The Late-Round Fantasy Football Podcast artwork

1107: Catchable Targets

STACKED extracted the fantasy-relevant player signal from this podcast and kept the full transcript here for context.

29 min
Duration
Estimated from transcript
Jun 30, 2026
Published
Tue, June 30, 2026
30
Player insights
26
Players mentioned
Topics
Darnell MooneyJa'Marr ChaseLuther BurdenMike EvansAlec PierceAmon-Ra St. BrownD'Andre SwiftDrake LondonEno BenjaminJameson WilliamsJerry JeudyJordan AddisonJustin JeffersonKhalil Shakir
Player analysis

Player insights

30

Alec Pierce

PositiveProjection317:00

Pierce is identified as a favorable regression candidate entering 2026, with a low catchable target rate in 2025 that should improve based on historical regression patterns.

Insight page

Amon-Ra St. Brown

PositiveProjection21:48

St. Brown's high catchable target rate reflects the quality of the Detroit offense and quarterback play, supporting sustained efficiency.

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D'Andre Swift

PositiveProjection25:32

D'Andre Swift is cited as an example of a player with low catchable target rate over two consecutive seasons who did not bounce back, illustrating that regression logic does not always apply and some players may simply lack the efficiency profile to improve year over year.

Insight page

Darnell Mooney

PositiveRole16:45

Mooney is a favorable regression candidate for the Giants; his role could expand depending on the health of Malik Nabers, creating potential for increased opportunity and catchable targets.

Insight page
PositiveRole274:10

Darnell Mooney is identified as a favorable regression candidate for the Giants entering 2026, with potential for an improved role depending on the health status of Malik Nabers. His catchable target rate has room to improve from depressed 2025 levels.

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Drake London

PositiveSleeper321:40

London is identified as a favorable regression candidate and late-round flyer for best ball in 2026, despite being a contested catch archetype. He saw a lot of uncatchable targets according to Fantasy Pros in 2025, positioning him for favorable regression in catchable target rate.

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Eno Benjamin

PositiveValue16:15

Benjamin has been a positive regression candidate for two straight years; he had under a 50% catchable target rate last year according to Fantasy Pros, which seems low and suggests upside if quarterback play improves with the Jets.

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Ja'Marr Chase

NegativeRole12:00

Chase's ADOT has declined year over year, with his lowest ADOT of his career in 2025; he's running more out routes and hitch routes rather than downfield work, which increases his catchable target rate but represents a shift in deployment and role within the offense.

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PositiveRole200:09

Jamar Chase's ADOT has declined year over year, with his lowest ADOT of his career in 2025 as he runs more out routes and hitch routes rather than downfield work. Despite the shift toward shorter routes, this represents a favorable development because he's receiving more catchable passes, which should support efficiency metrics like yards per route run.

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Jameson Williams

PositiveProjection21:48

Williams was a surprising inclusion on the high catchable target rate list, suggesting unexpected efficiency despite his injury history and role uncertainty.

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Jerry Jeudy

PositiveSleeper317:40

Jeudy is identified as a favorable regression candidate and late-round flyer for best ball in 2026, with a low catchable target rate in 2025 that should improve year over year.

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Jordan Addison

PositiveSleeper319:50

Addison is identified as a favorable regression candidate and late-round flyer for best ball in 2026, with a low catchable target rate in 2025 that should improve based on historical regression patterns.

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Justin Jefferson

PositiveSleeper319:50

Jefferson is identified as a favorable regression candidate and late-round flyer for best ball in 2026, with a low catchable target rate in 2025 that should improve based on historical regression patterns.

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Khalil Shakir

PositiveProjection21:42

Shakir is expected to maintain a high catchable target rate due to his offensive role and usage pattern; his short average depth of target (around four yards) makes it difficult to miss with targets in his environment.

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Luther Burden

PositiveProjection18:00

Burden had a historic rookie season with 2.74 yards per route run (highest among rookie receivers with 200+ routes since 2020) and caught 47 of 60 passes; however, he's an unfavorable regression candidate because his extremely high catchable target rate (7.7 ADOT) may not be sustainable, and Caleb Williams historically has lower catchable target rates, suggesting Burden could see more uncatchable targets going forward.

Insight page
PositiveProjection290:10

Burden posted a historic rookie season with 2.74 yards per route run (highest among rookie receivers with 200+ routes since 2020 per True Media) and caught 47 of 60 passes, but JJ Zachariason identifies him as an unfavorable regression candidate entering 2026. His ADOT was only 7.7 yards, and with Caleb Williams historically showing below-average catchable target rates, Burden may see a higher uncatchable target rate if asked to work downfield more.

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Marvin Harrison Jr.

PositiveSleeper321:10

Harrison is identified as a favorable regression candidate and late-round flyer for best ball in 2026, with a low catchable target rate in 2025 that should improve based on historical regression patterns.

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Matthew Stafford

NegativeProjection23:58

Matthew Stafford's touchdown rate is identified as one of the most glaringly obvious regression spots this year. Despite posting an almost 8% TD rate and not rushing, he is not being drafted as a top-10 quarterback, suggesting the market may be undervaluing his regression risk or overvaluing other QBs.

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Mecole Hardman

PositiveProjection22:30

Hardman is cited as an example of a player with poor catchable target rate who is commonly expected to regress and improve next year; however, JJ Zachariason cautions against assuming automatic bounce-back without deeper analysis of the underlying situation.

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Michael Pittman

PositiveProjection21:48

Pittman is listed among receivers with high catchable target rates, positioning him as a player less likely to regress in efficiency metrics.

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Michael Wilson

PositiveSleeper321:10

Wilson is identified as a favorable regression candidate and late-round flyer for best ball in 2026, with a low catchable target rate in 2025 that should improve based on historical regression patterns.

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Mike Evans

PositiveValue18:30

Evans is a favorable regression candidate; he only played half a season last year with a low catchable target rate, but his catch rate has been solid for his contested-catch archetype, and he now joins Brock Purdy's offense, which consistently has better-than-average poor throw rates, suggesting he should get more on-target passes.

Insight page
PositiveProjection26:00

Evans is a favorable regression candidate despite playing only half a season in 2025 (an outlier). For his archetype as a downfield contested catch receiver, his catch rate has been solid. Moving to the 49ers with Brock Purdy, who consistently maintains better-than-average poor throw rates, Evans should receive more on-target passes in 2026. JJ Zachariason also notes that Evans had a weak efficiency season in 2024 but played only eight games with Baker Mayfield not fully healthy; applying catchable target rate regression logic, Evans can be positioned as a candidate for a massive bounce-back season if health and QB stability improve.

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Nico Collins

PositiveSleeper319:50

Collins is identified as a favorable regression candidate and late-round flyer for best ball in 2026, with a low catchable target rate in 2025 that should improve based on historical regression patterns.

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Puka Nacua

PositiveProjection340:40

Nakua is identified as an unfavorable regression candidate on the surface, but this should not be interpreted as negative. He has maintained at least a 73% catchable target rate in each of his last three seasons (per Fantasy Pros), making him one of the few players who consistently makes uncatchable balls catchable. He receives a high rate of targets near the line of scrimmage but also a high rate of downfield targets, suggesting his efficiency is driven by elite receiver skill rather than scheme, positioning him to sustain his production.

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Quentin Johnston

PositiveSleeper321:10

Johnston is identified as a favorable regression candidate and late-round flyer for best ball in 2026, with a low catchable target rate in 2025 that should improve based on historical regression patterns.

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Rashee Rice

PositiveProjection21:57

Rice is listed among receivers with high catchable target rates, positioning him as a player less likely to experience efficiency regression.

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Stefon Diggs

PositiveProjection334:20

Diggs is identified as an unfavorable regression candidate entering 2026, with his landing spot being a key variable. He has a lower-than-receiver-average aDOT, which historically correlates with higher catchable target rates that are sticky year over year, suggesting his 2025 efficiency may not be sustainable.

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Xavier Worthy

PositiveSleeper319:50

Worthy is identified as a favorable regression candidate and late-round flyer for best ball in 2026, with a low catchable target rate in 2025 that should improve based on historical regression patterns.

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Zay Flowers

PositiveProjection340:40

Flowers appears to be an unfavorable regression candidate on the surface, but JJ Zachariason is increasingly bullish on him and actively trying to get more exposure to him in 2026. He has increased his yards per route run in each of the last three seasons (1.86, 2.47, 2.55) and came off a career-best catchable target rate in 2025, suggesting his efficiency gains are real and sustainable rather than regression-prone. Zachariason expects the catchable target rate to scale back but remain solid.

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Full transcript

Episode Transcript

320
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0:50This is the Late-Round Podcast with your host, JJ Zacharyarysen.
0:53JJ Zacharyarysen. What's up everyone? It's JJ Zacharyarysen in this episode 1107 of the Late-Round Fantasy Football Podcast.
0:59Thanks for tuning in. I hired Brandon Gadula to be part of the Late-Round Fantasy Football team back in January.
1:06Since then, he's helped with a prospect guide specifically with tight ends.
1:09He's helped me in building out everything you're now seeing with market score.
1:14And nearly every week, he's sending out a newsletter to all Late-Round subscribers.
1:18That newsletter, by the way, totally free. And if you're not subscribed, you're missing out.
1:23Because Gadula's deep dives are really awesome and they're definitely worth your time.
1:27One of his more recent newsletters had to do with catchable targets.
1:31I think a lot of times there are metrics out there that we assume regress in the exact same way.
1:37That a high rate one year means a lower rate the next year.
1:41Or a lower rate means a higher one the next year.
1:45And while regression is almost always inevitable, it doesn't always work out that cleanly.
1:49So I sat down with Brandon for a quick chat about catchable targets.
1:54Both from a receiver and quarterback perspective. Because I wanted to see what we could take away from his research for drafts this year.
2:01Now before getting into my conversation with him, I wanted to remind you to check out the Late-Round Draft Guide.
2:08It's filled with game theory talk, ways to spot breakouts and busts, draft strategy for this season, players to target, players to avoid, and so much more.
2:16It'll be out on July 10th and you can pre-order right now at a discount.
2:21Check it all out over on LATEROUND.com Now here's my discussion with Brandon Gadula.
2:26So Brandon, you sent a newsletter blast out not long ago on catchable targets data.
2:31Can you describe what you were aiming to do with that?
2:34Yeah, the goal, pretty simple. Just looking into catchable target data to see, specifically for wide receivers at the time, in order
2:41to see if it was sticky year over year, or if it could tell us about regression of any kind, identify regression,
2:48not just for catchable target rate, but its impact on other related statistics.
2:52But, you know, regression, as we've talked about, just a big part of my process in the world of so much subjectivity
2:59and guessing about roles and how coaches will use certain players.
3:03It's really one of the few things that we can just test and say, like, look, I'm not even accounting for quarterback changes or role changes.
3:11But if we see changes year over year that we can kind of somewhat predict when it comes to catchable target rate,
3:18that's really good information for me to use in my process.
3:22So, you know, the thing with catchable targets is, first of all, you can you'll find very different numbers based on your
3:29source to just keep that in mind. I used fantasy pros.
3:33It was just really widely available, easy to see, and other people could use it if they want to.
3:39But it could be a function of wide receivers, could be a function of quarterbacks.
3:44So I ended up looking a little bit into quarterbacks after the fact as well.
3:48But, you know, one of the things with receivers that I think is important, and it became as I got like really
3:55down, like deep in the weeds with catchable target rate, it just kind of hit me that, you know, yeah, we look
4:03at volume for a lot of these guys. But outside of the top tier receivers who get a ton of volume, what
4:10we're really kind of looking at is efficiency numbers for these sort of outside tier two, honestly.
4:15Like once you get into tier three, four or five, like these types of wide receiver 30 and beyond type names, you're
4:22really looking for like efficiency, whether that's per target, per route numbers.
4:26And so, you know, if you look at two receivers, let's say both average 10 yards of target, 100 total targets, but
4:33player A, let's say gets 100 catchable targets. Player B gets 75.
4:37That should matter. That should sort of say that player B did more with his catchable targets.
4:42But, you know, if catchable target rate at the same time stays the same because of player archetype or quarterback infrastructure or
4:49whatever, you know, then we also know that player A's catchable targets going to be higher than player B's catchable targets.
4:56So, you know, of course, it's not quite as simple as that, but just to answer your question directly, very clear aim,
5:03just to see what we can learn from a prior season catchable target rate as we project forward to the next year.
5:10I think a lot of fantasy managers and especially, I mean, even myself to a degree, assume regression with catchable targets.
5:17You know, I do want to caveat that regression in and of itself can't just be blanketed and use the same way from one statistic to the next.
5:26But I think intuitively catchable targets seem like something that would regress.
5:30You know, one year you have a really low catchable targets rate, and that's because, you know, you had a backup quarterback
5:37or the quarterback had an injury or whatever the case may be.
5:41And then the next year just gets a little bit better because that's just what happens with football and larger sample sizes.
5:48But is that what you found at a high level with these guys?
5:52Yeah, at a high level, for sure. And again, I'm not, you know, sometimes when I'm doing regression, I will look at
5:59like, did this guy have the same quarterback or, you know, did the quarterback was the week one starter different?
6:06I don't even do that because sometimes I think if there's signal, there's signal.
6:10And sometimes you can get really bogged down in the details.
6:14And sometimes you don't have to if the numbers are strong enough.
6:18But yeah, it does seem like catchable targets, according to my research, which did it back to 2017.
6:23It really just looked at year over year data for receivers who had at least 50 targets in consecutive seasons.
6:30So yeah, like the numbers do look like they regress toward the league average, but it's not, you know, super straightforward.
6:37The high level summary effectively is when you bucket players into quartiles.
6:40So basically four equal buckets, the players with really low catchable target rates in a given season.
6:46They tend to see a noticeable uptick in catchable targets the next season, which is what we would expect.
6:52They don't stay terrible forever. The top quartile by catchable target rate, the guys getting a very high rate of catchable balls.
6:59They also regress, but not necessarily to the league average, which I think both of those things make sense.
7:05League average, by the way, again, just really depends on the source that you're looking at.
7:10Again, I used fantasy pros, but I looked at other sources too.
7:14And the general trends for catchable target rates, like directionally, they're very strong.
7:18You know, some guy might stand out a little bit differently, but for the most part, so long as you're just looking
7:25at the same source, I think you're going to be fine.
7:29But yeah, like when you see really low catchable target numbers, that probably some of that has to do with your quarterback
7:36play, but also your archetype, also a level of how much you contribute to that in terms of getting open.
7:43But what I thought, what I found just as interesting was, yeah, it's nice to say players who really didn't see a
7:50lot of catchable targets or specifically saw a high rate of uncatchable passes.
7:54Like, yeah, they kind of come back toward the league average, but the players who get a lot of catchable targets, that
8:01high rate of catchable targets, they do step back a little bit, but they tend to kind of as a bucket.
8:08Be above the league, which not all these guys are like super low-a-dot guys, which I think is interesting.
8:14There's kind of good players who kind of are able to see a lot of catchable balls and make the most of it.
8:21Could be catch radius stuff. And again, that's one of those things with regards to your specific source for catchable targets.
8:28Like if a receiver makes an athletic play toward the ball, that might be a penalty toward him if it's catchable and he can't quite get there.
8:37That just might be different on how some sources chart it.
8:40It could be totally due to the quarterback, could be how much the receiver is doing.
8:45But yeah, I think again, at a high level, we do see these numbers regress.
8:50And what was interesting too, and one thing I didn't get into in the newsletter, and I would love to do more
8:57of, is I looked at yards per target and yards per catchable target year over year.
9:02And yards per catchable target had a much higher R squared year over year from these receivers who had consecutive qualified seasons.
9:09It's about 0.06 just yards per target. But yards per catchable target was 0.14, almost 0.15, which I thought was interesting.
9:16And it really led me to believe, like, I want to look more into this because in fantasy football, we're definitely not
9:23maxed out with the stats we're looking at. There's a lot we can do with analytics.
9:28But as we get more data, I'd love to just kind of change the divisor.
9:33I can never pronounce that. But just change the, you know, we have routes.
9:38Initially, we had yards per catch. Then we had yards per target, yards per route.
9:42Let's look at yards per catchable target. I want to do more with that based on what I found because I do
9:50think that there's a lot to this. Yeah, essentially the denominator of a fraction, right?
9:54Like essentially the whatever we're whatever we're dividing by in those cases.
9:58I do think that what you mentioned on there or in that answer is important.
10:03And that was the a dot stuff because a dot obviously gives us a sense of the type of role that a player is playing.
10:11Right. Like if it's a super high a dot, then he's a he's usually more of a field stretcher.
10:17If it's a lower a dot, then he's not.
10:20And there is a relationship between lower a dot and higher catchable targets.
10:24Correct. And then and then higher a dot and lower catchable targets.
10:28And so that probably plays some role. I would imagine in the stickiness year over year because a player plays a similar
10:35role, you know, a field stretching wide receiver who's been in the league for four years.
10:40And that's the role that he plays. Probably isn't going to change that up all of a sudden, you know, the following season.
10:48It's not like everyone, you know, I mean, you can look at like Alec Pierce right now, but like we don't know exactly what even that is.
10:56That's going to look like, you know, after after what he's done throughout his career.
11:01So I do think that that's part of probably part of the reason that we see like the guys who are in
11:08the higher end bucket, you know, the higher quartile where, like you said, they're not necessarily falling because they might just have
11:15these like perfect fantasy friendly roles that allow for higher catchable targets.
11:19Just because they're in like the perfect a dot range.
11:23Right. And maybe the quarterback itself is just good at throwing in that that a dot range.
11:28And so if the if the situation, if the deployment is all sticky year over year, then all of a sudden, you
11:35know, you have a very similar catchable targets rate year over year and it's able to be more reliable and not regress to some mean.
11:43Yeah. And I think that's interesting, too, because we're we're usually or historically, you know, at least I I'll put a frame it this way.
11:51I've looked for like upside guys, right, like higher a dot receivers kind of looking a little bit down on some of
11:58the the high volume receivers who don't get, you know, the downfield work to the degree.
12:03I was really surprised and I dug into this for the draft guide looking at market score.
12:09But like market score is pretty it's still pretty high on Jamar Chase, but I dug into Jamar Chase and like his
12:16a dots been going down year over year. Like he had it.
12:20I think I think every single season he definitely had his lowest a dot in 2025 of his career running a lot
12:27more, but running a lot more out routes, hitch routes and stuff.
12:31So I think that's interesting. But that's also like rather than look at that as a negative, he's getting catchable passes.
12:37Right. Right. That's super relevant. So I want to like I want to continue to explore this because I do think there's a lot of signal here.
12:46Yeah. Yeah, for sure. And then let's look at quarterbacks.
12:49Like, did they regress with their on target rates to like is that, you know, similar mechanism as to what you saw with wide receivers?
12:57Yeah. So I basically do the same thing for quarterbacks and the year over year are squared for poor throw rate since
13:042017 among quarterbacks with 100 plus attempts in consecutive seasons.
13:08It's about 0.16. It's not bad for receivers overall.
13:11It's like 0.14. But again, it comes down to the details, right?
13:14The guys who are really high or really low in these poor throw rates.
13:19So it's basically the same story. I could just kind of leave it at that.
13:24But I think it also makes sense. Higher a dot quarterbacks versus lower a dot quarterbacks.
13:29Or frankly, you know, it's really, really difficult to isolate out.
13:32Like we know which receivers in theory. In theory, we know who's good.
13:37But with quarterback samples grow. They touch the ball in basically every single play.
13:41They're in control. We can even isolate out more like, OK, was he under pressure?
13:46Like, let's look at things from a clean pocket.
13:49Can he have catchable balls from a clean pocket?
13:52These types of things. So it's a lot easier.
13:55And we would expect quarterback rate to be a little bit stickier.
13:59And it is. But yeah, the quarterbacks who throw, you know, not a lot of poor passes.
14:04They do kind of trend toward the league average.
14:07It's about 0.1 or sorry, 1.7 percentage points higher the next year in terms of poor throw rate.
14:13League average roughly, again, according to fantasy pros, about 16% just to simplify it.
14:17And so if you're if you're at like a 12%, you might be closer to 13 and a half, 14%.
14:24But you're still generally, again, as a bucket going to play better by that metric.
14:28And then the inverse, of course, the guys who just threw a lot of bad passes get a bit better at minus 2.1 percentage points year over year.
14:37But I will say both of these studies require you to have like a qualified season the next year.
14:44So if you're throwing a lot of bad passes as a quarterback, you might not get 100 attempts the next year.
14:50Same as receiver. If you're not getting yourself open or or if maybe OK, maybe you're still on the low end of
14:57catchable target rate, but you can't even like get close to it.
15:01There's no catch radius like you're not going to qualify for the next season.
15:06So just keep that in mind. But again, to sum it up, quarterback pretty similar.
15:11The tail end is going to regress a little bit back toward the league average.
15:15But we still tend to see the guys who have that higher poor pass rate still going to be a little bit
15:22higher than league average as in general from a bucket standpoint.
15:26Let's look at 2026 and let's let's just look at favorable and unfavorable regression candidates in 2026 and see if there are
15:33any players based on the catchable targets data that you think should regress favorable.
15:38We'll start the favorably side. So are there players out there that you think might end up being undervalued because of this
15:45and because of maybe the market not factoring in that regression or just just players that will see favorable regression within the statistic?
15:52Yeah. So one thing that's interesting, just league wide is like a dot trending down.
15:57So poor throw rate is kind of down a bit, which is nice.
16:01Kind of more catchable passes being thrown just as a duck gets depressed.
16:05But there are still some favorable regression candidates entering 2026.
16:08Some of these guys a little bit more relevant for best ball.
16:12Someone like 80 Mitchell has actually been a positive regression candidate for two straight years.
16:17He's like he's got one of the few seasons.
16:20And again, this is fantasy pros, which I think these numbers are kind of low.
16:25But it just also hammers home the difference in how site like sites will source things.
16:30But he had under a 50% catchable target rate last year.
16:34And that scene again seems kind of crazy, but it's just consistent.
16:37And again, directionally, they're all the same across different sources.
16:41But 80 Mitchell for the Jets and then, you know, possibly has improved quarterback play.
16:45I think that's interesting. Darnell Mooney as well for the Giants could have a bit of a role depending on the health of Malik neighbors.
16:53So I think that's interesting. But some bigger, well, I guess I'll throw in one more flyer just as I'm going down the list.
17:01But Alec Iomaner also hits. But for some more directly fantasy relevant guys toward the top end, Roma Dunze and Mike Evans
17:08saw a really low catchable target rate. Evans, of course, didn't play a full season.
17:13But I'll start with a Dunze. His ADOT. So again, a lot of this is kind of tied to ADOT.
17:20But ADOT can change based on your role as well.
17:23A Dunze, his ADOT was 13.9 yards downfield in 2025.
17:26And what's interesting is we're kind of comparing a Dunze.
17:29We know he's got like a foot issue, a whole sort of new normal for him.
17:34So maybe his ADOT does change. And what's interesting is he has a very direct comparison of somebody who saw a really
17:41high catchable target rate in Luther Burt. But Burden's ADOT was only 7.7 yards, according to True Media.
17:47Again, just a super high catchable target rate that led to phenomenal yards per route run.
17:52I'm not saying that was the only case for it, but a really historic rookie season.
17:57And if Burden starts pushing downfield more, he has a quarterback who historically, and Caleb Williams, not the greatest catchable target rates from him.
18:05So I think that that's interesting here where a Dunze could see some more catchable balls.
18:10Burden might see a little bit of a higher uncatchable target rate.
18:14So just something to keep in mind. Mike Evans, though, I think is really interesting.
18:19He's a little bit of a peculiar one for market score.
18:23A lot of that has to do with age and team competition for him.
18:27But he only played half a season last year.
18:30Super outlier. It was interesting to see Evans because for the archetype he is, like a downfield contested catch guy, his catch
18:37rate's been pretty solid, all things considered. And now he heads to a new offense.
18:42He's got Brock Purdy, who consistently has been better than average in terms of poor throw rate.
18:47So should get a lot of on-target passes to Mike Evans.
18:51So I think that's interesting. Some other names, though, surprisingly, Devontae Adams.
18:55Probably because 90% of his targets are just contested in the end zone.
18:59Alec Pierce and Emeka Ibuka also make the list.
19:02I mean, there's a lot of big names in the newsletter, too.
19:06I could rattle off a few more. And Jerry Judy, who I know you've been kind of interested in in terms of best ball as a late flyer.
19:15I think I think that's kind of the thing that is interesting.
19:19Like the late the late flyers for best ball is really how I'm thinking about this early on.
19:24Xavier Worthy, Nico Collins, Jordan Addison and Justin Jefferson.
19:27T Higgins, Quentin Johnston, Marvin Harrison and Michael Wilson.
19:30And surprisingly, Drake London. But I guess he's also another one of those like contested catch guys.
19:36So, again, it was kind of a strange year.
19:38A lot of uncatchable targets, according to Fantasy Pros last year.
19:42So you do see a lot of names who could get, you know, a better a better go of it in 2026.
19:49What about on the other side for the the unfavorable candidates?
19:53Yeah. So, again, you have to keep in mind that historically speaking, we see this is a little bit stickier.
19:59But at the top of the list is the fond digs where, you know, where he winds up, you know, for 2026.
20:06It will depend on where he lands, but pretty low a dot or like lower than receiver average.
20:12It wasn't terrible or anything last year for him.
20:15Already talked about this, but Luther Burden just like a crazy efficiency season, which I think is interesting.
20:212.74 yards per route run, which is the highest yards per route run among a rookie receiver with 200 plus routes since 2020, according to True Media.
20:29But caught 47 of 60 passes. Just, you know, crazy season there.
20:33And then we get into two really interesting names who could, if you are taking this very literally and kind of missing
20:40the big picture, they could scare you. But Puka Nakua and Zay Flowers.
20:44Puka, just a good reminder that, like, I would have bet he has a lot to do with, like, getting after passes
20:51and making more balls catchable than he probably should.
20:54But Nakua, you know, if you look historically, he's had at least the 73% catchable target rate in each of his last three seasons, according to Fantasy Pros.
21:03So he's one of the types of players who just makes things happen.
21:08He does get a lot of targets near the line of scrimmage, but also a really high rate of downfield targets, which is interesting as well.
21:16So I don't want to take this as, like, a negative for Puka by any means.
21:21Kind of similar for Zay Flowers, who I keep liking more and more this year in basketball.
21:27I keep trying to get more exposure to him.
21:29He's increased his yards per route run in each of the last three seasons.
21:341.86, 2.47, and 2.55. Coming off of a career best catchable target rate.
21:38And, like, history says that'll scale back, but still not necessarily be terrible.
21:42Some other names on the list would be Khalil Shakir, which you'd expect would kind of stay high.
21:48Michael Pittman, Jackson Smith and Jigba. Jamison Williams, which was surprising, but also Amon Ross St.
21:53Brown, which kind of speaks to pretty good offense, good quarterback.
21:57And Rasheed Rice. So I'm less concerned about the guys with high catchable target rates and more interested in the guys with low catchable target rates.
22:05Yeah, it makes sense. And a lot of those guys, you know, like you saying Khalil Shakir, oh, that makes sense.
22:12It's obviously, you know, he's going to see, like, a four-yard A dot.
22:16You know, it's just the way they use him in an offense.
22:20So clearly, it's kind of hard to screw up a target in that kind of environment.
22:25So the last question I have for you, what do you think the main takeaway is here?
22:31Right? Like, everyone just heard a bunch of names, and hopefully you jotted some of those down, and at least made you
22:38think about players a little bit differently. But do you think that we should weigh this more into our evaluation?
22:44Do you think it's already being captured? Or do you think that some people might be overrating it?
22:50You know, like there's a situation with like a Mecca Buka right now, for instance, where it's really easy to look at
22:57what went down with him last year and say, oh, he had a really, and I've done this on the show many
23:04times, you know, like, oh, he had a poor catchable targets rate.
23:08That's going to regress. He'll be a lot better next year, no matter what.
23:12Is there any like major takeaway that you have from the study?
23:16Well, you mentioned, hopefully people jotted these names down and just clarify, all these names that I talked about were in the newsletter.
23:24So if it's still in your inbox, check that out.
23:27And if not, you should definitely sign up because we got some cool stuff each and every week at the Late Round Newsletter.
23:34But, you know, I think it's difficult to know because this is such a small sliver of the puzzle.
23:40And I sometimes don't know. Like, again, a lot of my process is built around regression.
23:45Sometimes I don't know what people are seeing in certain players to make them higher or lower.
23:51One thing that's really interesting, and this is not a catchable target situation, but like Matthew Stafford's touchdown rate is one of
23:58the most glaringly obvious regression spots this year. But for the first time, a quarterback who doesn't rush, who had like an
24:05almost 8% touchdown rate, he's not being drafted. It's like a top 10 guy.
24:10So it's like people are kind of learning. And I don't know if I see it totally in terms of catchable target
24:17data, just because I think something like scoring rate, like touchdown rate is a lot more talked about and a lot more present than catchable target rate.
24:25But like, I think that we're getting smarter as a collective.
24:29And so I do think that this is starting to be factored in more as it's really easy just to, you know,
24:36more people talk about things like catchable target rate.
24:39But again, when like if one source says like if you have three sources and to say this guy was kind of
24:46average and catchable target rate and one source says like this guy didn't see any catchable targets like that's where it gets
24:53hard to like factor this in because it is a very peculiar stat.
24:57So it is one like one thing I'll say for sure is I actually want to factor this in more because again,
25:04the spots I'm always looking for are the things that we can kind of verify.
25:09And whenever I can almost I won't say lazily because like I did the work and like check things out.
25:16But when you don't have to account for like, OK, but if he changes teams, it doesn't really fit.
25:22It's like, yeah, overall, like you see this being sticky enough that there's signal in it.
25:27And I think that we should all be factoring it in a little bit more.
25:32Again, that doesn't mean that we saw 80 Mitchell on the low end.
25:36I think 80 Mitchell is a little bit polarizing.
25:39Sorry, we saw him on the low end for two straight years.
25:43So it didn't necessarily bounce back. I think some people were like, this guy's not good enough.
25:48But you could just as easily say like he's due for like a league average catchable target rate.
25:54You know, for him in particular this year, it's it's it might matter.
25:58He's not going to be like an alpha. We know that.
26:02But when you apply that kind of logic to an Emeka Ibuka or you say, hey, Mike Evans, you know, kind of a weak efficiency season.
26:10But Baker wasn't fully himself. Evans wasn't fully himself in eight games.
26:14Like maybe that's how you sell yourself on Mike Evans having just a massive season.
26:19And I think you can do that while not really getting out over your skis or making things kind of just making
26:26things up and saying, it's going to get better because, you know, we've done the research and it's like historically speaking.
26:32Yeah, it is going to get better for these guys.
26:36Yeah, I love it, man. I love it. Let everyone know where they can find you and the good stuff you're working
26:43on, which is the same stuff that I'm working on for the most part right now.
26:48Yeah, I'm I'm occasionally on Twitter at Godula 13 GD ULA one three.
26:52I'm on blue sky at Godula. And then everything else I do late round dot com late round newsletter draft guide.
26:59Very excited for that this year. Yes, super excited again, July 10th.
27:03That's when it's coming out. We are at the finish line with it.
27:07We're we're working hard. You know, there's going to be some long hours these next two weeks, but it will be out.
27:14Make sure you check it all out late round dot com.
27:17And most importantly, guys, check out the late round newsletter because Brandon is putting so much work into that every single week.
27:25And there's studies like this catchable targets one that he's putting out there consistently.
27:29This just happened to be one that we turned into a podcast because this is just a particularly interesting topic.
27:35But there's a lot of other topics that he's dug into already.
27:39So check all that out. The newsletter is free, so you don't have to pay anything.
27:44But it's all at late round dot com. As always, everyone, thanks for tuning in.
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28:42So bien.

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