Week 16 NFL DFS + Fantasy Football Matchups Breakdown Column With Matt Savoca

(43) Indianapolis Colts (20.5) @ Pittsburgh Steelers (22.5)

All Graphs Reflect Last Five Weeks of Data, Click Graphs to Enlarge

Team Passing and Pace

First, let’s take a look at the possibility of this game turning into a shootout, as teams that play faster and pass more than average tend to score more fantasy points. When both teams play aggressively, it often creates a game environment perfect for fantasy scoring. Games have a higher probability of going over their Vegas total as well. Ideally, we’re seeking matchups where both teams are in the upper-right quadrant of the chart below (see the chart’s caption for more details).

The X-axis is Early-Down Air Yards divided by team game-script-adjusted plays per second (using Awesemo’s Game-Adjusted Pace from the Advanced Stats Page). The Y-axis is True Neutral Early-Down Pass Rate, a key indicator of a team’s desire to have a pass-oriented game script. The matchup-specific teams’ logos are displayed amongst all other teams in order to contextualize team pace and passing versus league averages (the dotted lines on the chart).

While the Steelers remain as committed to the passing attack as any team in the NFL, if their quarterback can’t deliver the ball accurately in the passing game, the fast-paced and the pass-happy nature of the offense is all for naught. With Indianapolis leaning slightly run-heavy but throwing more air yards per second of play compared to NFL averages, this game absolutely has shootout potential, but the ranges of outcomes for each team, from a scoring standpoint, are extremely wide.

Recent Quarterback Performance

Next, let’s examine the starting quarterbacks’ recent play. Sustained drives in the NFL rely on efficiency at the quarterback position, so I’ve identified my three favorite performance indicators for assessing quarterback performance. The three bar charts below (see the graph’s caption for more detail) represent a quarterback’s per-drive efficiency (left bar-chart), per-play efficiency including rushes/scrambles (center) and per-pass efficiency (right). Higher rankings from both players indicate a higher likelihood of efficient play, thus a higher probability of fantasy points.

The three columns represent my three primary performance indicators for quarterbacks. Furthest left (tDSR) is True Drive Success Rate, a drive-based efficiency metric that measures a quarterback’s ability to turn drives into touchdowns, regressed based on sample size. The middle column, Expected Points Added (EPA), is a measure of per-play efficiency and includes scrambles and designed runs. Finally, on the right is per-pass efficiency, Completion Percentage Over Expectation (CPOE) based on the publicly available completion percentage model included in the NFLFastR package.

The two quarterbacks in this matchup are moving in completely opposite directions, with Philip Rivers enjoying the best five-game stretch of his 2020 season, ranking top-3 in both per-drive and per-play efficiency. Ben Roethlisberger‘s playing at the level of an NFL backup in this five-week stretch, raising concerns about the health of his surgically-repaired elbow, as well as his viability as the Steelers’ starting quarterback in 2021.

NFL DFS Player Pool Picker: Upside Analysis

Now, let’s examine the primary skill players from each offense. Unless participating in a large-field tournament, these are the players you should be focusing on in your daily fantasy football lineups. For each player, I’ve made it easy to compare their per-game fantasy (in column 3) to their DraftKings main slate salary ranking (in column 2). Column 4 ranks the player using my favorite position-specific volume metric: Expected fantasy points, which is curated by PFF.  The Defense vs. Position column is an extremely helpful position-specific and player-group specific (for example, the metric delineates between primary wide receiver vs. secondary wide receivers) metric that helps determine if an offensive player is likely to be in a position to exceed their expected fantasy points. Higher numbers in the Defense vs. Position column indicate easier matchups for the offense, while numbers closer to one indicate a stout defense against that specific position-group.

The final column, Expected Projection, combines a player’s expected fantasy points with their weekly matchup into one helpful value metric. Apart from the Awesemo projections (which should still carry the most weight in determining player value), Expected Projection is one of my favorite metrics to help me narrow down my favorite plays of the week. The rankings are always specific to the slate, meaning if a player or team is ranked No. 1 at a specific metric, they may not necessarily be ranked No. 1 in the NFL, but they are for this specific slate.

Indianapolis Colts NFL DFS Core Offenses

Team Player Positional Salary Rank FPTs/Gm Rank Expected FPTs/Gm Rank Defense vs. Position Expected Projection
IND Philip Rivers, QB #12 #9 #25 #4 11.5 Fpts (QB18)
IND Jonathan Taylor, RB #4 #3 #10 #11 13 Fpts (RB7)
IND T.Y. Hilton, WR #19 #10 #24 #18 14 Fpts (WR12)
IND Nyheim Hines, RB #22 #7 #15 #11 12 Fpts (RB14)
IND Michael Pittman Jr., WR #36 #37 #59 #11 9 Fpts (WR39)
IND Zach Pascal, WR #44 #39 #67 #2 8.5 Fpts (WR44)

Despite several strong outings in a row, Jonathan Taylor‘s fourth-highest salary among running backs appears touch to pay-up for this weekend, especially with the Steelers ranking in the top-12 against running backs over the last five weeks. With Nyheim Hines seemingly relegated to a part-time role in recent weeks, T.Y. Hilton, the 19th highest-salary wideout on the slate, seems like the safest bet on the Colts side of the ball.

Pittsburgh Steelers NFL DFS Core Offenses

Team Player Positional Salary Rank FPTs/Gm Rank Expected FPTs/Gm Rank Defense vs. Position Expected Projection
PIT Ben Roethlisberger, QB #7 #8 #10 #14 16.5 Fpts (QB12)
PIT Diontae Johnson, WR #12 #15 #15 #20 15 Fpts (WR10)
PIT JuJu Smith-Schuster, WR #14 #14 #22 #14 14 Fpts (WR12)
PIT Chase Claypool, WR #15 #29 #34 #21 12 Fpts (WR22)
PIT Eric Ebron, TE #7 #8 #11 #7 6.5 Fpts (TE15)
PIT James Conner, RB #16 #26 #40 #28 7.5 Fpts (RB25)

Is the Steelers offense a full fade right now? With expected projections that rank well-below salary-based expectations across the board, almost every Steelers skill-position player seems like a thin-play this Sunday. None of the Steelers’ big-three receivers, nor Eric Ebron (who may miss this game with a back injury) stand-out as valuable plays based on the chart above.

NFL DFS Backfield Values: Running Back Opportunities

Nailing the running back position in your fantasy football lineups is vitally important. There are many metrics that help fantasy gamers determine which running backs earn higher-value touches than their peers, but my favorite is Quality Opportunities per game. It only counts running back looks that come via the receiving game (as receptions are much more valuable on a per-play basis than rushes) or via goal line rushes (inside the opponent’s 10-yard line) since there isn’t anything more valuable than a touchdown.

 

This chart measures Quality Opportunities per Game (targets or goal line carries) and its variant, Quality Opportunity Share, which are both key performance indicators for running backs. This metric helps filter so-called “empty touches” from a running back’s workload and highlights the opportunities that are most likely to be successful for fantasy football. It includes injured players in order to help contextualize players who might be receiving a smaller or larger workload based on personnel shifts.

While Nyheim Hines continues to have “hidden” value due to his unique usage, Jonathan Taylor is now receiving nearly the same number of high-value looks on a per-game basis compared to his receiving-specialist teammate. The Steelers haven’t been able to generate any consistent offense with their ground attack (though Snell had a strong second half against the Bengals in Week 15), and with Conner likely returning this weekend, none of the Steelers’ backs appear particularly appealing this week.

NFL DFS Receiving Values: Skill Position Opportunity Ranges

The wide receiver and tight end positions are two of the higher-variance positions in all of daily fantasy football, so it’s important to consider both floor and ceiling when predicting a player’s usage. Players with unexpectedly high opportunity in the passing game often have the best chances to outperform their projections, so I created a chart that measures a player’s opportunity range of outcomes (see the caption of the graph for more details on how this is calculated.). The horizontal bars represent a player’s expected opportunity range, while the center dot represents their average opportunity.

This chart measures the mathematical uncertainty in each player’s true weighted opportunity metric (the metric is explained in the caption of the Game Opportunity Chart above), providing an insight into a player’s range of outcomes related to receiving opportunity. For each player, the team-color dot is the “true” metric, while the red dot indicates the “observed” stat. The bars represent a player’s 95% credible interval, which we can use to measure the uncertainty (both positive and negative) related to their expected workload through the air.

Diontae Johnson, T.Y. Hilton, and Chase Claypool appear to have the highest opportunity upside at the receiver position, while Eric Ebron, assuming he plays, has considerably more upside than any other non-wideout in this matchup. The Colts spread-out their passing attack more than any other team in the NFL, but Hilton has aimed to change that over the last five weeks.

NFL DFS Auxiliary Offensive Players for Large-Field Contests

In daily fantasy football, depending on the size and type of contest you’re playing, it’s often advantageous to expand your player pool to less-utilized offensive players. In this section, we examine every part-time player’s usage based on playing time, opportunity and (again) defensive matchup. For each player, I create an Opportunity Score, which scales a position-specific opportunity metric between zero (least valuable) and 100 (most valuable). Scores above 50 tend to indicate starter-level opportunity, while scores over 80 indicate star-level usage. Finally, I categorize the players as an NFL DFS value, a mass multi-entry option (MME-only) or a player to avoid altogether.

Indianapolis Colts NFL DFS Tournament Picks

Team Player Snap Share Opportunity Score Defense vs. Position Outlook: Value, MME-only, Look Elsewhere
IND Trey Burton, TE 41% 78 #13 MME-only
IND Mo Alie-Cox, TE 51% 62 #13 Look Elsewhere
IND Jack Doyle, TE 53% 32 #13 Look Elsewhere
IND Ashton Dulin, WR 10% 1 #2 Look Elsewhere
IND Marcus Johnson, WR 36% 44 #2 Look Elsewhere

Pittsburgh Steelers NFL DFS Tournament Picks

Team Player Snap Share Opportunity Score Defense vs. Position Outlook: Value, MME-only, Look Elsewhere
PIT James Washington, WR 39% 27 #21 MME-only
PIT Benny Snell, RB 30% 85 #28 Look Elsewhere
PIT Jaylen Samuels, RB 18% 46 #28 Look Elsewhere
PIT Vance McDonald, TE 46% 3 #7 Look Elsewhere

James Washington and Trey Burton are viable in large-field tournament lineups building around the possibility this game being a shootout, but besides that, the second and third options (fourth in the Steelers’ case) aren’t that exciting in a game where each team’s defense has a chance to dominate the opposing offense.

Final Thoughts

With the Colts content spreading the ball to five different weapons on offense and the Steelers playing their worst football all season, players from this game will likely be somewhat unpopular, making contrarian game stacks centered around either offense somewhat viable. Though this game features plenty of offensive potential,  with both defenses playing at playoff-caliber levels, neither teams’ skill-position players stand out as value-plays this weekend.

Prediction: Colts 27, Steelers 26


Looking for more NFL DFS picks and daily fantasy football matchups content? We have loads of articles, data and more on the Awesemo NFL home page. Just click HERE.

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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