NFL Data Deep Dive: Opportunity, Efficiency, Target Share + Top Stacks for Week 6

The NFL Data Deep Dive goes beyond the box score, looking into the advanced metrics you need to know in order to make informed fantasy football decisions. After games wrap each week, Matt Savoca shows a look behind the curtain to his process, delivering the visualizations and proprietary statistics along with some quick-hitter thoughts that he uses to prepare for his weekly Main Slate Matchups column, published every Thursday, right here on Awesemo.com. Let’s dig into the data from Week 5 as we look ahead to Week 6 of the fantasy football season and NFL DFS slates.

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Team Efficiency (Click Graph to Enlarge)

The above two charts are two measures of team efficiency. The left chart measures offensive per-drive ability on the Y-axis and defensive per-drive ability on the X-axis. The right chart measures per-play ability. Both graphs use the expected points model popularized by the nflfastR data package.
  • The Colts are underperforming relative to expectation. Part of this is the inefficient play of the offense. They rank in the bottom third of the league in offensive expected points added per play.
  • Cardinals continue to outplay their expectation. Playing the Jets will do that, though.
  • Steelers entering the upper echelon of teams in terms of per-play offensive efficiency. The defense is elite.
  • The Rams are allowed to run all they want, and play as slow as they want, if they’re going to be this efficient.
  • The Packers are rested and for real, but don’t sleep on the Bears. Both teams have elite defenses on a per-play basis.
  • The Eagles offense is actually outplaying its per-drive expectation — which is good, since it is worst in the NFL.
  • The 49ers are regressing significantly year over year on both sides of the ball.

Team Aggressiveness (Click Graph to Enlarge)

The above chart measures team aggressiveness. The X-axis is Air Yards per second (Air Yards per Play/Seconds per Play) as a measure of pace and deep passing aggressiveness. True Neutral Early-Down Pass Rate (Y-axis) measures the number of times a team chooses to pass the ball on first or second down while within one possession. The raw number is fitted to its historical mean by using empirical Bayes estimation. This chart updates on Wednesdays when FootballOutsiders updates their pace data.
  • Russell Wilson is running the coolest offense in the league. Numbers are slightly skewed by late-game numbers, i.e. Wilson’s game winning drive win Week 5.
  • Joe Burrow and the Bengals are, literally, Chiefs-level aggressive. The outlook looks strong for both Tyler Boyd and Tee Higgins, both this season and long-term.
  • The season-ending injury to Dak Prescott shouldn’t affect the Cowboys’ aggressiveness all that much, but it could certainly affect the efficiency of play.
  • Philadelphia is doing the least with the most this season. They’re hideously inefficient but remain one of the least conservative teams in the league. The injuries to wideouts, along with Zach Ertz‘s inability to separate as he has in previous years, have clearly taken their toll.
  • The Raiders are certainly picking their moments to be aggressive, but the splits with Henry Ruggs on and off the field are encouraging.
  • The Vikings now the least pass-happy team in the league. Kirk Cousins is relatively efficient, but touchdowns are needed by fantasy players on this offense to have big days.
  • The Rams are more pass-happy than they were to begin the season.

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Quarterback Efficiency (Click Graph to Enlarge)

This graphic measures quarterback efficiency in terms of their ability to use their given drives to consistently score points. True Drive Success (Y-axis) rate uses empirical Bayes estimation to create a fitted version of raw drive success rate, which is raw scoring drives divided by total offensive drives. Expected Points Added per drive (X-axis) is a measure of a player’s ability to provide more (or less) than the expected points, based on nflfastR’s expected points model, on a given set of plays. It is normalized to a value between zero (worst) and one (best). This graphic measures quarterback efficiency in terms of their ability to use their given drives to consistently score points. True Drive Success (Y-axis) rate uses empirical Bayes estimation to create a fitted version of raw drive success rate, which is raw scoring drives divided by total offensive drives. Expected Points Added per drive (X-axis) is a measure of a player’s ability to provide more (or less) than the expected points, based on nflfastR’s expected points model, on a given set of plays. It is normalized to a value between zero (worst) and one (best).
  • Jared Goff and Sean McVay are at it again, though numbers look particularly good after two weeks of playing against the Giants and Washington.
  • Aaron Rodgers or Russell Wilson would be the MVP if the season ended today
  • Patrick Mahomes is still playing at a high level despite the relatively inefficient play of the Chiefs over the last few weeks.
  • Ben Roethlisberger‘s making a case for Comeback Player of the Year
  • Prescott’s injury stings so much because he had rounded the corner into elite status. He was playing like a quarterback who gets paid Mahomes/Deshaun Watson-level money, just like he was asking for. I can’t think of an athlete I’m rooting for more in 2021 than Prescott.
  • Jimmy Garoppolo was a mess on Sunday, but has still been relatively efficient on a per-play basis overall. I don’t think the team is lying when they’re saying the ankle injury continues to be a major factor in sitting Garoppolo.
  • Tom Brady is struggling. The names he’s surrounded by (Nick Foles, Carson Wentz, Matt Ryan, C.J. Beathard, Matthew Stafford) on this chart are disheartening.
  • Joe Flacco outplayed Sam Darnold in a one-game sample, but not by much. They’re only outdone, in terms of team inefficiency, by Daniel Jones and the Giants.

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Skill-Player Opportunities for NFL DFS (Click Graph to Enlarge)

NFL DFS
True Weighted Opportunity Share is a variant of Weighted Opportunity Rating, a metric created by 538’s Josh Hermsmeyer to combine a player’s share of team targets and share of team air yards into a single metric. True Weighted Opportunity share uses empirical Bayes estimation to estimate a player’s ‘true’ target share, based on the team’s sample of targets, and a player’s ‘true’ air yard share, based on the team’s sample size of air yards. As the season progresses, the error bars, which represent the 95% credible interval for the metric, will shrink, indicating the more certainty in the model. Raw weighted opportunity rating is indicated by the red dots.

High-Value Opportunities (Click Graph to Enlarge)

NFL DFS
Quality Opportunities and Quality Opportunity Share are measures of high-value usage for fantasy football. A target, on average, is worth significantly more than a non-goal-line rush in any type of scoring system that uses point per reception, so Quality Opportunities combine targets and goal-line rushes into one high-upside opportunity metric. An advanced version of the metric also includes light-front carries and only on-target (catchable) targets. The chart will be updated as the data becomes available. True Quality Opportunity Share measures the player’s percentage of team Quality Opportunities and fits it to a historical mean using empirical Bayes estimation.

Condensed Passing Offenses for NFL DFS Stacks (Click Graph to Enlarge)

NFL DFS
The condensed offenses chart uses True Weighted Opportunity Share (see above) to find passing attacks that are focused on distributing significant pass volume to their top two or three play makers. The width of the bars represents each team’s relative pass volume, measured by comparing raw passes per game and raw air yards per game. Wider bars represent higher-volume pass offenses. When used in tandem with identifying fantasy-friendly future game scripts, the condensed offenses chart can help fantasy football players make informed decisions about theoretical variations in volume or receiver stacks to target. As an example using the chart above, a lineup with Adam Thielen should expect to capture roughly 33% of the Vikings’ passing game. Alternatively, if one were to predict that Thielen to see less volume than he did in previous weeks, according to this chart the next reasonable assertion would be that Justin Jefferson (using the bar chart on the left) and then Irv Smith (using the bar chart on the right) would be in line to receive a bulk of that opportunity.
  • Jacksonville spreads the ball out more than any other team, and they’re one of the lowest-volume pass offenses. Playing Gardner Minshew on his own in NFL DFS might be smarter than focusing on top options.
  • The same goes for the other Florida teams; the Buccaneers and Dolphins are both bottom five in passing game consolidation.
  • Pittsburgh’s introduction of Chase Claypool in recent weeks skews their metric towards the bottom. They should be closer to the middle over the next few weeks.
  • Justin Jefferson is doing his best Stefon Diggs impression, at least in terms of percentage share of the team’s weighted opportunity. He has very similar WOPR metrics to Diggs in 2019.
  • Baltimore’s pass offense is much more consolidated around their top two pass catchers (Mark Andrews, Marquise Brown) than in recent years.

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Bell Cow Backs (Click Graph to Enlarge)

NFL DFS
The final chart is a measure of running back effectiveness over usage-time (total touches). Any players who appear above the blue shaded area are outperforming the historical trendline for the position, while players below the line are underperforming compared to their historical counterparts. Each season, only a few backs emerge from the pack and shift towards the top-right of the chart. These backs should be considered the true “workhorse” NFL backs and can be used as a starting point for identifying cash-game “locks” at the running back position.
  • Josh Jacobs continues to lead the league in touches, though Jon Gruden has hinted at limiting Jacobs’ workload and getting Devontae Booker more run in the coming weeks. I’ll believe it when I see it.
  • Dalvin Cook will be severely missed if he misses even just one week due to a groin strain in Week 5. To the extent running backs matter toward winning, Cook is one of them that does.
  • The upper-tier has a new face (for 2020) that should be familiar — Todd Gurley. He’s now above the historical trendline for avoided tackles. He’s playing well in Atlanta for a struggling team.
  • La’Mical Perine and Le’Veon Bell have legitimate gripes with their coach (update: Gase won the gripe-war against Bell and Bell got booted from the Jets after this article’s submission). Frank Gore has not been efficient on his touches by any means, and yet remains the focal point of the Jets’  backfield.
  • Justin Jackson did a decent enough Austin Ekeler impression for the Chargers in Week 5. He’s ascended above the trendline as his touch count continues to increase.
  • Jordan Wilkins has been the most efficient Colts back on a per-touch basis.

PFF Grade Net Advantages (Click Graph to Enlarge)

NFL DFS
The PFF Net Advantage Chart measures personnel matchups with distinct advantages or disadvantages versus their upcoming opponent. Each graph represents a distinct “phase” of the game for which PFF grades teams. The “Net Advantage” is a comparison scaled version of each team grade to their opponent’s comparable scaled defensive grade. As an example, “Pass Block Advantage” is calculated by determining the difference between an Offense’s team pass-block grade versus their opponent’s defensive pass-rush grade. Overall Advantage is a comparison of a team’s overall grade versus their opponent’s overall grade. “Composite Advantage” is a weighted combination of all other advantages, with greater weight given towards passing advantages. Only advantages/disadvantages with a standard deviation above 1, or below -1 are shown. All non-pictured personnel matchups can be considered a toss-up. These grades do not account for injuries.
  • It’s not safe to trust the Cowboys’ No. 1-ranked composite advantage with a new quarterback under center for the rest of the season.
  • Miami should roast the Jets in the passing game. It could be another good week to look at Ryan Fitzpatrick in NFL DFS.
  • The Vikings have an implied total of 30 points this week against a middling Falcons defense who can’t stop anybody.
  • Regardless of their starting quarterback, Washington should have a legitimate chance to win against the lowly division rival Giants due to their ferocious defense.
  • Things don’t look nearly as rosy for Carolina as they did a week ago versus the Falcons. It’s going to be tough to trust Teddy Bridgewater, Mike Davis or any of the Panthers’ pass catchers against a staunch Bears squad in Week 6.

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Author
A middling athlete who was offered his first sports analytics position at age 14, I've been working on NFL and fantasy football data science since 2017. With a particular passion for data visualization and dashboard building, I love to make data accessible by using graphs and charts to communicate ideas that are difficult to explain with words alone. You can contact me by e-mailing [email protected].

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