I’m still in the first month working here at FG. One goal I had for each article that I was going to write was to have some actionable content for you, the reader, to apply to your fantasy leagues or upcoming drafts.
I may have finally met my match with a statistic that doesn’t really apply toward future production — catch rate.
Catch rate is a descriptive statistic, meaning it has no bearing on future production or outcome. It’s a noisy statistic but one that is commonly used when describing a receiver’s production. It’s year-to-year correlation doesn’t matter that much (0.48). It hardly correlates to wins (0.39). And it can wildly fluctuate year-over-year depending on quarterback, types of route run, defender positioning, etc.
While I don’t believe there’s much to be taken here to be applied directly to upcoming fantasy drafts, there is still some usefulness in it when used in conjunction with depth of target and whether or not a player is producing above or below league baselines thresholds.
What do I mean by that last part? Glad you asked! Let’s learn more on the subject.
Catch Rate By Distance
Let’s take a look at comparing catch rate by depth. This provides a glimpse into how successful a receiver generally is by contrasting their catch rate at varying distances downfield. We’ll use Julio Jones as an example.
Image courtesy of AirYards.com
The first thing I want to bring to your attention is the orange line. This represents the league average. Passes thrown at the line of scrimmage — zero yards in terms of depth of target — have just under an 80% completion rate. Passes thrown with 35 Air Yards have approximately a 30% chance of being completed.
Over the course of Jones’ career, he’s been above league average in the catch rate department — above the orange line — at just about every depth. His career catch rate of 63.7% isn’t spectacular by any means, but when you look at the sum of these parts — all the different passes throw to him at varying depths over the course of his career — well, there quite frankly aren’t many receivers that can put up that type of consistent performance above league average.
Wide Receiver Catch Rates in 2018
Last year’s highest catch rate belongs to record-breaker Michael Thomas. Thomas’ catch rate of 85.0% set the bar incredibly high considering it’s coming off a 147-target season. Let’s take a look at the top-10 finishers in catch rate last season with at least 40 targets thrown in their direction.
| Receiver | Team | G | Targets | Rec | RecYd | RecTD | Y/Rec | Catch% | aDOT | FantPt |
| Michael Thomas | NO | 16 | 147 | 125 | 1405 | 9 | 11.2 | 85.0% | 7.8 | 319.5 |
| Ryan Switzer | PIT | 16 | 44 | 36 | 253 | 1 | 7.0 | 81.8% | 3.4 | 69.4 |
| Tyler Lockett | SEA | 16 | 71 | 57 | 965 | 10 | 16.9 | 80.3% | 13.6 | 220.4 |
| Phillip Dorsett | NE | 16 | 42 | 32 | 290 | 3 | 9.1 | 76.2% | 10.2 | 81.9 |
| Cole Beasley | DAL | 16 | 86 | 65 | 672 | 3 | 10.3 | 75.6% | 7.4 | 150.2 |
| Danny Amendola | MIA | 15 | 79 | 59 | 575 | 1 | 9.7 | 74.7% | 7.9 | 127.7 |
| Bruce Ellington | HOU | 7 | 42 | 31 | 224 | 1 | 7.2 | 73.8% | 4.9 | 59.6 |
| Chester Rogers | IND | 16 | 72 | 53 | 485 | 2 | 9.2 | 73.6% | 6.3 | 113.1 |
| Adam Humphries | TB | 16 | 104 | 76 | 816 | 5 | 10.7 | 73.1% | 6.7 | 188.7 |
| Adam Thielen | MIN | 16 | 155 | 113 | 1373 | 9 | 12.2 | 72.9% | 9.5 | 307.3 |
Nine of the top-10 receivers listed above were primary slot receivers. Most of these receivers possessed a single-digit average depth of target (aDOT) under 10 yards. As referenced in the Julio graph above, these lower aDOT routes produce the highest catch rates.
The lone receiver who was not a primary slot receiver was Phillip Dorsett. Dorsett ran much more shallow routes than I had previously thought prior to going through this exercise. Chris Hogan (12.7), Rob Gronkowski (12.7), and Josh Gordon (13.6) all had higher aDOT’s than Dorsett’s 10.2. Dorsett also barely made this list (42 targets), so he could either just be an outlier here or had fantastic rapport with Tom Brady.
What about the other end of the spectrum? If the highest catch rate specialists from last year were mostly slot receivers, are the players at the bottom of this list the heavy field stretchers?
| Receiver | Team | G | Targets | Rec | RecYd | RecTD | Y/Rec | Catch% | aDOT | FantPt |
| John Ross | CIN | 13 | 58 | 21 | 210 | 7 | 10.0 | 36.2% | 13.9 | 84.9 |
| Kelvin Benjamin | KC | 15 | 67 | 25 | 380 | 1 | 15.2 | 37.3% | 17.2 | 69.0 |
| John Brown | BAL | 16 | 97 | 42 | 715 | 5 | 17.0 | 43.3% | 16.1 | 143.9 |
| Michael Gallup | DAL | 16 | 68 | 33 | 507 | 2 | 15.4 | 48.5% | 13.9 | 95.7 |
| Jermaine Kearse | NYJ | 14 | 76 | 37 | 371 | 1 | 10.0 | 48.7% | 9.8 | 80.1 |
| Courtland Sutton | DEN | 16 | 84 | 42 | 704 | 4 | 16.8 | 50.0% | 14.0 | 136.3 |
| David Moore | SEA | 16 | 52 | 26 | 445 | 5 | 17.1 | 50.0% | 17.4 | 101.0 |
| DeVante Parker | MIA | 11 | 47 | 24 | 309 | 1 | 12.9 | 51.1% | 12.7 | 60.9 |
| Marquez Valdes-Scantling | GB | 16 | 72 | 38 | 581 | 2 | 15.3 | 52.8% | 12.3 | 111.0 |
| Antonio Callaway | CLE | 16 | 81 | 43 | 586 | 5 | 13.6 | 53.1% | 13.9 | 132.3 |
BINGO! Fantasy football doesn’t need to be difficult.
Players with low catch rates were generally those that experienced low-percentage throws as deep ball specialists. There were also a few ineffective players among this subset — namely Jermaine Kearse — but for the most part, this group here had high aDOT’s resulting in low catch rates. In fact, outside of Kearse, all of these receivers had an aDOT north of 12.0. The league average catch rate at 12.0 aDOT is approximately 55% and this entire subset underperformed here in 2018.
One thing worth noting is just because these catch rates were low, that doesn’t mean these players don’t have value for fantasy squads. John Brown, Courtland Sutton, and Marquez Valdes-Scantling should see enough volume in 2019 where they can overcome low catch rates to produce big outings whenever they’re able to come down with the ball on deep attempts. While catch rates are hardly predictive of future success, targets are the key contributing factor and the lifeblood of fantasy scoring.
Tight End Catch Rates in 2018
Out of all tight ends that saw at least 40 targets last year, Austin Hooper sported the highest cate rate at 80.7%. Kyle Rudolph (79.0%) and Gerald Everett (78.6%) rounded out the top-three. One major common theme among these tight ends? Low average depth of target. All three of these tight ends had less than a 7.0 aDOT and all three also sported less than 10.0 yards per reception.
At the other end of the spectrum, the lowest catch rate among qualifying tight ends (min. 40 targets) belonged to O.J. Howard (48.6%). Sporting a position-leading 16.6 yards per reception and the second highest aDOT (12.4), Howard was used frequently downfield in the Buccaneers passing game. That role shouldn’t differ much in 2019 with Bruce Arians on board. Tyler Higbee (55.8%) and Eric Ebron (60.0%) were also bottom-dwellers in the low catch rate department, rounding out the bottom-three.
Intuitively, with the tight position generally running more shallow routes than their wide receiver counterparts, the tight ends had a higher group catch rate (67.5%) than the wideouts (63.6%). That’s more indicative of the roles each play in their offenses, but it was noteworthy nonetheless.
The one key takeaway from this article is to remember that catch rate is descriptive, not predictive. Catch rates can wildly fluctuate year-over-year depending on quarterback, types of routes run, defender positioning, etc. Context is key, specifically the depth of target. When constructing your fantasy teams, a mix of receivers that operate at different depths of targets can help you avoid inconsistent weeks and create a nice fantasy baseline to rely on.
