Chicago Bears @ Green Bay Packers Matchup Analysis

Game Analysis

Create an account to get analysis and updates sent to your inbox.

Lean – Chicago (+7.5) over GREEN BAY

The Bears hired Andy Reid disciple Matt Nagy to be their new head coach after finishing as my 30th rated offense last season. Mitch Trubisky finished as the 29th quarterback in expected points added per play but Nagy will hope to bring the former 2nd-overall draft pick to the next level. There were 10 quarterbacks drafted in the top 3 this decade before Trubisky and 7 of them improved in their sophomore season while 3 dropped off. Recency bias will lead many people pointing at Jared Goff as a reason for optimism because he had an excellent second season after the team hired a young offensive-minded head coach. Although, it’s worth noting that Goff’s dramatic improvement was clearly an outlier among his peers due to a terrible rookie season much worse than Trubisky’s first year. Excluding the largest improvement and largest drop-off, Goff and Robert Griffin III, our metrics show the average development among these highly touted quarterbacks was +1.9 points per game from their rookie to sophomore season. Still, Trubisky will get every chance to succeed and it’s not crazy to think he can improve more than the average given what should be a much better play calling (Chicago was far too predictable last season). Trubisky put up great numbers in college at North Carolina while playing exclusively out of the shotgun formation but the Bears only ran the shotgun formation on about half their plays last season. Meanwhile, Nagy’s Chiefs used the shotgun 72% of the time. Nagy will look to use Tarik Cohen in the Tyreek Hill role and I expect Cohen to receive much more looks down the field after only getting 2 deep ball targets last season. Hill saw 24 targets on passes thrown more than 20 yards for Nagy’s Chiefs in 2017. I’m not as optimistic about Chicago’s two-receiver signings, Allen Robinson and Taylor Gabriel. After inking a $42 million deal, Robinson comes in after missing basically all last season with an ACL tear and wasn’t impressive at all the year prior in 2016, finishing 60th out of 92 qualifying wide receivers with only 1.3 yards per route run. The Bears will need Robinson to play more closely to his performance in 2015 where he finished 12th in the same category. Meanwhile, Gabriel was even worse by finishing with just 1.0 yards per route run last year (72nd). Our projections expect the Bears’ offense to be near the bottom of the league again but there’s certainly potential for them to break out ala Jared Goff and the 2017 Rams given that Nagy’s attack is light years ahead of the ultra-conservative and predictable offense that Trubisky was forced to run last season (a.k.a. let’s run on first-down every time and set up our rookie QB into 2^nd-and-long situations as often as possible).

Green Bay’s 2017 season was defined by an injury to their star quarterback Aaron Rodgers. Backup quarterback Brett Hundley played about 5 points worse per game and according to our numbers, the Packers would’ve scored 73 more points replacing Hundley’s plays with Rodgers level of play. That difference would have moved Green Bay’s Pythagorean win projection up from 6.3 to 8.2 wins, which is still not impressive by Green Bay’s usual standard. The mediocre performance was caused by Rodgers himself playing about 5 points per game below his career average. However, our quarterback model sees this as an anomaly and ranks Rodgers as the 2nd best quarterback in expected points added for the 2018 season.

The Packers are hoping for a Jimmy Graham resurgence after he finished 22nd out 25 qualifying tight ends in yards per route run last season. Graham finished top 10 in yards per route run the previous six seasons and his drop-off last season may not be a fluke given that tight ends typically begin declining after age 29 and Graham is now 31 years old. Graham could be a disappointment and I expect Randall Cobb to get most of the action between the numbers from Rodgers.

It might surprise people that Green Bay’s rushing attack finished with the best success rate in the NFL last year. That success was enhanced by Hundley’s 7.5 yards per rush on 36 quarterback runs but running backs Jamaal Williams and Aaron Jones combined for 4.3 ypr and the offensive line is solid, led by the excellent tackle play of David Bakhtiari and Bryan Bulaga. The Packers’ tackles will have their hand full in pass protection after the Bears recent trade for Khalil Mack, who recorded 79 quarterback pressures in 2017 (2nd).

Mike Pettine was brought in to take over Green Bay’s defense this offseason and he’ll be bringing the same aggressive pressing scheme he found so much success with under Rex Ryan in New York. The Packers know Pettine’s scheme relies on excellent cornerback play and attempted to sign Kyle Fuller, but the Bears matched the deal. Instead, Green Bay used their top two draft picks on cornerbacks and brought in Tramon Williams, who finished 9th last season in yards allowed per cover snap. The Packers also added Muhammad Wilkerson to bolster their pass rush alongside Clay Matthews and Nick Perry. Wilkerson finished 2nd in pressures amongst all defensive linemen in 2015 but has been disappointing since and Pettine is hoping a change of scenery will bring the best out of him. We’re expecting the revamped Green Bay defense to finish top 10 and the offense to be among the league’s best led by a healthy Aaron Rodgers.

My ratings don’t show much value in the side, but Chicago applies to a 70-39-6 ATS week 1 contrary indicator and I’ll lean with the Bears plus the points.

Team Stats
Game Log

Bears
Packers

CHI

Offense

Defense

Pass

Pass Plays 31.9 35.7
Succ Pass Plays 36.5% 44.4%
Sack Rate 9.5% 7.4%
Int Rate 2.2% 1.4%
Deep Pass Rate 18.1% 16.7%
Big Pass Yards 33.4% 32.0%
NYPP 5.5 6.0

Rush

Rush Plays 26.8 28.1
RB YPR 3.6 3.8
Stuff Rate 30.9% 17.6%
Succ Rush Plays 38.6% 42.9%
Big Rush Yards 51.3% 34.3%
Yards Per Rush 3.8 3.9

Game

All Snaps 58.8 63.8
Early Down Succ 39.7% 45.3%
Succ Rate 38.4% 43.1%
Big Yards Rate 38.9% 34.8%
Yards Per Play 4.8 5.0
Fumble Lost Rate 1.0% 1.4%
Time Per Play (sec) 29.8 29.7
Run Ratio 45.6% 43.5%
Starting Field Pos 26.9 28.8
Game Control -3.0 3.0

Points 16.5 20.0

Offense

Defense

Pass

Pass Plays 38.3 34.4
Succ Pass Plays 42.1% 49.0%
Sack Rate 8.5% 6.9%
Int Rate 3.1% 2.0%
Deep Pass Rate 15.5% 19.0%
Big Pass Yards 35.3% 41.1%
NYPP 5.1 6.8

Rush

Rush Plays 24.6 30.1
RB YPR 4.0 3.6
Stuff Rate 18.7% 24.8%
Succ Rush Plays 50.5% 40.6%
Big Rush Yards 30.2% 41.3%
Yards Per Rush 4.4 3.8

Game

All Snaps 62.9 64.4
Early Down Succ 48.0% 46.9%
Succ Rate 45.8% 45.1%
Big Yards Rate 37.6% 41.7%
Yards Per Play 4.9 5.4
Fumble Lost Rate 0.7% 1.1%
Time Per Play (sec) 27.8 29.5
Run Ratio 39.6% 46.3%
Starting Field Pos 26.4 29.9
Game Control -2.9 2.9

Points 20.0 24.0

* game log stats denoted as Off/Def

2017 Game Log				PASS				RUSH			GAMES
Wk	Opp	Score	Game Control	Succ Pass Plays	Sack Rate	Int Rate	NYPP	Succ Rush Plays	Stuff Rate	Yds per Rush	All Snaps	Early Down Succ	Succ Rate	Big Yards Rate	Yds per Play	Fum Lost Rate	Run Ratio	Starting Field Pos
1	ATL	17 – 23 L	-2.5	31.8% / 50.0%	9.1% / 6.3%	0.0% / 0.0%	4.0 / 9.6	52.6% / 32.0%	15.8% / 24.0%	6.6 / 2.6	63 / 57	37.5% / 45.2%	38.1% / 42.1%	31.2% / 49.7%	4.8 / 6.6	0.0% / 0.0%	30.2% / 43.9%	28.1 / 18.3
2	@TB	7 – 29 L	-18.1	56.5% / 48.5%	2.2% / 6.1%	4.4% / 0.0%	6.3 / 5.9	25.0% / 36.1%	43.8% / 11.1%	1.3 / 3.3	62 / 69	50.0% / 41.2%	48.4% / 42.0%	6.5% / 14.4%	5.0 / 4.5	3.2% / 1.4%	25.8% / 52.2%	27.0 / 31.1
3	PIT	23 – 17 W	4.4	33.3% / 47.6%	8.3% / 7.1%	4.5% / 0.0%	3.5 / 5.0	44.7% / 64.7%	28.9% / 5.9%	5.8 / 4.1	62 / 59	42.0% / 56.3%	40.3% / 52.5%	55.3% / 29.4%	4.9 / 4.8	1.6% / 3.4%	61.3% / 28.8%	32.7 / 36.4
4	@GB	14 – 35 L	-16.9	38.2% / 41.4%	2.9% / 6.9%	6.1% / 0.0%	6.0 / 5.8	40.0% / 48.0%	26.7% / 4.0%	3.4 / 3.7	64 / 54	36.0% / 43.2%	39.1% / 44.4%	25.6% / 50.6%	4.8 / 4.8	3.1% / 0.0%	46.9% / 46.3%	28.5 / 33.5
5	MIN	17 – 20 L	-0.9	37.0% / 50.0%	3.7% / 11.1%	3.8% / 0.0%	5.9 / 3.9	48.3% / 35.5%	13.8% / 25.8%	4.0 / 5.1	56 / 67	46.5% / 44.2%	42.9% / 43.3%	34.7% / 30.3%	4.9 / 4.5	1.8% / 0.0%	51.8% / 46.3%	26.6 / 30.9
6	@BAL	27 – 24 W	4.4	28.6% / 27.3%	19.0% / 6.8%	0.0% / 4.9%	5.3 / 3.8	41.8% / 46.2%	29.1% / 15.4%	4.2 / 4.8	76 / 70	42.1% / 37.3%	38.2% / 34.3%	41.1% / 21.6%	4.5 / 4.2	2.6% / 1.4%	72.4% / 37.1%	27.6 / 29.9
7	CAR	17 – 3 W	11.4	18.2% / 41.0%	36.4% / 12.8%	0.0% / 5.9%	7.7 / 4.7	32.3% / 33.3%	16.1% / 33.3%	2.3 / 3.6	42 / 69	41.7% / 37.7%	28.6% / 37.7%	67.3% / 49.8%	3.7 / 4.2	0.0% / 1.4%	73.8% / 43.5%	28.7 / 24.6
8	@NO	12 – 20 L	-7.8	32.4% / 50.0%	5.9% / 6.7%	3.1% / 0.0%	4.4 / 9.5	45.2% / 36.4%	32.3% / 18.2%	5.1 / 3.2	65 / 63	36.2% / 52.1%	38.5% / 42.9%	61.2% / 57.9%	4.7 / 6.2	0.0% / 3.2%	47.7% / 52.4%	24.8 / 30.8
10	GB	16 – 23 L	-5.0	37.5% / 50.0%	12.5% / 10.7%	0.0% / 0.0%	6.7 / 6.5	29.4% / 52.6%	35.3% / 15.8%	3.2 / 4.2	57 / 66	35.7% / 55.3%	35.1% / 51.5%	51.1% / 39.1%	5.7 / 5.2	1.8% / 0.0%	29.8% / 57.6%	26.5 / 30.8
11	DET	24 – 27 L	0.0	48.4% / 52.9%	3.2% / 8.8%	0.0% / 0.0%	5.7 / 8.4	60.0% / 40.0%	13.3% / 40.0%	7.4 / 2.6	61 / 59	56.9% / 53.2%	54.1% / 47.5%	45.5% / 39.4%	6.5 / 6.0	1.6% / 1.7%	49.2% / 42.4%	23.9 / 24.0
12	@PHI	3 – 31 L	-17.1	22.9% / 45.0%	5.7% / 2.5%	6.1% / 0.0%	3.8 / 6.1	6.7% / 41.7%	53.3% / 22.2%	0.5 / 5.0	50 / 76	18.2% / 45.1%	18.0% / 43.4%	7.8% / 32.6%	2.8 / 5.6	0.0% / 3.9%	30.0% / 47.4%	27.9 / 40.5
13	SF	14 – 15 L	2.5	47.1% / 56.4%	11.8% / 5.1%	0.0% / 2.7%	5.0 / 7.1	21.1% / 45.7%	26.3% / 22.9%	3.3 / 3.2	36 / 74	26.9% / 50.9%	33.3% / 51.4%	23.8% / 27.5%	4.1 / 5.3	0.0% / 0.0%	52.8% / 47.3%	25.7 / 24.9
14	@CIN	33 – 7 W	9.2	54.5% / 30.0%	6.1% / 7.5%	0.0% / 2.7%	7.6 / 4.1	55.3% / 53.8%	31.6% / 7.7%	6.1 / 5.4	71 / 53	58.6% / 38.5%	54.9% / 35.8%	43.6% / 33.3%	6.8 / 4.4	0.0% / 1.9%	53.5% / 24.5%	30.9 / 23.5
15	@DET	10 – 20 L	-10.6	45.8% / 43.2%	4.2% / 10.8%	6.5% / 0.0%	6.4 / 5.5	46.7% / 38.1%	33.3% / 4.8%	2.9 / 4.4	63 / 58	48.0% / 41.9%	46.0% / 41.4%	16.6% / 27.9%	5.5 / 5.1	0.0% / 1.7%	23.8% / 36.2%	23.9 / 28.0
16	CLE	20 – 3 W	8.7	28.6% / 35.1%	17.9% / 2.7%	0.0% / 5.6%	5.8 / 4.8	35.5% / 40.0%	41.9% / 15.0%	3.1 / 3.8	59 / 57	26.2% / 37.2%	32.2% / 36.8%	60.1% / 25.3%	4.4 / 4.4	0.0% / 1.8%	52.5% / 35.1%	27.9 / 26.8
17	@MIN	10 – 23 L	-9.5	23.7% / 41.9%	2.6% / 6.5%	0.0% / 0.0%	4.5 / 5.8	33.3% / 42.1%	53.3% / 15.8%	2.0 / 3.9	53 / 69	33.3% / 46.2%	26.4% / 42.0%	51.7% / 28.6%	3.8 / 4.8	0.0% / 0.0%	28.3% / 55.1%	19.5 / 27.3

* game log stats denoted as Off/Def

2017 Game Log				PASS				RUSH			GAMES
Wk	Opp	Score	Game Control	Succ Pass Plays	Sack Rate	Int Rate	NYPP	Succ Rush Plays	Stuff Rate	Yds per Rush	All Snaps	Early Down Succ	Succ Rate	Big Yards Rate	Yds per Play	Fum Lost Rate	Run Ratio	Starting Field Pos
1	SEA	17 – 9 W	2.5	50.0% / 40.0%	8.7% / 10.0%	2.4% / 0.0%	6.2 / 4.5	35.5% / 38.9%	19.4% / 50.0%	2.8 / 5.0	77 / 48	44.6% / 44.4%	44.2% / 39.6%	37.8% / 58.7%	4.8 / 4.7	0.0% / 2.1%	40.3% / 37.5%	25.9 / 27.5
2	@ATL	23 – 34 L	-12.4	50.9% / 51.6%	5.7% / 9.7%	2.0% / 0.0%	5.8 / 7.2	56.3% / 55.6%	25.0% / 18.5%	3.8 / 5.2	69 / 58	53.8% / 55.3%	52.2% / 53.4%	24.2% / 50.0%	5.3 / 6.3	1.4% / 0.0%	23.2% / 46.6%	22.1 / 26.7
3	CIN	27 – 24 W	-6.6	43.8% / 53.3%	12.5% / 10.0%	2.4% / 0.0%	5.8 / 6.4	47.1% / 32.3%	29.4% / 29.0%	3.8 / 3.6	65 / 61	44.0% / 46.8%	44.6% / 42.6%	58.1% / 31.8%	5.3 / 5.0	0.0% / 1.6%	26.2% / 50.8%	25.8 / 26.5
4	CHI	35 – 14 W	16.9	41.4% / 38.2%	6.9% / 2.9%	0.0% / 6.1%	5.8 / 6.0	48.0% / 40.0%	4.0% / 26.7%	3.7 / 3.4	54 / 64	43.2% / 36.0%	44.4% / 39.1%	50.6% / 25.6%	4.8 / 4.8	0.0% / 3.1%	46.3% / 46.9%	33.5 / 28.5
5	@DAL	35 – 31 W	-4.2	51.5% / 59.5%	12.1% / 2.7%	0.0% / 2.8%	5.5 / 6.6	64.0% / 60.0%	12.0% / 14.3%	6.4 / 4.7	58 / 72	58.0% / 57.9%	56.9% / 59.7%	43.3% / 28.7%	5.9 / 5.7	1.7% / 2.8%	43.1% / 48.6%	22.3 / 25.7
6	@MIN	10 – 23 L	-5.9	39.0% / 44.7%	9.8% / 0.0%	8.1% / 2.6%	3.8 / 6.3	20.8% / 35.3%	29.2% / 41.2%	3.0 / 3.3	65 / 72	33.3% / 43.9%	32.3% / 40.3%	11.5% / 46.0%	3.5 / 4.9	0.0% / 1.4%	36.9% / 47.2%	30.1 / 30.2
7	NO	17 – 26 L	2.5	23.1% / 59.0%	3.8% / 2.6%	4.0% / 5.3%	3.0 / 8.3	70.8% / 53.8%	16.7% / 12.8%	7.5 / 4.2	50 / 78	48.7% / 61.4%	46.0% / 56.4%	45.4% / 49.2%	5.2 / 6.3	0.0% / 0.0%	48.0% / 50.0%	18.2 / 30.1
9	DET	17 – 30 L	-9.8	43.9% / 64.7%	7.3% / 2.9%	0.0% / 0.0%	5.7 / 10.4	70.6% / 24.2%	11.8% / 45.5%	4.6 / 1.9	58 / 67	59.6% / 40.7%	51.7% / 44.8%	25.4% / 43.2%	5.4 / 6.2	0.0% / 1.5%	29.3% / 49.3%	25.8 / 32.5
10	@CHI	23 – 16 W	5.0	50.0% / 37.5%	10.7% / 12.5%	0.0% / 0.0%	6.5 / 6.7	52.6% / 29.4%	15.8% / 35.3%	4.2 / 3.2	66 / 57	55.3% / 35.7%	51.5% / 35.1%	39.1% / 51.1%	5.2 / 5.7	0.0% / 1.8%	57.6% / 29.8%	30.8 / 26.5
11	BAL	0 – 23 L	-7.6	38.1% / 32.3%	14.3% / 9.7%	8.3% / 3.6%	4.5 / 5.2	44.0% / 44.4%	32.0% / 25.9%	3.0 / 2.2	67 / 58	44.0% / 43.9%	40.3% / 37.9%	26.4% / 34.1%	4.0 / 3.8	3.0% / 0.0%	37.3% / 46.6%	20.1 / 46.6
12	@PIT	28 – 31 L	1.4	40.0% / 65.2%	13.3% / 2.2%	0.0% / 4.4%	7.6 / 7.4	54.2% / 45.8%	20.8% / 8.3%	3.3 / 5.0	54 / 70	45.0% / 57.1%	46.3% / 58.6%	60.3% / 38.1%	5.7 / 6.6	0.0% / 1.4%	44.4% / 34.3%	26.9 / 31.7
13	TB	26 – 20 W	1.6	33.3% / 43.6%	8.3% / 17.9%	4.5% / 0.0%	3.2 / 5.9	60.0% / 48.6%	13.3% / 17.1%	6.7 / 4.7	54 / 74	52.5% / 43.1%	48.1% / 45.9%	40.1% / 34.7%	5.1 / 5.3	0.0% / 1.4%	55.6% / 47.3%	28.5 / 25.3
14	@CLE	27 – 21 W	-4.5	57.4% / 43.3%	2.1% / 6.7%	0.0% / 7.1%	5.4 / 7.0	39.3% / 39.3%	32.1% / 14.3%	3.1 / 4.9	75 / 58	51.9% / 39.5%	50.7% / 41.4%	28.7% / 32.7%	4.6 / 6.0	0.0% / 0.0%	37.3% / 48.3%	28.5 / 22.4
15	@CAR	24 – 31 L	-5.5	46.8% / 56.3%	6.4% / 3.1%	6.8% / 0.0%	5.6 / 7.4	63.2% / 45.2%	10.5% / 14.3%	6.3 / 3.7	66 / 74	53.8% / 55.4%	51.5% / 50.0%	44.5% / 38.7%	5.8 / 5.3	1.5% / 0.0%	28.8% / 56.8%	28.8 / 27.7
16	MIN	0 – 16 L	-9.1	31.7% / 42.9%	2.4% / 10.7%	5.0% / 0.0%	3.1 / 4.4	41.7% / 32.4%	16.7% / 10.8%	4.7 / 3.1	65 / 65	41.3% / 45.5%	35.4% / 36.9%	19.2% / 44.4%	3.7 / 3.7	0.0% / 0.0%	36.9% / 56.9%	28.3 / 31.8
17	@DET	11 – 35 L	-11.1	33.3% / 51.6%	11.1% / 6.5%	6.3% / 0.0%	4.3 / 9.8	40.7% / 25.0%	11.1% / 33.3%	3.8 / 2.2	63 / 55	38.3% / 43.9%	36.5% / 40.0%	46.9% / 60.8%	4.1 / 6.5	3.2% / 0.0%	42.9% / 43.6%	26.3 / 38.2

Chicago Bears @

Green Bay Packers

Sun, Sep 9

5:20 PM Pacific

Game Analysis