2016 QB Projections – AFC South & NFC South

2016 QB Projections – AFC South & NFC South

Introduction

If you have landed here directly, I encourage you to read the first part of the series (projecting the AFC North and NFC North). … In the first part of this series I discuss my projection methodology and define the metrics used to measure team performance.

Now, to the fantasy QB projections for the South divisions!


AFC South

Houston Texans

  o.snapsgmspa.drpbkpa.skpa.ydpa.tdpa.intru.attru.yd fpt.4ptfpt.6pt
HOU.QBTMTeam1090.016.0596.848.53776.525.517.635.2110.1233.7284.7
HOU.QB1Brock Osweiler1021.915.0562.046.13663.224.212.932.296.6231.9280.2
HOU.QB2Tom Savage68.11.034.72.4216.51.31.13.013.513.215.9
HOU.QB3

ind_sch

Houston, much like Detroit, broke their season up into two mini-seasons in 2015. In the first half of 2015, the defense put them in early (frequently huge) deficits, and their play splits are highly representative of a team playing from behind almost every offensive snap. In the first eight weeks, the Texans played nearly 86% of their offensive snaps (512) from behind or virtually tied. This will tilt most coaches away from what they’d prefer, and Bill O’Brien is no exception.

hou_split18_2015

During the second half of 2015, the team went on a defensive tear, starting with a shocking MNF upset in Cincinnati. Below you see the play splits from the back end of the season, where scripts were almost tilted 180° in their favor.

hou_split1017_2015

Based on this, I have a hard time projecting this offense – game script will create a good deal of volatility in Bill O’Brien’s playcalling. It’s clear from the above charts he will pass from behind, pass when tied, and run when ahead. The difficulty arises when deciding when each will take place, and for what percentage of offensive snaps.

Brock Osweiler limits this offense, but less so than the Menagerie of Bad QBs the Texans used last year. As a result, I’ve projected Houston similar to last year from a play profile perspective.

Indianapolis Colts

  o.snapsgmspa.drpbkpa.skpa.ydpa.tdpa.intru.attru.ydru.tdfpt.4ptfpt.6pt
IND.QBTMTeam1100.016.0666.834.14477.932.619.952.2256.12.0307.5372.6
IND.QB1Andrew Luck1031.315.0629.131.54243.031.520.950.3251.42.0290.9353.8
IND.QB2Scott Tolzien65.01.037.72.6234.91.10.81.94.80.013.015.2
IND.QB3

ind_sch

After seeing the Vontae Davis injury news, I had to go and adjust an already high Pass % even higher, and add more inefficiency. Las Vegas projects the Colts to win nine games, but I don’t see how that will be possible given the perennially putrid OL and funnel pass defense Ryan Grigson puts on the field year, after year, after year, after year.

ind_split1h_18
ind_split1h_1017Indianapolis actually improved from a game script perspective once Andrew Luck was abandoned for the season. It’s quite possible this team could spiral to a 1-5 or 2-4 start right out of the gate, and never fully recover until some feel-good wins at the end of the season to limp to 7-9.

ind_split2h_18
ind_split2h_1017

Even with a lead late in the game, Rob Chudzinzki prefers to lean on his QB and calls a very pass-heavy, TE-friendly script. Whether that’s Andrew Luck, Scott Tolzien, or the re-animated carcass of Matt Hasselbeck remains to be seen. Whatever the case, I expect plenty of TDs and INTs from Andrew Luck if he manages to stay upright all season.

Jacksonville Jaguars

  o.snapsgmspa.drpbkpa.skpa.ydpa.tdpa.intru.attru.ydru.tdfpt.4ptfpt.6pt
JAC.QBTMTeam1040.016.0603.242.24039.027.115.154.6245.71.1271.0325.3
JAC.QB1Blake Bortles1040.016.0603.242.24039.027.115.154.6245.71.1271.0325.3
JAC.QB2Chad Henne
JAC.QB3

jac_sch

We’ve read all spring and summer about how much Jacksonville inflated their passing statistics by being behind in the second half (particularly the fourth quarter) and making the box score look pretty at the end with a couple of late-game passing TDs. Let’s see what that looks like:

jac_split3q_2015
jac_split4q_2015

The data backs up what we saw on the field. This team ran so few plays with a positive game script (31st in Points Against – 448; 4.78 Point Different Per Offensive Snap) in 2015 that it’s incredibly difficult to know what we’ll get in 2016. The small slivers we have in the plots above indicate they will remain pass heavy, but perhaps more in the realm of 52-56%. That makes sense, given the receiving weapons surrounding Blake Bortles.

I expect the offense will slow their pace as they play with leads and kill clock with Chris Ivory and T.J. Yeldon. I believe that will lead to improved efficiency from Bortles, and that his Dropbacks, Sack Rate, and INT Rate all decrease in line with a QB who plays with a lead some of the time.

Tennessee Titans

  o.snapsgmspa.drpbkpa.skpa.ydpa.tdpa.intru.attru.ydru.tdfpt.4ptfpt.6pt
TEN.QBTMTeam1010.016.0525.236.83712.123.612.248.5290.92.4262.2309.5
TEN.QB1Marcus Mariota1010.016.0525.236.83712.123.612.248.5290.92.4262.2309.5
TEN.QB2Matt Cassel
TEN.QB3

sch_ten

So far, against vanilla defensive schemes, “Exotic Smashmouth” has looked to take the league by storm. I want to temper my enthusiasm, but the plus plays I see from Marcus Mariota, Derrick Henry, and Tajae Sharpe this preseason make it difficult to do so.

The Titans spent most of 2015 playing from behind, averaging a 6.26 point deficit for every offensive snap (31st). The play split reflected this, with Tennessee logging heavy pass volume after the first quarter throughout the season. You can see this visualized below.

ten_split_2015
ten_split1h_2015

To get some clarity on what they might try to do from a passing perspective this season, I had to isolate the first quarter play splits. I can’t say I was surprised in the least.

ten_split1q_2015

The snap volume and pace (reflected in the 18.4% of offensive snaps) indicate Mike Mularkey will be content to eat play clock with a run-heavy scheme, and pass judiciously. In the first quarter, Tennessee averaged 33.7 sec per pass play, and 37.5 sec per rush play.

While this may limit volume of the Titan passing game, they’ll look to make up for it with play-action deep passes that boost yards-per-attempt. Marcus Mariota exhibited an excellent attempt average for a rookie, posting 7.6 YPA in just over ten games worth of play time. Additionally, he finished eighth in Points Per Dropback (200+ dropbacks).

Another positive I see for Mariota is that his surrounding cast improved by leaps and bounds over the offseason, with the additions of Rishard Matthews and Tajae Sharpe. Each should immensely improve Mariota’s Catch Rate and yardage.


NFC South

Atlanta Falcons

  o.snapsgmspa.drpbkpa.skpa.ydpa.tdpa.intru.attru.ydru.tdfpt.4ptfpt.6pt
ATL.QBTMTeam1090.016.0654.039.24487.729.417.232.765.40.8274.2333.1
ATL.QB1Matt Ryan1090.016.0654.039.24487.726.217.232.765.40.8261.2313.5
ATL.QB2
ATL.QB3

atl_sch

The more I watch this preseason, the more concerned I become with Matt Ryan as a steady-eddie play at his ADP. Perhaps he’s been asked to make riskier throws as a practice, but I see a QB that is making poor decisions – it’s possible he’s not seeing the defense as well as he once did. He tends to throw INTs in close games… last year alone, 10 of his 16 interceptions occurred with the game “in doubt” (+/- 8 pts, more than four minutes remaining in the game). He’s making mistakes when it isn’t necessary. I see it again this preseason, and it will limit his fantasy point production.

atl_split2h_2015
atl_split1h_2015

Game scripts are reasonable, and have been consistent for the last three seasons. On average, the Falcons are snapping the ball with a 2.5 point deficit, and split Pass % and Rush % in line with league norms. What you see is what you get with their play splits. This shouldn’t change in 2016.

Carolina Panthers

  o.snapsgmspa.drpbkpa.skpa.ydpa.tdpa.intru.attru.ydru.tdfpt.4ptfpt.6pt
CAR.QBTMTeam1030.016.0545.938.23909.227.312.7116.2580.97.0340.1394.7
CAR.QB1Cam Newton1030.016.0545.938.23909.227.312.7116.2580.97.0340.1394.7
CAR.QB2
CAR.QB3

car_sch

Las Vegas has set the win total at 10.5 games, which is more in line with a slightly regressing team that won three more games than their Pythagorean Expectation (15 vs. 12.1) in 2015. The biggest difference? Scoring 160 points more over the season than years prior. They scored touchdowns on 27.2% of offensive drives (1st) and punted only 36.2% of drives (5th), which is impressive for a team with 235 drives (2nd) on the season.

car_split1h_2015car_split2h_2015
car_split4q_2015

When we look at their Game Script Plots, we see they were behind so little in 2015 that it’s difficult to tell how this offense will function if they fall behind this season. Digging in a little further, we can look back at past Pythagorean Expectation for a hint on how a team might administer its offense. Since 2006, teams outputting a Pythagorean Expectation between 10 and 11 wins (in line with the 10.5 wins projected by Vegas) have averaged 413 Points For and 316 Points Against. The 53% Pass Split I’m projecting for them is approximately the 25th percentile, and a few ticks higher than last season. Cam is still well in line to finish as QB1.

New Orleans Saints

  o.snapsgmspa.drpbkpa.skpa.ydpa.tdpa.intru.attru.ydru.tdfpt.4ptfpt.6pt
NO.QBTMTeam1100.016.0671.033.65035.936.914.023.635.40.8321.4391.2
NO.QB1Drew Brees1100.016.0671.033.65035.935.414.023.635.40.8321.4391.2
NO.QB2Garrett Graham
NO.QB3

no_sch

The prevailing theme in New Orleans the past few years has been Drew Brees or Bust. Lately, they’ve busted anyway, despite his best effort, thanks to an incredibly poor pass defense that yielded 477 Points Against in 2015. The offense has been consistent the last three seasons, posting 409, 401, and 414 Points For.

no_split_2015 no_split_2014

The touchdown split has changed, perhaps philosophically, the last two seasons (80% Pass/20% Rush in 2012 & 2013, versus 67% Pass/33% Rush in 2014 & 2015). I expect that to shade back toward 72-75% this season, with improved offensive weapons around Brees. Likewise, the play splits should remain steady, as none of the foundational roles of the offense have changed since 2011.

Tampa Bay Buccaneers

  o.snapsgmspa.drpbkpa.skpa.ydpa.tdpa.intru.attru.ydru.tdfpt.4ptfpt.6pt
TB.QBTMTeam1020.016.0581.429.14252.926.212.239.5118.42.0274.2326.5
TB.QB1Jameis Winston1020.016.0581.429.14252.926.212.239.5118.42.0274.2326.5
TB.QB2Mike Glennon
TB.QB3

tb_sch

The key to Tampa Bay making any sort of leap this year will lie in their defense. In 2015, their defense yielded the seventh-most points in the league (417), placing the offense in many unfavorable scripts. You can see these scripts below. In the second halves of games, the Buccaneers ran only 22% of their offensive snaps with a lead, which makes it difficult for any offense to be two-dimensional. All told, the Bucs averaged a 4.97 point deficit for every offensive snap in 2015.

tb_split_2015

What we do see, though, is Dirk Koetter preferring to run (versus the crowd) in “game neutral” situations (51% Pass/49% Rush). I expect that to move slightly pass-heavy heading into Year 2 of Jameis Winston, but the Bucs’ financial commitment to Doug Martin this offseason sends a clear message they will give him heavy workloads early, and again if they have a second half lead.

tb_split1h_2015
tb_split2h_2015

If the defense doesn’t improve much, however, I expect to see plenty of shoot-outs.


Conclusion

That wraps up both South divisions. Next? We move onto the AFC and NFC West divisions. Stay tuned.

Josh Hornsby

Josh Hornsby leads engineering teams in the oil & gas industry. His background in new product development, combined with nearly 20 years of data-driven fantasy experience, compels him to think outside the box and wreck the echo chamber of current fantasy analysis. Josh loves to challenge popular thinking and typically does so with numbers in hand. You can find him on Twitter @FantasyADHD

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3 thoughts on “2016 QB Projections – AFC South & NFC South”

  • Great stuff… these are a huge help for separating players among tiers. Am I right in assuming the remaining divisions will be released Thursday and Friday respectively?

    Also… I’m not sure if it’s just my computer, but Osweiler/Savage’s projected statistics for ru.td, fpt.4pt, fpt.6pt total are being cut off by contributor photos.

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