We, as fantasy football managers, can be heavily swayed by anecdotal evidence and personal experience, and that can cause us to ignore larger trends that will help us find long-term success.
Maybe you drafted Josh Allen early in your drafts last year and are convinced that an early-round quarterback is an absolute must to win your league. Maybe you selected Christian McCaffrey and swore off of early-round running backs and would rather play the late-round and waiver-wire guessing game for your backs (which, by the way, is harder to do than you might think).
And while median fantasy football projections help get your bearings as we enter draft season, they don't do a good job explaining the range-of-outcome reality that exists with fantasy prognostication.
Fantasy football is volatile. Injuries happen. Players are less (or more) efficient than expected. This means that -- with, say, a reasonable discrepancy in touchdown rate from expectation -- players can easily fall from a QB6 projection to a QB13 output, and we won't think twice about it.
But in order to put some math behind this and help uncover the actual odds certain players return us with top-tier fantasy results, I went ahead and simulated the NFL season 10,000 times to see which tight ends (and quarterbacks, running backs, and wide receivers) are most likely to lead the league in fantasy points. This can help us uncover who has tangible, predictable league-winning upside for the 2022 season.
The Process and Expectations
It's very easy to get stuck in neutral when constructing fantasy football projections. Yes, we want to be accurate, but trying to find a rigid answer to a rate stat isn't going to help us very much.
At tight end, this is actually a really fascinating exercise.
We have a few players who are projected for substantial roles that few other tight ends can match. This year, that's Travis Kelce and Mark Andrews -- followed after a tier break by Kyle Pitts, Darren Waller, and George Kittle.
These guys have workloads that are in a different stratosphere than the rest.
After them, everything gets flat, and we'll see tight ends -- by year's end -- separated not really by volume but rather touchdown variance and some hard-to-project per-target efficiency numbers.
For these simulations, I used the same method as I did with the other positions: I studied historical deviations and ranges of outcomes for players based on numberFire's preseason fantasy football projections. This helped me tailor projections for the simulations.
From there, I accounted for historical injury rates among positions, replacements for injuries when they occur in the simulations, and -- of course -- actual fantasy point variance because, even if a player plays all 17 games, he is unlikely to score his exact projection.
It's important that the simulation results resemble historical precedent. Otherwise, we're off base with either our baseline projections or our standard deviations.
Here is how tight ends -- bucketed by average draft position (a proxy for initial fantasy rankings) -- have fared in meeting certain thresholds.
| ADP Bucket | Leader% | Top-5% | Top-12% | Top-24% |
|---|---|---|---|---|
| TE1 to TE6 | 16.7% | 43.3% | 61.7% | 86.7% |
| TE7 to TE12 | 0.0% | 10.0% | 43.3% | 68.3% |
| TE13 to TE18 | 0.0% | 17.5% | 40.4% | 70.2% |
| TE19+ | 0.0% | 2.7% | 12.3% | 36.9% |
Since 2012, each of the overall TE1s by season's end has had a top-six average draft position (ADP), meaning the search for league-winners (historically) hasn't gone very deep into drafts. The top-six tight ends by ADP have a top-five and top-12 hit rate that is unmatched by the rest of the position.
Notably, there is not much difference between the second and third tiers used here. In fact, the better upside (by top-five seasons) has belonged to the tight ends in the third tier.
It's beyond the purview of this study, but it's likely the result of overvaluing last year's results to separate the non-elites come draft time next season.
Simulation Results and Analysis
Here are the results of the 10,000 season simulations and each tight end's average draft position in FanDuel's best ball fantasy football formats.
A caveat here is that a lot of these are going to feel "wrong" across positions. It feels wrong to think that there's a minuscule chance for a low-end TE1 to be the top performer, but based on historical trends -- and the mathematics behind the range of outcomes -- it's accurate. Some of them will get injured, and others will overperform.
The goal is to project 2022 not as the flowery, flawless preseason we all hope to see but as the utter mess that it always winds up being.
| Tight End | FanDuel Best Ball ADP | Leader % | Top-5 % | Top-12 % | Top 24 % |
|---|---|---|---|---|---|
| Travis Kelce | 1 | 30.7% | 65.3% | 83.4% | 92.8% |
| Mark Andrews | 2 | 21.0% | 57.2% | 77.5% | 90.2% |
| Kyle Pitts | 3 | 10.2% | 43.6% | 69.2% | 86.5% |
| Darren Waller | 5 | 10.2% | 42.9% | 68.4% | 86.3% |
| George Kittle | 4 | 7.7% | 39.0% | 66.2% | 84.9% |
| Dalton Schultz | 6 | 3.4% | 26.3% | 54.4% | 77.4% |
| Dallas Goedert | 9 | 2.4% | 20.9% | 48.6% | 75.9% |
| T.J. Hockenson | 8 | 2.1% | 18.8% | 46.0% | 72.9% |
| Dawson Knox | 7 | 1.2% | 14.6% | 39.6% | 68.0% |
| Hunter Henry | 13 | 1.0% | 11.9% | 35.7% | 65.8% |
| Cole Kmet | 12 | 0.9% | 12.0% | 35.6% | 66.7% |
| Albert Okwuegbunam | 15 | 0.9% | 11.0% | 34.8% | 64.8% |
| Noah Fant | 19 | 0.9% | 11.1% | 34.9% | 65.1% |
| Pat Freiermuth | 14 | 0.9% | 10.3% | 34.0% | 64.4% |
| Zach Ertz | 10 | 0.8% | 12.2% | 36.3% | 65.5% |
| Robert Tonyan | 22 | 0.8% | 9.4% | 31.9% | 62.3% |
| Mike Gesicki | 11 | 0.8% | 10.4% | 34.3% | 63.3% |
| Irv Smith Jr. | 18 | 0.6% | 9.7% | 32.6% | 62.8% |
| David Njoku | 17 | 0.6% | 9.5% | 31.1% | 61.4% |
| Gerald Everett | 20 | 0.5% | 9.3% | 30.9% | 60.2% |
| Tyler Higbee | 16 | 0.4% | 10.0% | 33.2% | 62.2% |
| Logan Thomas | 34 | 0.4% | 6.1% | 25.9% | 56.4% |
| Austin Hooper | 23 | 0.3% | 7.4% | 27.9% | 57.4% |
| Evan Engram | 21 | 0.3% | 7.1% | 27.6% | 57.5% |
| Adam Trautman | 35 | 0.3% | 6.6% | 25.6% | 54.2% |
| Jonnu Smith | 32 | 0.1% | 2.6% | 15.2% | 44.5% |
| Kyle Rudolph | 29 | 0.1% | 2.2% | 13.3% | 41.7% |
| Mo Alie-Cox | 26 | 0.1% | 3.1% | 17.3% | 45.9% |
| Hayden Hurst | 24 | 0.1% | 2.3% | 14.9% | 43.5% |
| Tyler Conklin | 33 | 0.1% | 2.4% | 14.9% | 42.9% |
| Brevin Jordan | 28 | 0.0% | 1.3% | 10.5% | 36.4% |
| C.J. Uzomah | 27 | 0.0% | 0.1% | 2.9% | 19.5% |
| O.J. Howard | 40 | 0.0% | 0.2% | 3.7% | 21.4% |
| Cameron Brate | 25 | 0.0% | 0.1% | 1.2% | 12.3% |
| Donald Parham Jr. | 37 | 0.0% | 0.1% | 2.3% | 17.1% |
| Josiah Deguara | 38 | 0.0% | 0.0% | 1.0% | 12.0% |
Okay, okay, okay, we gotta talk about Kelce and Andrews, right? Combined, they comprise more than 50.0% of the league-leading seasons in the simulations. That can't be right -- can it?
Well, remember that these are based not on the specific performances of past projected TE1s but rather on numberFire's fantasy football projections.
In half-PPR formats, Kelce is projected for 238.0 points, and Andrews is at 215.1. Nobody else is above 175. Even when accounting for historical variance, they are set up to dominate this season.
What does a closer look at history tell us, though? Since 2016, numberFire's model has projected only 10 tight ends for at least 200.0 half-PPR points. That sample recorded two overall TE1 seasons but six top-three seasons. The five seasons outside the top three came from guys who failed to play 14 games.
Moreover, on a per-game basis, three of these 10 were the TE1, and nine of them had top-five scores in half-PPR points per game. We know which tight ends are great. We just can't always guarantee their health.
As for that second tier of Pitts (10.2% to lead the league), Waller (10.2%), and Kittle (7.7%), they really do deserve attention compared to the rest of the position, as nobody else has better than a 3.4% chance to lead the position in fantasy points.
For someone outside the top five to be the TE1, we're really asking for injuries and/or substantial underperformance from five tight ends with elite volume projections relative to the rest of the position. Kelce (150.2 targets), Andrews (146.3), Pitts (132.6), Waller (121.4), and Kittle (113.0) are joined by only Dalton Schultz (102.3) and T.J. Hockenson (100.7) in the 100-projected-target club.
This is much more bunched up at the top than we have for, say, quarterback. Nobody is projecting five quarterbacks for an extra 100 pass attempts compared to the rest.
Tight end really warrants its own discussion, and it's clearly led by five potential league-leaders.
Of course, a low-end top-five -- or even top-10 -- season from a tight end you draft as an afterthought in the late rounds or whom you acquire from the waiver wire during the season is a great return on investment.
However, the reality is that true league-winning upside (both historically and projectably) will require some serious investment in our fantasy football drafts.