Week 9 Data Deep Dive: NFL DFS Opportunity, Efficiency, Target Share + Top Stacks

The Week 9 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 8 as we look ahead to Week 9 of the daily fantasy football season and NFL DFS slates.

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The NFL DFS Data Deep Dive for Week 9

Team Efficiency (Click Graph to Enlarge)

nfl dfs
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.
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  • Only one team ranks above average in all four charted categories (Defensive EPA/Play and EP/Drive, Offensive EPA/Play and EP/Drive): The Kansas City Chiefs.
  • At the very least, the grossest first-place team in the NFL (the Philadelphia Eagles) has an above average offense. Despite all their injuries, the Eagles still rate above average in defensive expected points per drive and defensive expected points added per play.
  • Regardless of a lackluster performance on Monday Night Football against the Giants, the Buccaneers seem poised to become the most efficient team in the NFC. Their offense isn’t as efficient on a per-drive basis, as their defense, however.
  • Teams these charts suggest you shouldn’t sleep-on in the second half of the season: The Saints, Bengals, Rams and Dolphins. Yes, the Dolphins could absolutely make a run at a playoff spot. The Bengals are likely a year away, though, especially in the ruthless AFC North.
  • Jacksonville is slipping into “Jets-only” territory on the chart on the right. The switch to quarterback Jake Luton probably isn’t going to help the dreadful offensive efficiency numbers.

Team Aggressiveness (Click Graph to Enlarge)

nfl dfs
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.
  • Teams that are above average in both early-down air yards per second of play (the x-axis) and true early-down pass rate (y-axis) have a win percentage of .645 this season. Teams above the trendline (shaded area in blue) are a combined 21-2 (.913 win percentage).
  • Even without Chris Godwin, the Buccaneers are calling early-down runs a bit too often. At least they’re throwing deep when they do decide to throw in neutral situations.
  • The Panthers and Texans should consider throwing deeper on their early-down throws to increase their efficiency.
  • The Vikings aren’t aggressive by any means, but they’ve been efficient on their attempts. In spite of a poor showing in this chart, they’re first in the league in yards per pass attempt. Another way of reading this is: If you aren’t aggressive, you need tremendous efficiency to remain successful.
  • It’s Russell Wilson’s MVP race to lose, simple as that.
  • Justin Herbert continues to transform the Chargers into a sneakily aggressive team despite the team’s attachment to early-down runs.

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Quarterback Efficiency (Click Graph to Enlarge)

nfl dfs
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).
  • Welcome to the “Jets Zone,” Ben DiNucci. It wasn’t a pretty first start for the late-round rookie.
  • Yes, Nick Mullens is vastly outplaying Jimmy Garoppolo on a per-play basis this season. The switch at quarterback shouldn’t be too terrible for San Francisco. The loss of George Kittle is definitely, definitely terrible, however.
  • Kirk Cousins has had a marked improvement in the second quarter of the 2020 season. He’s among the league’s elite passers in both metrics.
  • Tua Tagovailoa needs to finish his drives with touchdowns, but his expected points added per play is highly encouraging after one start, especially against a Rams’ squad that ranks well above average in defensive expected points per drive and expected points added per play.
  • Drew Lock’s comeback against the Chargers in week 8 was certainly epic, but he’s still firmly in the “career backup” zone, along with fellow opening-day starters Sam Darnold and Daniel Jones.

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

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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.
  • The Seahawks receivers keep flip-flopping. After Tyler Lockett stole the show in week 7, D.K. Metcalf took over in week 8 with an outstanding performance, and a re-taking of the team lead in true weighted opportunity share. He ranks ninth in the NFL in the metric.
  • Travis Fulgham is the best thing that happened to the Eagles in a long time, now ranking 16th in the NFL and third in the NFC East in true weighted opportunity share.
  • Cooper Kupp’s 21-target day has still light on the air yards, which means he’s still in the 20s among receivers in this metric. It wasn’t nearly the same boost as Keenan Allen’s 19-target game in week 3.
  • Marquise Brown seems to have a decent reason to be miffed about his production, his on-field output doesn’t match the top-10 true weighted opportunity share he’s seen this season.
  • Expect T.J. Hockenson to see a massive amount of the Lions’ targets and air yards while Kenny Golladay misses time. The circumstances are less than ideal, but the breakout is underway in Detroit.
  • Not that they had much of a chance Sunday against the Chiefs, but the Jets desperately miss Jamison Crowder when he’s unavailable. The offense can’t function whatsoever without him.
  • Jakobi Meyers is a new entrance to the chart, he slides in right next to Julio Jones (whose numbers are deflated in this metric due to Calvin Ridley’s massive air yards share) after commanding nearly 25% of the Patriots’ passing volume during their week 8 loss.

NFL DFS High-Value Opportunities (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.
  • Your true quality opportunity kings are Davante Adams and Alvin Kamara. Adams completely outpaces the rest of the league in quality opportunity share, whereas Kamara is a running back used similarly to a primary wide receiver in terms of usage. Stefon Diggs, first in total quality opportunities, is arguably in the midst of his finest season yet.
  • The 49ers loss of Kittle is likely the nail in the coffin to a season lost to injuries. Brandon Aiyuk is the likely target leader from here on out.
  • Kupp has crept into the top-10 in both charts, which tends to happen after a 20-target game.
  • The primary wide receiver in Tennessee, in spite of the continued efficiency of A.J. Brown, is fourth-year receiver Corey Davis, who’s healthy and has finally clicked with quarterback Ryan Tannehill.

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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.
  • Three two-player stacks are beginning to pull away from the pack in terms of usage and value: Carolina, Minnesota and Seattle. When considering raw pass volume (thickness of the bar), it’s apparent that the Seahawks’ dynamic duo at receiver is by far the best in the NFL this year.
  • With Crowder still sidelined, Jeff Smith saw a top-five weighted opportunity in week 8. It didn’t result in a huge stat line, but the usage was top-notch on the fledgling Jets offense.
  • Curtis Samuel enters the Panthers’ top-three stack (chart on the right), passing Mike Davis in usage in the week before Christian McCaffrey’s return.
  • It will be interesting to see if Marquez Valdes-Scantling’s heavy usage alongside Adams when Allen Lazard returns. Lazard has begun practicing and could soon re-enter the fray, along with running back Aaron Jones, when the Packers play Thursday night.
  • Only six teams have two-player stacks (of active players) that receive less than 40% of the teams’ true weighted opportunity: The Steelers, Jaguars, Browns, Buccaneers, Dolphins and Colts.

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NFL DFS Bell Cow Backs (Click Graph to Enlarge)

fantasy football
The RB elusivness 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 his quietly fantastic season, making the most of the poor conditions in Cleveland and ranking second in the league in touches in week 8 with 31.
  • Dalvin Cook was the only other back besides Jacobs to receive more than 30 touches last week, and he broke the week 8 slate with four touchdowns in the Vikings’ surprise victory over the Packers.
  • Darrell Henderson hasn’t been spectacular on his 100-plus touches, but he has been right in line with the historical trendline. If he misses time, it’d be advantageous for the Rams to give more touches to Cam Akers, who’s the only Rams back to rank above-average in avoided touches based on their touch total.
  • Jonathan Taylor is about nine avoided tackles short of expectation (based on the last five years of data), which is alarming and unexpected based on his college profile. Jordan Wilkins is the only Colts back with 50-plus touches who ranks has an avoided tackle total above historical expectation.
  • The Ravens need to feed J.K. Dobbins — it’s that simple. He’s lapping his teammates in terms of avoided tackles. Gus Edwards continues to be more involved, particularly at the goal line, than Dobbins’ fans would like, however.
  • With the advantage of a full workload, David Montgomery has proven himself a worth primary back, clumped with Cook and Kareem Hunt in the upper-right of the chart.

PFF Grade Net Advantages (Click Graph to Enlarge)

DraftKings
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 looking like Seahawks, Vikings and Chiefs passing stacks will be extremely viable in week 9. All have consolidated passing offenses and plus matchups in week 9.
  • The Texans’ matchup also looks great on paper, facing a rookie quarterback on defense and possessing a litany of offensive advantages versus the struggling Jaguars defense.
  • Chase Edmonds appears to be set up nicely in week 9 against the Dolphins, with Kenyan Drake set to miss at least this week with a mid foot sprain. The Cardinals have the second best net run advantage on the main slate.
  • The Washington defensive line looks like it might be the defining force in the (ugly) divisional matchup against the middling Giants this weekend. The Titans also appear to have a clear advantage of the Bears’ banged up offensive line.
  • With the Chargers’ trading defensive back Desmond King, and the Raiders ranking top on the slate in net receiver advantage (offensive receiving grade versus defensive coverage grade), could we see a shootout in the Raiders – Chargers showdown during the afternoon slate? The numbers say it’s certainly possible.
  • Even the struggling Patriots should wallop the Jets in week 9. Unsurprisingly, the Patriots, in spite of their highly mediocre play since Cam Newton’s return, they’re ranked second in net overall advantage. Expect them to run it down their division rivals’ throats.

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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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