Ben Gretch is the Senior Fantasy Analyst at RotoViz. He is the author of “2017 Will Not Look Like 2016 – Or Anything We’ve Seen Before” and the weekly column Stealing Signals.
For the past two seasons over at RotoViz, each week I’ve broken implied point totals down into projected passing, rushing, kicking, and D/ST points. I’m excited to bring it to FantasyLabs this season because the idea behind the article originated with a 2014 RotoViz post written by Jonathan Bales, who interviewed some top daily fantasy minds in the piece. In it, A.J. Bessette discussed a strategy for subdividing what we know as the implied total.
“Once I have the total for each team, I look at some historical scoring rates — what percentage of scoring has typically gone to each position for certain teams. So let’s say we’re looking at the Packers and the Giants, who Vegas has projected at 24 points each. By looking at historical scoring, we’d see that we should project Aaron Rodgers with more touchdowns than Eli Manning just because Green Bay scores a higher percentage of touchdowns to field goals, and Rodgers also accounts for a much higher percentage of the Packers’ scores than Manning for the Giants, even with the same projected points.”
Bessette also went on to discuss the necessity of adjusting for opponents’ rates; we need to account for the effect a team’s matchup can have on how points will be scored in a given week.
I started tracking a modified version of this idea in 2014 and found it to be helpful. I began writing the column in 2015 with promising results.
Methodology
My approach has been to focus on the team level. Nearly all real-life scoring can be classified in four buckets: Rushing, passing, kicking, and defense/special teams, which includes return touchdowns and safeties.
In this post we look at what percentage of total scoring for each offense and defense comes from each of these buckets, and then we apply those rates to implied point totals. There are two projections provided: One that applies an average of the offense’s and defense’s rates to the implied total, and another that applies the properties of standard deviation to emphasize noteworthy rates that deviate further from the mean.
One problem early in the season is that we don’t have 2017 scoring data yet and are thus limited to 2016 rates. As we work our way into 2017, I’ll weight 2016 splits less each week. For Week 1, it’s all we have, so be careful to make adjustments for coaching and personnel changes as necessary. Consult the Fantasy Football Preview Dashboard to get a sense for how these changes might impact performance on a team-to-team basis.
Next week, we’ll do a 75/25 weighting of 2016/17 and in Week 3 a 50/50 and so on. The Week 5 article will rely solely on data from the first four weeks of 2017. By nature, this method will get better throughout the season as we learn about each team’s 2017 tendencies. Until then, there are plenty of useful matchup notes to check out.
Passing Scoring and Notes
2016 League Average Passing Points Rate: 40.5 percent
Note: Lines pulled from Sports Insights on September 8th.
Pittsburgh tops the passing table in both calculation methods. Much ado is made of Ben Roethlisberger‘s home/road splits, but with Le’Veon Bell only a week removed from the end of a lengthy holdout I’m liking the upside potential for the passing game against a secondary that recently traded Joe Haden.
Roethlisberger, Antonio Brown, and Martavis Bryant are collectively expensive, but in the Models they are projected for far less ownership than Bell is. This year FantasyLabs users can review ownership trends across GPPs of various buy-in levels with the DFS Ownership Dashboard, which is reason enough to subscribe to FantasyLabs. After lineups lock, visit the DFS Contests Dashboard to see how Roethlisberger-Brown-Bryant stacks fared in terms of uniqueness. The Correlations Matrix shows that their interdependence is strong. Using Roethlisberger-wide receiver stacks as leverage on Bell is probably a sharp move. For more on Roethlisberger, see the Week 1 quarterback breakdown.
Similarly, the Arizona passing game makes for strong leverage on David Johnson. Detroit gave up a league-high 55.3 percent of points via the passing game last year, three full percentage points more than any other team. Carson Palmer and Larry Fitzgerald grade out well in many of the Pro Models. Fitz is the highest-rated receiver in the Levitan Model. For more on Fitzgerald, see the Week 1 wide receiver breakdown.
The Giants stand out as a team that has a low implied total but does well in the subdividing method. They have the second-highest rate and the opposing Cowboys conceded the fifth-highest rate of points in the passing game. If they hit their implied total of 21.75 points (per the Vegas Dashboard), it’s a good bet Eli Manning will have thrown a couple scores. Monitor the injury status of Odell Beckham with the NFL news feed. If he plays, consider stacking him with Manning via the Lineup Builder.
Rushing Scoring and Notes
2016 League Average Rushing Points Rate: 22.7 percent
The Panthers draw a 49ers defense that allowed a league-high 25 rushing touchdowns last year. The Charlotte Observer’s Scott Fowler recently suggested Jonathan Stewart would be the beneficiary of any short-yardage opportunities, and he did score nine rushing touchdowns in 2016. Of course, rookie dynamo Christian McCaffrey is also in consideration. While the boring, old Stewart is projected for less than five percent ownership, McCaffrey is expected to be chalky on DraftKings, where his receiving ability has translated into a top-10 median projection.
Devonta Freeman and Tevin Coleman combined for 24 of Atlanta’s 58 offensive touchdowns in 2016. They are road favorites in Week 1 against a Bears defense that allows rushing points at an above-average rate. Playing on the road, outside, on grass, the Falcons could prioritize the run a little more than they normally do. Assuming they approach their implied total, it’s a good bet that one or both of the backs are in on the scoring.
While LeSean McCoy should be fairly popular (even as a pivot play), the opposing running backs on the Jets should be sneaky tournament options. New York’s implied total is a putrid 16.25, but in a tournament we’re looking for high-end outcomes, and they’ve enjoyed some positive reverse line movement, as their total has increased from 15.5 even though they’re getting only 46 percent of the bets. It’s possible they could beat their total against a team that also appears to be tanking. Last year, Matt Forte and Bilal Powell combined for all 10 rushing touchdowns, and the Bills allowed a full third of their conceded points to come on the ground, the highest rate in the league.
Kicking and Defense/Special Teams Scoring and Notes
2016 League Average Kicking Points Rate: 31.5 percent
This methodology was strikingly accurate at projecting strong kickers early last year, although it waned a bit by the end of the year. Still, over 70 percent of the kicker recommendations named in these weekly articles last year scored seven or more real points over the season, not counting distance bonuses.
Dan Bailey is your top projected kicker for Week 1 based on last year’s scoring splits, with Ka’imi Fairbairn, Matt Bryant, Dustin Hopkins, and Caleb Sturgis rounding out the top five.
2016 League Average D/ST Points Rate: 5.2 percent
The D/ST table is included mostly to be transparent with all the data. Keep in mind that in my review of the 2015 data, the subdivided defense/special teams scoring projections were the only scoring type to perform worse than the betting lines, and it was notably bad. The implication is that conceding or scoring D/ST touchdowns and safeties isn’t predictive of future performance, which is useful to know, since it’s possible that some teams could have inflated over/unders and/or implied point totals if they have scored and/or conceded a high rate of points via defense/special teams.
In other words, later in the year we should fade a small degree of the implied totals for teams who grade highly here. Of course, the unleavened fade is already baked into the passing, rushing, and kicking projections in this column because those percentages are relative lower. That’s probably not actionable for Week 1, but we’ll keep an eye out for teams who score a lot of points via D/ST scores to see whether their future lines appear too large relative to their offensive output.
News Updates
After this piece is published, FantasyLabs is likely to provide news updates on a number of players herein mentioned. Be sure to stay ahead of your competition with our industry-leading DFS-focused news blurbs:
