Jacksonville Jaguars @ New York Giants Matchup Analysis

Game Analysis

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Note: I released this play via mass email to everyone on my mailing list and posted it in the blog section of this site on August 8 when the line was +3.5 (-115). The line has moved down a bit but the Giants are still a 1-Star Best Bet at +3 or more.

**NEW YORK GIANTS (+3.5 at -115) over Jacksonville Jaguars

New York had high hopes last season after a successful 11-5 campaign in 2016, but an injury-plagued offense and a disappointing defensive performance (after ranking 6th in 2016) led to a disastrous 3-13 season and the firing of head coach Ben McAdoo. Pat Shurmur, who had good success transforming the Minnesota Vikings’ offense last season, is the new head coach and the offense should be much better with Shurmur at the helm.

A lot went wrong for the Giants and QB Eli Manning last season but nothing tops losing his top 3 wide receivers in the same week 5 game. Sterling Shepherd missed a month while Odell Beckham and Brandon Marshall missed the remainder of the season. Injuries on the outside combined with the lack of a real threat in the ground game led to a predictable offense and Derek Carr was the only quarterback afforded less time in the pocket than Manning last year. The good news is the Giants seem to have a solution to these offensive problems for 2018.

New York bolstered their offensive line by adding former Patriots’ starter Nate Solder at left tackle and drafting guard Will Hernandez at 34th overall, which should open up lanes for number 2 overall pick Saquon Barkley up front. First-year running backs are coming fast out of the gates recently with three rookies finishing top 10 in scrimmage yards last season after two rookies finished in the top 10 in that category in 2016. Barkley is the consensus projected top contributor of this year’s class, listed at nearly at a coin-flip (+125) to win Rookie of the Year at Bookmaker, and he will have the benefit of running the same inside zone scheme with Shurmur that he ran so successfully at Penn State. The return of Odell Beckham will also add a spark to New York’s offense and reports out of training camp show he’s taking some snaps in the slot as Shurmur loves to utilize inside receivers with both Adam Thielen and Stefon Diggs of the Vikings finishing in the top 10 last season in yards per route run from the slot. The strategy could prove especially effective versus a Jaguars secondary that couldn’t retain nickelback Aaron Colvin, who ranked 4th last season in yards allowed per slot cover snap.

Last season’s offensive woes directly affected New York’s defense in the field position game with Giants’ opponent drives average start at the 30-yard line (30th in the NFL). New York’s defense dropped from 6th in my 2016 ratings to 24th last year. The Giants’ linebackers were terrible in coverage as they surrendered the 28th most receiving yards to tight ends and the 29th most yards per target to opposing running backs. However, New York seems to have addressed the issue with the signing of LB Alec Ogletree, who finished 10th in yards allowed per cover snap amongst linebackers (min 300 snaps). Top cornerback Janoris Jenkins didn’t get along with the previous coaching staff and played much of last season hurt before opting for surgery in week 13. Jenkins finished 6th in yards allowed per cover snap amongst all cornerbacks in 2016 and new defensive coordinator James Bettcher will want him back at that level after spending three years in Arizona with Patrick Peterson at his disposal. Still, arguably Bettcher’s best asset on this Giants defense is tackle Damon Harrison, who tied for the league lead in 2017 with 45 run stops. New York has solid defensive talent and should improve on that side of the ball.

The success of the 2017 Jaguars was due to their defense, which ranked 2nd in the league in points allowed. The Jacksonville stop unit was led up front by Calais Campbell and earned the nickname Sacksonville with an 8.8% sack rate (2nd). However, much of the damage was against backup quarterbacks and Campbell himself recorded 9 of his 14.5 sacks versus just Houston and Indianapolis. Jacksonville became the first team since the 2013 Seahawks to hold opponents under 5 yards per pass play and they also led the league with a 4.1% interception rate. However, there have been 25 teams in the last 5 seasons to gain more than 100 points in expected points added from interceptions, including the Jaguars last year, and those teams averaged just 73 points added from picks the following season, which is exactly the league average. Furthermore, Jacksonville’s defense experienced a league-leading 19% swing in fumble recovery rate luck from 2016 and is unlikely to be as lucky recovering fumbles this season.

Great defensive seasons are often the result of good fortune in combination with good talent and the correlation of year-to-year points allowed on defense in the NFL is only half of the year-to-year correlation of points scored, which illustrates how much of a team’s defensive performance is out of their control. So, while the Jags’ defense may be just as talented as a season ago, their performance level is very likely to regress towards the mean. Last season, New York was just one of the many examples of drastic fluctuations a defense can experience from one year to the next and the Jaguars’ likely defensive regression is one reason they enter this season a bit overrated.

The Jaguars’ offense was built around RB Leonard Fournette, who had seemingly solid statistics but finished with less than 4 yards per rush, ranking 28th among qualifying running backs. Blake Bortles rated about average last season in our pass efficiency numbers but he benefitted from big leads in many games, which allowed him to attempt the fewest passes since his rookie season. Our quarterback model has Bortles ranked 23rd heading into 2018 and I expect the Jags’ offense to finish in the bottom half of the league.

The Jaguars went 9 years without a winning record before nearly reaching the Super Bowl last season but without any exceptionally dynamic players on offense and a defense in line for some regression, it looks like they will take a step back this year. Meanwhile, the Giants are adding two excellent offensive skill players in Odell Beckham and Saquon Barkley, have a better offensive line, and I expect the defense to bounce back to a level somewhere between their performance of the last two seasons, which would be a significant improvement over 2017’s uninspired effort.

Historically, home field advantage is worth slightly less in week 1 but even after accounting for that this game should be closer to pick (our current numbers favor Jacksonville by just 0.3 points). And, there is some history to suggest that the Giants enter this season underrated. Teams that won 4 or fewer games the previous season, but have won at least 12 games total in the previous two seasons combined, are 28-14-1 ATS in week 1 games. There is some injury risk in releasing this play now but injuries could negatively affect either side and there is more risk in having this line move lower. I’ll take the New York Giants for 2-Stars at +3.5 (-115 or better) and for 1-Star down to +3 at -110 odds.

Team Stats
Game Log

Jaguars
Giants

JAC

Offense

Defense

Pass

Pass Plays 33.6 37.1
Succ Pass Plays 45.1% 38.5%
Sack Rate 4.6% 8.9%
Int Rate 2.0% 3.5%
Deep Pass Rate 18.2% 21.2%
Big Pass Yards 34.3% 43.6%
NYPP 6.6 5.1

Rush

Rush Plays 34.1 26.9
RB YPR 3.7 3.9
Stuff Rate 21.8% 23.0%
Succ Rush Plays 41.9% 44.8%
Big Rush Yards 41.9% 38.3%
Yards Per Rush 4.2 4.1

Game

All Snaps 67.7 64.0
Early Down Succ 46.0% 44.9%
Succ Rate 43.4% 41.5%
Big Yards Rate 39.3% 42.8%
Yards Per Play 5.3 4.7
Fumble Lost Rate 0.8% 1.2%
Time Per Play (sec) 28.5 27.2
Run Ratio 50.7% 42.6%
Starting Field Pos 28.1 27.8
Game Control 4.9 -4.9

Points 25.9 17.7

NYG

Offense

Defense

Pass

Pass Plays 40.1 36.6
Succ Pass Plays 43.0% 43.7%
Sack Rate 6.0% 4.5%
Int Rate 2.3% 2.2%
Deep Pass Rate 13.5% 17.8%
Big Pass Yards 29.8% 41.0%
NYPP 5.3 7.2

Rush

Rush Plays 25.3 30.3
RB YPR 3.6 3.8
Stuff Rate 20.8% 22.6%
Succ Rush Plays 40.8% 42.5%
Big Rush Yards 34.0% 41.7%
Yards Per Rush 3.7 4.0

Game

All Snaps 65.4 66.9
Early Down Succ 46.6% 45.6%
Succ Rate 42.6% 42.7%
Big Yards Rate 31.8% 43.3%
Yards Per Play 4.8 5.6
Fumble Lost Rate 0.8% 0.6%
Time Per Play (sec) 26.6 28.6
Run Ratio 38.5% 45.6%
Starting Field Pos 26.6 30.2
Game Control -2.8 2.8

Points 15.4 24.3

* 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	@HOU	30 – 7 W	11.9	52.4% / 34.8%	0.0% / 21.7%	0.0% / 2.8%	6.0 / 2.4	41.5% / 60.9%	17.1% / 17.4%	3.8 / 4.0	62 / 69	53.3% / 44.6%	45.2% / 43.5%	32.6% / 12.8%	4.5 / 2.9	0.0% / 4.3%	66.1% / 33.3%	38.2 / 26.5
2	TEN	16 – 37 L	-7.9	41.7% / 42.9%	5.6% / 3.6%	5.9% / 3.7%	5.9 / 7.5	64.0% / 68.4%	12.0% / 10.5%	4.0 / 4.8	61 / 66	52.1% / 64.0%	50.8% / 57.6%	23.5% / 41.6%	5.1 / 5.9	1.6% / 0.0%	41.0% / 57.6%	23.4 / 39.9
3	BAL	44 – 7 W	23.9	54.5% / 24.1%	0.0% / 6.9%	0.0% / 7.4%	7.4 / 1.8	31.6% / 56.0%	10.5% / 20.0%	4.4 / 5.4	71 / 54	48.1% / 42.9%	42.3% / 38.9%	35.8% / 39.2%	5.8 / 3.4	0.0% / 1.9%	53.5% / 46.3%	38.5 / 24.1
4	@NYJ	20 – 23 L	-2.3	30.6% / 44.4%	2.8% / 13.9%	2.9% / 3.2%	3.8 / 6.0	57.5% / 31.3%	20.0% / 43.8%	4.4 / 8.0	76 / 68	50.8% / 37.3%	44.7% / 38.2%	27.6% / 68.6%	4.1 / 6.9	0.0% / 1.5%	52.6% / 47.1%	27.0 / 29.5
5	@PIT	30 – 9 W	4.5	37.5% / 42.9%	12.5% / 3.6%	7.1% / 9.3%	5.1 / 5.4	40.5% / 40.0%	24.3% / 35.0%	6.2 / 3.5	53 / 76	36.6% / 41.0%	39.6% / 42.1%	60.1% / 44.5%	5.9 / 4.9	0.0% / 0.0%	69.8% / 26.3%	26.4 / 21.8
6	LA	17 – 27 L	-5.1	37.5% / 37.5%	12.5% / 12.5%	2.9% / 0.0%	5.5 / 4.5	42.3% / 64.7%	30.8% / 20.6%	6.5 / 4.2	66 / 58	42.0% / 65.9%	39.4% / 53.4%	54.2% / 35.5%	5.9 / 4.3	0.0% / 1.7%	39.4% / 58.6%	25.3 / 30.5
7	@IND	27 – 0 W	18.7	53.6% / 34.0%	3.6% / 21.3%	0.0% / 0.0%	11.8 / 2.9	44.7% / 60.0%	21.1% / 20.0%	5.0 / 4.8	66 / 67	49.0% / 46.9%	48.5% / 41.8%	61.8% / 41.4%	7.9 / 3.5	3.0% / 0.0%	57.6% / 29.9%	20.1 / 28.0
9	CIN	23 – 7 W	7.2	55.3% / 30.0%	0.0% / 10.0%	0.0% / 0.0%	6.8 / 6.0	41.5% / 15.8%	12.2% / 21.1%	3.7 / 1.6	79 / 39	44.1% / 29.6%	48.1% / 23.1%	32.8% / 52.7%	5.2 / 3.8	1.3% / 0.0%	51.9% / 48.7%	21.1 / 20.2
10	LAC	20 – 17 W	-0.3	37.0% / 43.2%	5.6% / 0.0%	3.9% / 2.7%	4.9 / 6.4	29.6% / 48.4%	29.6% / 25.8%	5.0 / 2.8	81 / 68	36.1% / 54.9%	34.6% / 45.6%	34.7% / 38.4%	4.9 / 4.8	0.0% / 1.5%	33.3% / 45.6%	30.7 / 21.1
11	@CLE	19 – 7 W	3.9	31.3% / 32.4%	6.3% / 13.5%	0.0% / 6.3%	4.5 / 3.6	31.1% / 36.8%	35.6% / 26.3%	3.1 / 2.7	77 / 56	32.1% / 40.0%	31.2% / 33.9%	24.2% / 42.2%	3.7 / 3.3	1.3% / 5.4%	58.4% / 33.9%	33.0 / 30.4
12	@ARI	24 – 27 L	-5.2	40.0% / 43.6%	8.6% / 2.6%	3.1% / 2.6%	3.7 / 6.1	36.4% / 40.6%	31.8% / 21.9%	4.1 / 3.4	57 / 71	45.5% / 44.2%	38.6% / 42.3%	31.5% / 33.9%	3.8 / 4.9	3.5% / 1.4%	38.6% / 45.1%	25.5 / 30.9
13	IND	30 – 10 W	11.5	56.8% / 44.7%	2.7% / 10.5%	0.0% / 5.9%	8.9 / 3.9	40.7% / 50.0%	33.3% / 15.4%	3.6 / 5.4	64 / 64	45.8% / 46.7%	50.0% / 46.9%	39.9% / 39.3%	6.7 / 4.5	0.0% / 0.0%	42.2% / 40.6%	30.9 / 21.3
14	SEA	30 – 24 W	6.2	51.9% / 36.4%	0.0% / 6.1%	0.0% / 9.7%	9.9 / 7.9	34.9% / 45.8%	16.3% / 45.8%	3.7 / 5.9	70 / 57	51.0% / 44.7%	41.4% / 40.4%	47.4% / 77.8%	6.1 / 7.0	1.4% / 0.0%	61.4% / 42.1%	30.6 / 30.0
15	HOU	45 – 7 W	22.7	53.3% / 22.9%	3.3% / 11.4%	0.0% / 3.2%	10.9 / 2.8	42.5% / 47.6%	20.0% / 9.5%	3.5 / 4.1	70 / 56	53.6% / 35.0%	47.1% / 32.1%	49.6% / 40.9%	6.7 / 3.3	0.0% / 0.0%	57.1% / 37.5%	33.1 / 19.9
16	@SF	33 – 44 L	-7.9	54.9% / 64.5%	2.0% / 3.2%	6.0% / 3.3%	7.5 / 7.7	42.9% / 47.2%	28.6% / 22.2%	3.3 / 3.7	79 / 67	51.6% / 54.0%	50.6% / 55.2%	28.0% / 38.4%	6.0 / 5.5	0.0% / 0.0%	35.4% / 53.7%	25.5 / 38.4
17	@TEN	10 – 15 L	-5.6	33.3% / 29.2%	5.6% / 12.5%	5.9% / 0.0%	4.1 / 4.8	50.0% / 37.5%	16.7% / 30.0%	3.5 / 2.9	60 / 64	40.9% / 40.0%	40.0% / 34.4%	10.0% / 51.1%	3.8 / 3.6	3.3% / 1.6%	40.0% / 62.5%	21.9 / 38.2
18	BUF	10 – 3 W	1.7	33.3% / 26.2%	8.3% / 4.8%	0.0% / 5.0%	3.1 / 3.2	48.6% / 43.8%	22.9% / 15.6%	4.5 / 4.1	59 / 74	50.0% / 30.9%	42.4% / 33.8%	51.5% / 18.3%	3.9 / 3.6	0.0% / 0.0%	59.3% / 43.2%	26.3 / 21.2
19	@PIT	45 – 42 W	11.0	50.0% / 50.0%	0.0% / 3.3%	0.0% / 1.7%	8.2 / 7.7	50.0% / 33.3%	11.1% / 27.8%	4.6 / 4.6	62 / 78	48.9% / 44.6%	50.0% / 46.2%	46.7% / 49.7%	6.1 / 7.0	0.0% / 1.3%	58.1% / 23.1%	35.3 / 28.3
20	@NE	20 – 24 L	4.0	51.3% / 47.6%	7.7% / 7.1%	0.0% / 0.0%	7.0 / 7.1	26.5% / 22.7%	20.6% / 9.1%	3.0 / 2.2	73 / 64	43.4% / 45.7%	39.7% / 39.1%	54.5% / 46.7%	5.2 / 5.4	0.0% / 1.6%	46.6% / 34.4%	20.9 / 27.8

* 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	@DAL	3 – 19 L	-9.1	48.8% / 48.7%	7.3% / 2.6%	2.6% / 0.0%	4.8 / 6.7	23.1% / 54.8%	7.7% / 19.4%	2.8 / 4.2	54 / 70	46.2% / 50.9%	42.6% / 51.4%	27.8% / 37.0%	4.3 / 5.6	0.0% / 0.0%	24.1% / 44.3%	16.0 / 29.4
2	DET	10 – 24 L	-7.5	37.8% / 33.3%	13.5% / 12.5%	3.1% / 0.0%	5.6 / 5.0	38.9% / 43.8%	27.8% / 34.4%	3.4 / 4.3	55 / 56	41.5% / 37.5%	38.2% / 39.3%	30.0% / 42.4%	4.9 / 4.6	0.0% / 1.8%	32.7% / 57.1%	24.3 / 37.4
3	@PHI	24 – 27 L	-4.0	59.6% / 41.2%	0.0% / 8.8%	4.3% / 0.0%	7.8 / 4.7	23.5% / 48.7%	23.5% / 23.1%	2.9 / 5.0	64 / 73	55.8% / 47.3%	50.0% / 45.2%	23.4% / 30.4%	6.5 / 4.9	0.0% / 1.4%	26.6% / 53.4%	34.6 / 21.5
4	@TB	23 – 25 L	-5.2	49.0% / 48.7%	0.0% / 2.6%	0.0% / 0.0%	5.9 / 8.3	35.7% / 42.3%	28.6% / 19.2%	3.3 / 4.3	77 / 65	44.1% / 56.3%	44.2% / 46.2%	27.4% / 57.3%	4.9 / 6.7	0.0% / 0.0%	36.4% / 40.0%	27.7 / 29.9
5	LAC	22 – 27 L	2.4	34.1% / 36.4%	12.2% / 0.0%	2.8% / 2.3%	4.5 / 5.9	72.0% / 31.3%	12.0% / 21.9%	6.1 / 3.9	66 / 76	54.0% / 34.0%	48.5% / 34.2%	46.3% / 36.2%	5.1 / 5.1	1.5% / 0.0%	37.9% / 42.1%	28.2 / 29.0
6	@DEN	23 – 10 W	10.4	40.9% / 35.1%	13.6% / 7.0%	0.0% / 3.8%	5.4 / 6.4	18.8% / 44.4%	40.6% / 11.1%	4.6 / 2.6	54 / 75	27.5% / 40.0%	27.8% / 37.3%	53.4% / 47.0%	4.9 / 5.5	0.0% / 1.3%	59.3% / 24.0%	31.2 / 27.0
7	SEA	7 – 24 L	-1.0	22.5% / 50.0%	2.5% / 2.5%	0.0% / 0.0%	3.3 / 8.0	41.2% / 50.0%	17.6% / 21.9%	2.7 / 3.3	57 / 72	31.8% / 53.6%	28.1% / 50.0%	14.1% / 43.9%	3.1 / 5.9	1.8% / 1.4%	29.8% / 44.4%	22.8 / 33.8
9	LA	17 – 51 L	-19.5	42.5% / 54.5%	5.0% / 0.0%	2.6% / 0.0%	5.2 / 14.1	59.3% / 37.5%	11.1% / 40.0%	4.1 / 4.1	67 / 62	51.0% / 44.7%	49.3% / 43.5%	38.1% / 71.3%	4.8 / 7.6	3.0% / 0.0%	40.3% / 64.5%	27.0 / 40.8
10	@SF	21 – 31 L	-4.9	55.0% / 60.0%	7.5% / 0.0%	0.0% / 4.0%	6.5 / 11.5	52.2% / 41.7%	21.7% / 19.4%	5.0 / 5.3	63 / 61	56.5% / 51.2%	54.0% / 49.2%	35.6% / 67.7%	5.9 / 7.8	1.6% / 1.6%	36.5% / 59.0%	26.6 / 31.9
11	KC	12 – 9 W	2.1	38.9% / 42.9%	0.0% / 2.4%	2.8% / 7.3%	5.7 / 5.5	40.0% / 51.7%	22.9% / 10.3%	3.2 / 4.6	71 / 71	45.1% / 49.2%	39.4% / 46.5%	22.0% / 41.6%	4.5 / 5.1	0.0% / 0.0%	49.3% / 40.8%	30.2 / 21.5
12	@WAS	10 – 20 L	-0.8	29.0% / 35.1%	12.9% / 16.2%	3.7% / 3.2%	2.8 / 5.4	32.0% / 38.2%	20.0% / 23.5%	3.4 / 3.6	56 / 71	36.8% / 44.0%	30.4% / 36.6%	22.2% / 47.7%	3.1 / 4.6	0.0% / 0.0%	44.6% / 47.9%	21.8 / 32.4
13	@OAK	17 – 24 L	-4.2	40.5% / 48.6%	8.1% / 2.7%	0.0% / 0.0%	5.4 / 7.6	50.0% / 43.3%	20.8% / 26.7%	2.7 / 4.0	61 / 67	46.8% / 48.9%	44.3% / 46.3%	40.8% / 41.5%	4.3 / 6.0	3.3% / 1.5%	39.3% / 44.8%	28.0 / 28.7
14	DAL	10 – 30 L	-2.1	56.5% / 50.0%	0.0% / 0.0%	4.3% / 0.0%	5.0 / 11.1	55.2% / 50.0%	20.7% / 17.6%	3.5 / 3.7	75 / 64	61.0% / 56.8%	56.0% / 50.0%	17.6% / 51.4%	4.4 / 7.1	0.0% / 0.0%	38.7% / 53.1%	24.5 / 25.3
15	PHI	29 – 34 L	1.6	51.7% / 43.6%	1.7% / 2.6%	1.8% / 0.0%	7.4 / 6.0	43.5% / 39.3%	21.7% / 17.9%	3.3 / 3.9	81 / 67	50.0% / 43.1%	49.4% / 41.8%	48.4% / 24.0%	6.2 / 5.1	0.0% / 0.0%	28.4% / 41.8%	24.4 / 36.1
16	@ARI	0 – 23 L	-10.7	51.1% / 43.2%	4.3% / 5.4%	4.4% / 5.7%	5.3 / 5.8	30.0% / 25.0%	25.0% / 35.7%	2.2 / 2.7	67 / 65	57.1% / 36.7%	44.8% / 35.4%	23.5% / 29.3%	4.4 / 4.5	1.5% / 0.0%	29.9% / 43.1%	27.6 / 27.0
17	WAS	18 – 10 W	7.3	30.0% / 27.5%	6.7% / 7.5%	3.6% / 8.1%	4.0 / 3.4	37.5% / 37.5%	10.4% / 18.8%	5.5 / 3.8	78 / 56	41.1% / 35.7%	34.6% / 30.4%	38.8% / 24.4%	4.9 / 3.5	0.0% / 0.0%	61.5% / 28.6%	30.8 / 31.6

Jacksonville Jaguars @

New York Giants

Sun, Sep 9

10:00 AM Pacific

Game Analysis