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Bhayshul Tuten

Bhayshul Tuten

RBJAXJacksonville JaguarsQ▲ Hot

Other RBs on JAX
Games
7
2026 season
PPR PPG
16.9
RB14 overall
Total pts
118.3

This is how RBs have played against the Bears in the 2026 season.

RB1 = the highest-scoring RB against Bears in each game, not a fixed depth-chart spot.

WkTeamPlayerCarRuYdRuTDTgtRecReYdReTDFPts
1CARCARChuba Hubbard104913338123.7
2MINMINAaron Jones231050000010.5
3PHIPHISaquon Barkley1582021-209.0
4NYJNYJBraelon Allen1459022808.7
5GBGBMarShawn Lloyd10312216016.7
6ATLATLBijan Robinson961022-807.3
7NENERhamondre Stevenson62205593122.5
8SEASEAZach Charbonnet623043605.9
Average11.654.00.42.52.117.60.313.0
Median10.054.00.02.02.06.00.09.8
High2310525593123.7
Low622000-805.9

Averages are raw, outliers are never removed.

RB1 avg pts
13.0
PPR per game
Rank
28
of 32 (1 = most allowed)
vs League
-19%
lg avg 16.1
How Bhayshul Tuten should do vs the BearsSeason log, the group you pick, and a projection

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 Bhayshul Tuten 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 Bhayshul Tuten 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 Bhayshul Tuten's own average: green means the defense gives that slot more than Bhayshul Tuten usually produces.

Projected is Bhayshul Tuten'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.

Compare against
WkOppCarRuYdRuTDTgtRecReYdReTDFPts
1CLE15660112209.8
2DEN1365122-3014.2
3NE157312217017.0
4CIN177302218011.1
5PHI227203224011.6
6HOU123904448224.7
8IND1610412255129.9
Tuten avg15.770.30.42.32.125.90.416.9
Bears RB1 avg11.654.00.42.52.117.60.313.0
Difference-4.1-16.3-0.1+0.2-0.0-8.2-0.2-3.9
Projected as RB113.560.60.42.01.822.30.414.2

Difference is what the defense allows minus what Tuten 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 · Bhayshul TutenGood confidence · 14.2 proj pts7/10 start
  • Bhayshul Tuten averages 16.9 PPR points over 7 games (recent-weighted 19.5) and has played as the team's RB1.
  • The Bears have allowed 13.0 points to RB1s over 8 games (-19% vs league). The model applies 73% of that gap because the sample is small, giving a -14% adjustment.
  • Last season's average (5.9) is blended in at 22% weight because this season's sample is small.
  • Injury report: Questionable. The projection assumes the player plays.
  • Projection: 14.2 points.
  • For reference, a typical weekly starter-level RB scores about 13.1 and a top-tier one about 20.9.
  • A statistical model from box scores, Vegas lines, weather and injury tags. It cannot see role changes or in-game events.
Prediction & chance to scoreBhayshul Tuten vs the Bears

Prediction for Bhayshul Tuten

Nobody knows which slot Bhayshul Tuten will land in this week, so pick the one you expect. The projection changes because each slot faces a different average from the Bears.

If Bhayshul Tuten plays as
14.2
projected PPR points

I predict about 14.2 points for Bhayshul Tuten if playing as a RB1. Bhayshul Tuten has averaged 16.9 over 7 games, and the Bears have given up 13.0 to RB1s (-19% vs the league average of 16.1).

How this projection is built

1. The player. Bhayshul Tuten scored: Wk 1 9.8, Wk 2 14.2, Wk 3 17.0, Wk 4 11.1, Wk 5 11.6, Wk 6 24.7, Wk 8 29.9. Average 16.9; weighted toward recent games it is 16.5.

2. The defense. Over 8 games, the Bears allowed 13.0 points to their opponent's RB1. The league average for that slot is 16.1, so that is -19%.

3. Trusting small samples less. With 8 defensive games, only 73% of the gap is applied, capped at +/-30%. That gives a -14% adjustment (x0.86).

4. Result. 16.5 x 0.86 = 14.2. 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 Bhayshul Tuten is to reach it as a RB1.

44%
chance of 14+ PPR points
Why this percentage?

The projection (14.2) 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 7.6 points, leaning on Bhayshul Tuten'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 14.

With only 7 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
  • RB1s have averaged 11.6 carries, 54.0 rushing yards and 2.1 receptions against the Bears across 8 games.
  • The Bears allow 13.0 PPR points to RB1s, -19% versus the league average of 16.1 (ranked 28 of 32, where 1 is most generous). That is a tough matchup.
  • Outlier: Week 7, Rhamondre Stevenson (22.5 pts, 22 rush yds) sits far above the other games and pulls the averages up. Average with it vs without it: pts 13.0 vs 11.7; rush yds 54.0 vs 58.6. The table above keeps the raw averages.
  • Outlier: Week 2, Aaron Jones (23 car, 105 rush yds) sits far above the other games and pulls the averages up. Average with it vs without it: car 11.6 vs 10.0; rush yds 54.0 vs 46.7. The table above keeps the raw averages.
  • 4 of 8 games reached 10+ PPR points. Scores range from 5.9 to 23.7 (median 9.8).
  • RB1s scored a touchdown in 3 of 8 games (38%).

Insights are generated by rules from the table above and recalculate every week.