has played as the team's RB1.
- The Bears have allowed 17.1 points to RB1s over 2 games (+9% vs league). The model applies 40% of that gap because the sample is small, giving a +4% adjustment.
- Last season's average (17.8) is blended in at 50% weight because this season's sample is small.
- Projection: 17.5 points.
- For reference, a typical weekly starter-level RB scores about 12.2 and a top-tier one about 20.0.
- A statistical model from box scores, Vegas lines, weather and injury tags. It cannot see role changes or in-game events.
James Cook's stats vs the Bears
Season so far, compared with what the group you pick below has done against the Bears, plus a projection for this game.
What is this table?
Rows at the top are every game James Cook has played this season, using the same stat columns as the table above.
Compare against picks which group of Bears 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 James Cook will land in this week, so this is your call, not a guess.
Bears avg is the average line of that group. Difference is that minus James Cook's own average: green means the defense gives that slot more than James Cook usually produces.
Projected is James Cook's recent-weighted average scaled by how generous the Bears 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 | HOU | 13 | 57 | 0 | 4 | 3 | 12 | 0 | 9.9 |
| 2 | DET | 21 | 135 | 1 | 3 | 1 | 4 | 0 | 20.9 |
| Cook avg | 17.0 | 96.0 | 0.5 | 3.5 | 2.0 | 8.0 | 0.0 | 15.4 | |
| Bears RB1 avg | 16.5 | 77.0 | 0.5 | 1.5 | 1.5 | 19.0 | 0.5 | 17.1 | |
| Difference | -0.5 | -19.0 | +0.0 | -2.0 | -0.5 | +11.0 | +0.5 | +1.7 | |
| Projected as RB1 | 17.6 | 99.6 | 0.5 | 3.6 | 2.1 | 8.3 | 0.0 | 17.5 | |
Difference is what the defense allows minus what Cook averages (green = defense gives up more). Projected stats scale the player's averages by the matchup adjustment, so they are a rough guide.