NFL franchises use contextualized data to create competitive advantages. In order to realize an edge, teams need to employ the right data in the right way at the right time. This means distilling, interpreting and applying only the most influential data in a framework that accounts for personnel, opponents and evolving game situations. My goal is to be YOUR analytics department. Each week this season, I want to work for you by providing a peek into which numbers flag in my models as the most impactful ... or the most misunderstood.
This column will follow the format of: one trend to monitor, one news story viewed through the lens of analytics and a couple of my favorite -- or least favorite -- projections.
As always, let me know if your eye test is picking up on something interesting, or if there's a stat/trend you'd like me to take a deeper look at. You can hit me up on Twitter @CFrelund. As with any great analytics department, the more collaborative this is, the more value we can create.
Trend to watch: 3 offensive strategies paying off
We're getting really close to the four-game mark, which typically gives us enough data to get to a comfortable place with sample sizes to create profiles of team identities for the season. Each season, an offense's ability to deal with pressure is a major theme, predictor of success and important tracking metric. Winning teams cater to their personnel in order to create opportunities to exploit their opponents' deficiencies. This season, there are three main strategies that seem to be working for offenses early on. Here's what the data shows thus far, with an example of each:
- Shifts and motions. Not all pre-snap disguises and looks that throw defenses off balance are created equal. However, over the past three seasons, teams earned a passer rating that's about 14 percent higher when they use pre-snap shifts and motions compared with similar downs and distances results when they don't use them. Some teams are so adept at using these tactics that they see an even more dramatic difference. This season, the Chiefs have used pre-snap shifts and motions on 81 pass plays (third-most in the league), per Next Gen Stats. Patrick Mahomes has been pressured on 27 percent of his total dropbacks, but just 23.5 percent of the time when using shifts and motions. The Chiefs have used motion at the second-highest rate in the league (72% overall, 70% on passing downs) and average 7.1 yards per play with motion compared to 5.8 without. On passing plays, they average 8.7 yards per play when they use motion and 6.3 yards per play without. While there might not be extremely dramatic disparities between the two sets of data, these edges can be the difference between a drive ending in a field goal or a touchdown.
- Quick passes and rollouts where the QB throws on the move. Remember, the key here is to design plays and recognize situations where it's advantageous to use these tactics, not just calling for them on every passing down. NGS shows that Packers QB Aaron Rodgers has been pressured on 23.7 percent of dropbacks (ninth-lowest rate among QBs with at least 20 pass attempts). Through Week 3, 52.3 percent of his pass attempts have been quick passes (less than 2.5 seconds) and 11.4 percent have been outside the tackle box. Overall, the average pressure rate for QBs this season is 28.3 percent, but they've been pressured just 10.2 percent of the time when they've used quick passes (8.7% in Rodgers' case) and 46.6 percent of the time when throwing outside the tackle box (36.4% for Rodgers, eighth-lowest rate in the league). It's also worth noting that QBs have been under pressure on 26 percent of attempts outside the tackle box when they have a time to throw of four seconds or less, but Rodgers has faced pressure on just 20 percent of such attempts.
- Draws and screens. The Bills have run seven draw plays this season, per Pro Football Focus. That's tied for the second-most draws in the league -- only the Patriots have more with nine. On these seven rushing plays, Buffalo earned 37 yards (5.3 yards per carry). The timing of the draws can help set teams up for success, too. Looking back over eight seasons of data, first-half use of a draw play resulted in about a 22 percent greater touchdown rate on the drive it was used in. As for screens, Eagles QB Jalen Hurts has been pressured on 23.5 percent of dropbacks this season (eighth-lowest rate in the league). Philadelphia has run 21 screens this season (the most in the NFL), and he's 19-of-20 for 165 yards (8.3 yards per attempt) and a TD on those plays.
Before we move on to the next item, I just want to reiterate that the point is for offenses to find which outlets are successful to mitigate pressure based on personnel and potential. None of these tactics work every time, and they don't work equally for every team, but the teams that find their identity under pressure quickly create gains that help drive wins. It's also worth noting that these tactics will need to adapt as defenses adapt, so think of the observed trends as a starting point for success.
Trevon Diggs: Analytics show signs of breakout
With offenses passing more than ever, defensive backs are shaping game outcomes more than ever. This week alone, the Bucs signed Richard Sherman and the Panthers traded for CJ Henderson to help combat cornerback injuries. With that in mind, I thought it was worth looking a bit deeper at an example of how the back end and front end of defenses are working together this season (aka my homage to Cowboys CB Trevon Diggs, who's tied for the league lead in interceptions with three entering Week 4).
Thus far, Dallas is generating its lowest pressure rate (25.4%) since the start of the 2017 season, but the team is producing its lowest passer rating allowed (59.2) over that span when it does create pressure. Diggs has increased his individual win share by 31 percent in 2021 and part of what has helped drive that is the quality of the pressure up front. Faster and more effective pressure (leading to more scrambles, pocket breakdowns and checkdowns) creates more opportunities for Diggs to exploit. The other factor driving his win-share jump is that Diggs is closer to passing targets when the ball arrives (tracking at about 1.3 yards closer on average) and his hips are facing targets more often in coverage. Typically, hip direction is correlated with reaching a target faster and an increase in the rate of stopping the pass. My research suggests he's improved his game this season. Coordinator Dan Quinn's scheme and the opportunities being afforded Diggs have given him the space (literally) to realize those gains.
PROJECTION SECTION
NOTE: The figures cited below are provided by Caesars, current as of 2 p.m. ET on Friday, Oct. 1.
One Week 4 projection I like: Baltimore defeating Denver.
In 54.4 percent of my simulations for Sunday's Ravens-Broncos game in Denver, Baltimore wins. On a neutral site, the number would be 56.9 percent. There's a lot to like about the Broncos' defense, but one area that's a potential advantage for the Ravens is their ability to make impact run plays. NGS shows that the Broncos have a 12.2 percent run stuff rate (fourth-lowest in the league).
One Week 4 projection I love: Eagles QB Jalen Hurts earning more than 52.5 rushing yards against the Chiefs.
The Eagles did not leverage Hurts' rushing potential to its fullest in a Week 3 loss to the Cowboys. Looking at the box score (nine runs for 35 yards) doesn't really tell the whole story, though. Philadelphia used designed runs on just 9.4 percent of plays last week, but the play-calling forecasts to be different against a Chiefs defense that allowed Lamar Jackson to rush for 107 yards in Week 2.
One Week 4 projection I don't like: Vikings QB Kirk Cousins passing for more than 281.5 yards against the Browns.
This isn't meant to be a knock on a guy who's averaging 306 passing yards per game and completing 73.9 percent of his attempts. This is my model suggesting that facing Cleveland's secondary, which will likely finish the season among the top three in the league by win share, will limit deep gashes and hold Cousins to a more moderate stat line.
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