Fantasy Football: 8 Safe Picks Based on numberFire's Projections
If you look at numberFireâ€™s projections, youâ€™ll notice that thereâ€™s a column titled CI. This is the confidence interval of the projection. What this means is the fantasy points projection is the mean of a range of outcomes, and the confidence interval is calculated by adding and subtracting one standard deviation to and from that projection. If a player has a wide range of outcomes that will be reflected in a larger standard deviation. Projections that we are more confident in are reflected in a smaller range of outcomes.
In this two-part series, Iâ€™ll highlight some of the safest players, as well as those with high variance outcomes, in our projections using those standard deviations. First, let me set some boundaries.
Players with higher mean projections will naturally have higher standard deviations. But even when adjusting for this there are a number of archetypes that will naturally populate the largest and smallest range of outcomes. Oft-injured tight ends and rookies are harder to project and will have larger standard deviations, while players who are in stable situations will be easier to project. So instead of just listing them using a â€œCalculate standard deviation, sort, descendingâ€ process, Iâ€™ve handpicked some of the most interesting players with high and low standard deviations.
Here, we'll start with the safest picks.
Drew Brees, New Orleans Saints
Standard Deviation: 28.6
Drew Brees has the third-highest projected fantasy total of all quarterbacks and the lowest standard deviation among the top five passers. The reason that our projections like him so much are likely the same reasons behind his remarkably small standard deviation: We have over a decade of data saying that he is a top fantasy passer.
Until last year, he had finished no lower than QB6 as a member of the New Orleans Saints. And if you think Brees fell off last year, donâ€™t. His 0.24 Passing Net Expected Points per drop back was identical to his career average. Alvin Kamara will come back down to Earth, and our Team Power Rankings see the Saints' defense as merely a top-half unit. Both of these factors should lead to more pass attempts for Brees, who attempted his fewest passes since 2009. If a decade of data is screaming that Brees is a fantastic quarterback on the field and in fantasy, donâ€™t let one year of low-usage shake your confidence.
Matt Ryan, Atlanta Falcons
Standard Deviation: 24.2
He has finished no lower than QB19 in his career and his average finish is 11.5. The Atlanta Falcons, as a team, average just over 600 pass plays per season in Ryanâ€™s career, but unlike Brees, Ryanâ€™s Passing NEP per drop back has reached a career-low 0.08. If youâ€™re committed to getting a safe passer but want to wait into the double-digit rounds, Ryan can be your Walgreens Brees.
Lamar Miller, Houston Texans
Standard Deviation: 20.7
In our projections, Lamar Miller has the smallest standard deviation among all backs in our top 30, and he gets there on the back of some underrated volume. Miller has 506 carries and 84 targets during his 2 years in Houston and will face little competition to add to those totals again this year. Alfred Blue was relegated to 71 carries last season, and D'Onta Foreman may miss the beginning of the season on the PUP list. This could lead to Miller regaining the 57.8% rushing market share that he saw in 2016. Despite falling to 53.1% last year, he stilled ranked 12th in rushing market share.
The reason Millerâ€™s range of outcomes doesnâ€™t encompass a high-efficiency breakout is because, after his rookie year (where he started a single game), he has just one season with a positive Rushing NEP per carry. His volume makes him a safe value, but with Houstonâ€™s inept offensive line play doing its part to sustain Millerâ€™s streak of mediocrity, buy into the floor, not the ceiling.
Carlos Hyde/Nick Chubb, Cleveland Browns
Standard Deviation: 21.2/13.5
numberFireâ€™s projections have a clear favorite in this backfield, and this projection is made with substantial confidence. Carlos Hyde owns the the second-lowest standard deviation among top-30 backs, and Nick Chubb has the second-lowest among top-60 backs. We like Hyde to flirt with RB2 status and Chubb to struggle to be relevant from a season-long perspective. Hyde is expected to out-carry Chubb 208 to 142.
This split isnâ€™t arbitrary either. Over the past 10 years, second-round rookie backs have averaged 131 carries in their first year (from Pro Football Reference). Despite Chubbâ€™s impressive college pedigree, the history of second round backs is working strongly against him.
Hyde may start as the lead back, and if this is the case fantasy owners who drafted Chubb will be forced to reserve a roster spot as they wait for a potential breakout. If the Cleveland Browns improve even slightly -- which shouldn't be hard to do, there could be some semblance of a positive game script for Hyde. If and when that happens, Hyde could prove to be a sneaky value while others look to the younger back in town.
Demaryius Thomas, Denver Broncos
Standard Deviation: 18.3
In 2017, Demaryius Thomas, for the first time, failed to reach 90 receptions and 1,000 yards while playing a full season. Thomas turns 31 on Christmas, and itâ€™s reasonable to think that he may have lost a step. But if you watched his targets from the combination of Brock Osweiler, Paxton Lynch, and Trevor Siemian (my deepest condolences to you and your loved ones), youâ€™ll know that last season was lost before it began for the Denver Broncos' offense. Together, they averaged -0.1 Passing NEP per drop back.
The addition of Case Keenum should bring stability to the teamâ€™s fantasy players. It will also allow Thomas to capitalize on his .59 weighted opportunity rating (a metric from AirYards.com that combines a players share of air yards and targets), which was 11th in the league. With volume being such a big predictor of fantasy points and Thomas still seeing a lot of it, heâ€™s a safe play going in the middle of the fourth round.
Michael Crabtree, Baltimore Ravens
Standard Deviation: 18.3
Michael Crabtree doesnâ€™t have the history of success that a player like Thomas does, but he was able to find success with a change of scenery in his move to Oakland . And now he is in another new place, this time with the Baltimore Ravens. Playing on a Joe Flacco -led offense isnâ€™t ideal, but targets are and Baltimore has a flood of them available.
Based on AirYards.com data, the Ravens lost 204 targets and 2,212 air yards from receivers alone this offseason. In addition to Crabtree, they brought in Willie Snead and John Brown to fill that void. However, last season, due to injuries, suspensions, and poor play, the two combined for less than 400 receiving yards. Brown could be healthy for the first time in three years, or Snead could prove he was more than just a product of the aforementioned Brees. Both of those scenarios cut into the safety of Crabtreeâ€™s target-based value. But barring those seemingly unlikely events, Crabtree is in line for his biggest volume yet.
Jack Doyle, Indianapolis Colts
Standard Deviation: 15.7
In his best season in the league to date, Jack Doyle finished with the third-highest share of team targets among tight ends and pulled down 80 catches for 690 yards in 2017. The Indianapolis Colts signed former first-rounder Eric Ebron, who will present competition for him, but his production can still be sustainable.
Based on Sharp Football Stats, Indy ran the third-most snaps from 12-personnel (a single back and two tight ends), so when Ebron is on the field it doesnâ€™t necessarily mean Doyle will be off. Doyleâ€™s average depth of target (aDOT) will keep him from making a significant amount of big plays, but a high target total provides a steady floor throughout the season.
Zach Ertz, Philadelphia Eagles
Standard Deviation: 20.0
Let me preface this paragraph with one thing: safety isnâ€™t always a good thing. Zach Ertz has the seventh-highest standard deviation of our projected top-12 tight ends despite being slotted in as the third overall tight end. Ertz saw the fourth-most targets last season, with 110, and this is evident from a relatively low standard deviation. In other words, volume gives us confidence.
But Ertz doesn't offer the game-breaking upside of a player like Rob Gronkowski. Heâ€™s a safe pick, though streaming the position can work out well all the same. In formats that increase the value of the position and decrease the streaming options, the safety inherent with Ertzâ€™s usage is worth taking. But when Greg Olsen has the same upper-end projection as Ertz, or when Delanie Walker can possibly net you just one fewer point per game at a fraction of the cost, the predictability of Ertz becomes less valuable.