What the Metrics Say About the 2026 Rookie Class with Ryan Heath

Every incoming rookie gets defined by a blizzard of metrics, but which ones matter for predicting dynasty success? Ryan Heath of Fantasy Points joins Dynasty Compass to walk through the analytical models he built to rank rookies at wide receiver, tight end, and running back. He explains the specific metrics that predict early career fantasy success, which players in the 2026 class those metrics love, which ones concern him, and why. Ryan drops tons of insights on Jordyn Tyson, Jonah Coleman, Elijah Sarratt, Max Klare, Michael Trigg, Tanner Koziol, Zachariah Branch, and many more.

💡 Key Takeaways

• Yards per team passing attempt and first downs per route run are the most predictive metrics for WRs
• Reception share, missed tackles forced and athleticism score matter most for TEs
• "Yards After" and targets per routes run are critical to RB success
• Raw metrics can mislead; they need to be adjusted for age, team volume & strength of schedule
• Beware "one hit wonders" – guys with a single season of solid production
• Slot concentration and overreliance on screens are big red flags for WRs
• The evolution of the TE role and rise of multi-TE sets have serious implications for production

⏱️ Chapters/Timestamps

00:00 – Welcome & Model Building
05:44 – What the Model Predicts
10:35 – Predictive Metrics for WRs
17:14 – Predictive Metrics for TEs
28:09 – Predictive Metrics for RBs
33:17 – Flag Plants: Coleman, Tyson, Sarratt
41:54 – The Problem with Screens: Zachariah Branch
46:32 – Troubles with Washington, Bell & Hurst
52:27 – TEs Who Shine and Those Who Don’t
56:51 – The Problem with Slot Concentration
1:01:31 – Understanding Tiers Is Key

🔗 Links Mentioned

• Ryan's Rookie RB Rankings 
• Ryan's Rookie WR Rankings 
• Ryan's Rookie TE Rankings
• Follow Ryan Heath on Twitter/X
• Fantasy Points
• Follow Jeff on Twitter/X
• Jeff's Dynasty Rankings at Footballguys
• Footballguys Rookie Draft Guide

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Transcript

Jeff: Fantasy football is a game of numbers, and some numbers matter a lot more than others. My guest today is Ryan Heath from Fantasy Points. He's gonna talk about the metrics that truly matter and how his model identifies prospects with higher ceilings from the ones that have some red flags you may wanna know about. And that's next on Dynasty Compass.
[Theme music]
Jeff: Welcome to Dynasty Compass. I am your host, Jeff Blaylock, the other Jeff B from Footballguys, and we've got a great show today. I am joined by Ryan Heath from Fantasy Points. We're here to break down a bunch of metrics and talk about what's important and what's not to dynasty managers. Ryan, thanks so much for stopping by. I know you've been very busy right around the draft. Why don't you tell everybody what you've been up to and, uh, what your draft week looks like.
Ryan: Hey. Yeah, thanks so much for having me. Excited to be on here and talk some prospects. Uh, yeah. Right now I've just finished writing all three of my gigantic, uh, like model breakdown and rankings articles at the running back, wide receiver, and tight end position. Uh, all three of those are free to read right now on fantasypoints.com for anyone that's curious. It just takes you through my entire model, uh, my rankings at each position for pre-draft dynasty rookie drafts right now. So yeah, I'm just kind of doing the tour right now, going on as many shows as I can to just kind of talk through all these guys and get the word out. So yeah, appreciate you having me on and yeah, appreciate any listeners that are interested in this stuff or want to dive in further. Yeah, you can do it at fantasypoints.com.
Jeff: Yeah, it's a great site. I've been using it for years and following Ryan's work as well. It's, uh, always one of the first articles I read when it comes out, to see what I need to know about the numbers, what's important and what isn't. But before we get into that, I do have to ask you — I mean, what made you think, you know, when I grow up, I want to do math-ing and I want to do it in the fantasy football space?
Ryan: I mean, kind of from when I first started playing fantasy football, I was totally addicted to it and obsessed with it. Uh, I was 15 years old in 2015, which was the year that like every running back in the first round got hurt except for Adrian Peterson, if memory serves. Uh, David Johnson had his insane breakout the next year that like super got me hooked on fantasy. So yeah, just playing fantasy football, kind of realizing there was so much like to the numbers and the strategy that I could kind of dive into and get an edge with. Uh, and yeah, just stuck with it through high school and college, uh, had been writing about fantasy and yeah, math stuff like on the side. Uh, and it eventually yeah, turned into a full-time career, which I'm insanely thankful for. Uh, yeah, it's been a total dream come true every single day.
Jeff: Yeah. And you've even gone further than most. I mean, a lot of people may be interested in diving into the numbers, but you've actually gone through the process of building an evaluation model. And so how did that begin and how has that evolution been for you?
Ryan: Yeah. Building a prospect model is like the final boss for me. Like I had never done it until this offseason, right? This is my first year actually building out an entire model. I had kind of always just, uh, like consumed the work of Scott Barrett and other people around the industry to kind of help build up and create my opinions on rookies. Uh, but yeah, it was just with some encouragement, uh, from Scott, from JJ Zachariason, from some other people to like, yeah, you can do this. You can try your hand at this. Just like, don't be afraid to dive in is kind of what people were telling me and encouraging me. So yeah, I finally did it this year, and I'm pretty — it's been a really fun process, a difficult process, but I'm happy with the results and I'm glad I finally did it.
Jeff: Are you finding that the model's results are kind of confirming the way that you were already evaluating players? Or is it really taking over as one of the driving forces in terms of how you're evaluating players?
Ryan: A model is a tool to kind of help us evaluate a bunch of different data points, like spit them all out into like a total score, right? But it's just a tool. You gotta understand that a model doesn't always account for everything. There are things my model doesn't account for that I might think are important or less important or whatever. So there's always like other, uh, yeah, data points, characteristics that I think matter. And I'm gonna let those impact my rankings kind of along with my model. So it's a big part of my process, but it's not just blindly — I'm following the model ranking in every single scenario.
Jeff: And when we're talking about the model, we're really talking about more than one model, right? I mean, this is not just one thing. You've got models for different positions, correct?
Ryan: I, so it's really three separate models, uh, for the wide receiver position, the tight end position, and the running back position. Uh, yeah, I, they're just built completely separately. They're not like related to each other, uh, in any way. Uh, like some methods are gonna be similar between them. Like I'm adjusting for things like age and schedule, um, in kind of similar ways between some of 'em, you could say. But yeah, I really, the goal at each position is find out what's predictive and use that in the best way possible. And that is different at every single position.
Jeff: And when you say what's predictive — what is it that you're trying to predict? I mean, how does this model demonstrate or show you what you think fantasy success might look like?
Ryan: So it very much is fantasy success. So that is obviously going to differ from people that are more like real life focused in their draft evaluations. Um, but specifically what I'm trying to predict is the average of a player's best two out of their first three seasons, just in terms of PPR fantasy points scored. Uh, the reason for that is I just wanted like the closest proxy to early career dynasty value that I could possibly get. Uh, the point of this model is for people to use it to draft their rookie drafts off of. Uh, generally I want players that are gonna score points and gain dynasty value when I'm making selections. So yeah, that was just kind of the best proxy that I could find, um, just looking through different players and going with different iterations of that in terms of like average of best two or average of all three, or just your best season. Like I found that average of best two was, just kind of as a sniff test, was like the best, uh, proxy for a lot of players I had in mind.
Jeff: So really kind of more of the potential of what these players might be if they're able to use their talent, they get the playing time if they're not hurt. And I guess that would be one reason why you cut out one of those years, because invariably somebody's going to get hurt or not be able to play as much or be behind somebody else. Um, do you think that the model then, because it's aiming sort of at the potential — and if I'm saying that unfairly, please let me know — if it's aiming at potential, does it overstate production a little bit? Or do you adjust for that?
Ryan: I think it does very much care about production. Uh, that's — most like analytical models are gonna be primarily concerned with how much did you produce and when and against who did you produce? Right. That's like what we're thrusting at. Uh, but I mean, draft capital is also a massive part of the model just because draft capital is very predictive in terms of fantasy outcomes. Players that are drafted earlier by the NFL, uh, are on average going to score more fantasy points early in their career than those that are drafted later. So I think honestly, compared to a lot of other models around the industry, I would guess that draft capital is like a bigger factor on average in mine than some of the others. Uh, part of that is because I very purposefully try to not have like a ton of different production metrics, because I think very often one of my like criticisms of the analytics community in terms of fantasy football is that we use a lot of the same metrics that are all correlated with each other, that are all should be telling you like roughly the same thing. But you have 10 of these metrics that are measuring like per route production — like if I have yards per route run and first downs per route run and yards per route run against zone and against man — like all of these in my model, all of these are telling you roughly the same thing. They're highly correlated with each other. Uh, that's just not like great practice at building a model. So yeah, each of my models each have like two or three production metrics at most that are all kind of telling you different things hopefully. Uh, so yeah, on average that kind of ends up that draft capital is filling a bit of a larger hole than it might in other people's models.
Jeff: Yeah, we will dive into those in just a second, but I did want to talk about the draft for a second. This is being recorded before the draft, so if you have me watching or listening to this afterward, things that we may talk about might be very different than what actually happens. But I know, Ryan, one of the things I really like about the way you analyze it is you tend to think about where you believe someone's gonna be drafted — at least are they day one, day two, day three — and you really focus on comparing them to the backs or the receivers, the tight ends that are gonna be drafted in that same area. So you're not trying to compare a fourth round running back to Jeremiyah Love. You're trying to compare 'em to other fourth round backs. When did that kind of aha moment happen, that you think this is the best way to look at this?
Ryan: Yeah, so part of that is just as like a communicator. My job is to like take all of the data and information that I have in all of my spreadsheets and communicate it in a way, in an article that is understandable and feels relevant to the reader that's coming in without any knowledge of what's in my spreadsheets, right? So one of the better ways to do that, I find, is yeah, among guys drafted in this typical range, uh, that might compare in this metric or that metric in a certain way — these are the results, these are the five guys that are around this percentile of missed tackles forced or whatever, uh, on day two of the draft. Uh, just to me it, because you're not coming up with a valid comparison if you're comparing the per touch stats of a seventh round running back to a first round running back. Right, those just mean different things. Uh, teams are just much more likely to give touches to a round one running back than a round seven running back, regardless of what their per touch college efficiency was. Uh, it's just kind of not how teams make decisions. Uh, but yeah, I try to get a little bit closer to like, what are NFL teams actually thinking? What's like the level of investment that they have in these guys? I want to compare them kind of on equal footing. Like it makes more sense to compare Jadarian Price to like a James Cook than it does to compare 'em to an Isiah Pacheco or whatever.
Jeff: Alright, well let's dive in a little bit. You know, when I prepared the show sheet, we were first talking about doing the show, your running back article had not come out yet, so we'll be inserting that in as we go. So don't let that surprise you when I ask about running backs. Let's start with the wide receivers. What is it that you really focus on with them in terms of the metrics that you use and why did you pick the ones that you ended up going with?
Ryan: Yeah. So the first one is receiving yards per team pass attempt. Uh, that stat, it's just, as you would guess, it's receiving yards divided by all the pass attempts that their college team had in that season. Right. Uh, basically what this is telling you is how productive was the wide receiver in the context of their college offense, because we see different college offenses pass at like very, very different rates. Uh, that's one, I think, like one of the bigger stumbling blocks that people have when going from NFL data to college data, is just the team environments are just such a wider range than we have in the NFL. Uh, so yeah, that controls for team passing volume, of course. And then I also adjust that yards per team pass attempt metric for age and for strength of schedule. Uh, because I care how old you are when you produce, because it's a lot easier to produce when you're 23 years old against a bunch of 18 and 19 year olds that you're bigger and faster and stronger and more experienced than, than it is to do the same thing when you are also 18 or 19 years old. Right. Uh, that signal, if you're producing earlier in your college career at a younger age, uh, that tells us you might be better than a guy that's producing when he is older. You also have to probably pass upperclassmen on the depth chart. That is also something that's going to hold signal if your college coaches are deciding to play you above the upperclassmen, right?
Jeff: And that's taking into account what their style of offense is, so that you're not punishing Stanford's tight ends because they don't throw the ball. Or you're not punishing Navy's wide receivers because they don't throw the ball. You're looking at it in that context as well. So I think that helps with that sort of continuum and understanding that it isn't a yes or no, it isn't a — well, he's a wide receiver and he only caught 400 yards. Well, if the team only threw 36 times, 400 yards is pretty impressive.
Ryan: Yeah, that's right. Yeah, the team volume is super important. And also like who they're facing — are you up against Power Four competition, uh, or are you going against like, exclusively future accountants? Um, and all of these things is not — it, I'm not just adding these things in the model just 'cause it makes me sound smart and nuanced or whatever when I come talk about it on podcasts. It's because like adjusting for age, strength of schedule, team volume in all of these ways makes the model more predictive. That's ultimately what we're trying to do. Uh, and it, it's nice, it works out that when we think about all of these additional factors, it just makes the model better at predicting a three year sample, uh, say 2023 through 2025, uh, just based on training it from 2016 through 2021 or whatever. So that's like kind of the iterative process, like the math that's all behind that, that I'm doing and testing to make sure like, yeah, these things actually matter. And they all do actually matter. That's how they end up in the model at the end of the day.
Jeff: That sounds like a lot of math-ing. And so, for folks out there, I should have given you the trigger warning — we are gonna be talking about math, so just be aware that that's gonna happen. Uh, I think too, you know, dynasty managers are looking at age. I mean, they typically look at it just as that — how old is this guy, what is his career runway gonna look like at that particular age? I love how your view of it is quite a bit more nuanced than that. It isn't so much about the player's age, it's about the player's age relative to the players around him and what he's producing. How did your brain get to that kind of a comparison — that it's not so much that he's 23, it's that he's a 23-year-old against the 19 year olds.
Ryan: It's not so much as big a deal to me that a guy is 23 years old entering the league, that there's a difference of a couple years in terms of their like peak value or production window. It really is much more just the signal that it carries of how old were you when you produced. Uh, and this is kind of my gripe with, uh, like breakout age as a statistic that people use as well. Uh, just because it's so binary. Like I would much rather have the information of exactly how much did you produce at age 19, at age 20, at age 21, uh, than just a binary yes, no, were you over a 20% dominator rating or whatever at age 19 or 20 or 21. Like I just think by keeping these things continuous, by just adjusting every single year, it gives you just more of a holistic view of how impressive is this player's production actually. And that's like really the thrust of what I'm trying to get at in my receiver model.
Jeff: And the career first downs per route run — tell me about that one. What is that measuring and why does it matter to you?
Ryan: Career first downs per route run is another production stat that it cares about. Uh, that one is yes, a per route efficiency metric, but what I most found for it was in situations like Ohio State, for example, over the past five years, where there are multiple really good receivers that end up being stars in the NFL. Uh, while like the raw production or the, uh, target share or like the share production wasn't generally as good for these receivers, the first downs per route run was generally very strong for both of them. I kind of think of this as like, if you have two amazingly elite receivers on an offense, it's kind of gonna lift all boats. It's gonna make the offense itself very efficient at moving the chains over and over. And that's what I found is for yeah, the receivers on those types of teams — uh, for like Ja'Marr Chase and Justin Jefferson at LSU, for all these different examples — it's the first downs per route run that was really juiced. Uh, so that's kind of, uh, sort of an efficiency stat and also sort of like a giving credit for efficient offense against target competition type of stat.
Jeff: And how about your tight end model? I imagine you were looking at some different things than you were for wide receivers — it's a very different position and it takes a different kind of athlete to really excel at the NFL level.
Ryan: Production does matter at tight end. I think this is something that's been underrated, uh, certainly over like the previous five years. I think people are coming around to it now as we've had more of these like highly productive college tight ends enter the league and have success — like Sam LaPorta, Brock Bowers, uh, Trey McBride, like Harold Fannin, just kind of like this newer, most recent generation. I think for a long time people were like, eh, tight end production doesn't matter. I just want like big athletic guys that get drafted high basically. And that kind of worked for like a few years. But yeah, the game keeps changing. What is being asked of like an NFL receiving tight end in today's NFL meta is different than it was five or 10 years ago. Just with the different personnel packages that defenses are deploying, uh, the matchups that you're getting as an inline tight end versus as a flexed out guy. Uh, so to actually answer your question, best season reception share is the biggest production variable for tight end. So that's really just how, yeah, how many of your team's receptions, what as a percentage, uh, did you have in your best season? Uh, and then career missed tackles forced per game is my other tight end metric. Uh, so that combines a couple things. It combines receiving volume a little bit for sure, 'cause it's per game, not per touch or per reception or what have you. Uh, and also just the ability to create things after the catch, right. Uh, just, it's a little bit of a proxy for athleticism, you could argue, but it's like on-field athleticism — are you actually making defenders miss in a consistent way? So I found that those were two of the most predictive production stats, uh, for tight ends. I think part of the reason why is that it kind of combines like these two generations of tight ends — like the Brock Bowers types do really well in these stats. Uh, and even like, kind of the older generation of tight ends, even if they weren't necessarily amazing in like efficiency and yards per route run and all of this, uh, a lot of them were at least highly involved in their offenses or were creating missed tackles when they had the ball in their hands. So yeah, I think I've kind of like split the difference in the middle. Uh, maybe there's better ways to do it, split it up into different archetypes, but that's what I'm at right now just for production metrics.
Jeff: And then on top of those two, you also add in athleticism, right?
Ryan: Yeah. Uh, we have our own kind of composite athleticism score at Fantasy Points called SPORQ. Uh, S-P-O-R-Q. It's like a, Scott Barrett made it 10 years ago. It's a riff off of Nike's Spark, I think. But yeah, I took that over. That just, uh, combines a bunch of different combine events, uh, weight adjusted 40 yard dash, uh, just like the agility, the broad jump burst score, vertical, all of these different types of events, uh, in a way that, again, is meant to predict fantasy production. Uh, just because I, my research has still found that the highly athletic tight ends, even above and beyond what can be explained by their draft capital, by teams drafting athletic tight ends earlier — it is still overall predictive of more fantasy points. Um, but that's like another thing that I think probably matters more for like the inline archetypes than like an Eli Stowers, for example. So it, that's still kind of, uh, yeah, just something you have to keep in mind individually when you're evaluating each prospect.
Jeff: Yeah, and it's important, I think, as a model builder that you always wanna try to make it better. I mean, you want it to be as good as it can be, and you don't wanna just mess with it for the sake of messing with it. But I think there's always room to look at something and say, okay, how can we evaluate this better? I love the thought of SPORQ coming off of Nike — I always thought of it as, as the, uh, as the hybrid eating utensil
Ryan: Yes. That as well.
Jeff: Called a spork and spelled a little bit differently. But however it got there, I think it's a pretty deep measure. But I think one of the things too that's really difficult when you're looking at tight ends is their blocking ability. Because if they have wonderful receiving chops but they can't block and stay on the field, then it doesn't matter how well they catch the ball because they're not gonna get it. So does blocking come into your model at all, or is that sort of a post evaluation — you'd say, well, my model has this guy at fifth, but I think he's gonna be third because he's a really good blocker?
Ryan: Yeah, so that's gonna be like after the model, as I'm qualitatively evaluating a player and just what their NFL role is, I will consider that in my rankings. But yeah, it's not explicitly in my model. Where it comes in for me is how plausible of a path does this tight end have to, uh, 65 to 70% plus route share in the NFL? 'cause that's what you really need to hit to be fantasy relevant. Uh, and that is going to be different depending on how good of a blocker you are, right? Uh, like if you are gonna be on the field as the every down tight end, then your receiving skills don't have to be like, as sensational, uh, in order to hit that route share threshold. Right? Uh, you can still do it if you're not a good blocker, but you just have to be so good as a pure receiver that the team is incentivized and convinced to say, okay, we are going to, uh, run our personnel groupings in this way. Uh, we, even if we're sacrificing our run game in some ways, uh, like they just have to determine that it's worth it. And like it clearly is for the Brock Bowers, the Travis Kelce types, uh, for a Harold Fannin — and it might depend on the coach for an Eli Stowers. It's why it's really even pre landing spot, it's really hard to evaluate some of these guys in this sense. Uh, so yeah, I guess that's just kind of my brain dump thoughts. I do care about blocking, but it's much more like post-model evaluating will this guy actually have an every down NFL role, than like an explicit part of my model.
Jeff: And then of course, it's something you can't do before they land, but once they land, do you take into account the usage of multi tight end sets in the NFL? That does seem to be increasing. Of course, we've seen Sean McVay become a new convert of that, using it quite a bit there in LA. Does that come into play at all for you, or is that kind of a let's see what happens, or is that a year two evaluation addition?
Ryan: It does come into play some like, yeah, I'd be lying if I didn't at least think about, or yeah, in some places just write like, hey, if this 12 personnel trend is real, that could provide an out for some, some more of these coaches or some more of these flex only tight ends to get on the field more. I think that's a big part of what we saw with Harold Fannin. It's a little chicken or the egg in his rookie year, but like the team decided, yeah, 12 is one of our best groupings 'cause Fannin is one of our best receivers and we want him on the field as much as possible. He played in line as well and everything, and they were willing to make that trade off too. But yeah, I do think it's a relevant consideration, uh, that more teams are more willing to go into 12 for sure. But yeah, it's just so hard — it's almost not worth evaluating on like the league-wide level until you get to yeah, what team is he actually on, what is this coach's history of utilizing flex tight ends in 12 personnel?
Jeff: Is age as big a factor for the tight ends as it is for the wide receivers? I know athleticism certainly is a bigger factor, but what about age in relation to the wide receivers and the tight ends?
Ryan: Uh, it's not nearly as big of a factor for the tight end, so I'm still adjusting that reception share statistic for age. Uh, but just like the movement that their age is gonna create in the model is not nearly as big as it is for wide receiver. Uh, part of that you could argue is, hey, maybe this is like a small sample size issue — we've had Tyler Warren, uh, for example, have this like super late breakout, maybe literally just he is kind of skewing things a little bit. Um, but I do think there's some truth to it at the very least. There's more examples than that of just the later tight end breakouts working out in the NFL. So it's in there, it's not nearly as big a factor for wide receivers. Um, I don't really get concerned about it until like the super outer extremes. Uh, so for example, Michael Trigg, uh, had effectively like very little production until he was, I think, 23 years old, until his final season. Uh, and I had kind of like a comparison of the history of that exact profile in the article. And there's effectively no, uh, like successful NFL tight ends that had that profile of no real raw production or efficiency until that age-23 and then became efficient and moving to the NFL. It just wasn't really, uh, like a successful archetype in the past. So it enters your mind, um, in that way, but it's yeah, it's not nearly as big a deal as a wide receiver for me.
Jeff: And then with the running back model, what are the metrics that you're looking for there? How are you defining their production for the model's purposes?
Ryan: Yeah, so I did something kind of weird for the running back model. Uh, the biggest production metric that it cares about is what I'm naming yards after per game. So what this basically is, is just all the yards after contact on the ground and all the yards after the catch through the air that the running back accumulated in a given season, uh, as charted by PFF, that's all their yards after, and divided by their amount of games — yards after per game. Uh, this is like very correlated with something just like yards from scrimmage per game, like normal yards per game, uh, or like total missed tackles forced or yards from scrimmage per team play. I just found that it was more predictive. Um, I think probably because it is combining like that raw production, uh, like ability to command a bunch of volume, which we care about for fantasy running backs, and also like layering in some of the creation and efficiency stuff. Uh, that can point to who's gonna be an efficient runner, who's gonna have big plays in the NFL. So yeah, kind of like an all in one metric there. Uh, I do adjust that for strength of schedule. And then the other stat is just their final season targets per route run. Uh, just giving even more weight to receiving ability, which is so important for fantasy running backs in PPR leagues. Uh, just found that final season targets per route run specifically was like the most predictive receiving stat. You'd get similar results with yards per route run or yards per team pass attempt or any of these others, but that's just the one I chose. The one I found the most helpful to my model.
Jeff: Do you do any kind of control for the actual number of routes run? Because there are obviously some running backs who run very, very few routes, get very few receptions, but they could conceivably get a reception on all 18 routes that they run. So do you control at all for volume in addition to that efficiency?
Ryan: I do. Yeah. Uh, so for that one specifically, if you run fewer than 75 routes in a season, I just zero you out for that part of the model. I effectively say if your college team isn't asking you to run even that number of routes, they probably don't see you as much of like a receiving option, and that's ultimately the signal we're looking for. Right. How much receiving ability are you gonna bring to your NFL backfield? So yeah, if you weren't running at least 75 routes, then I just zero out that part of the model or yeah, that part of your score essentially.
Jeff: Yep. Uh, and then how about age? Is age also a factor here for the running backs?
Ryan: Uh, it is, but in kind of a roundabout way. Uh, so I found that when I, I mentioned I adjusted that yards after per game for strength of schedule — I found that adjusting it for age didn't actually help the model. Uh, so that was a like slightly surprising thing to me. Uh, but then what I found was that, uh, ignoring age in those seasons that it's pulling from the model was more predictive if I only looked at their second best season by yards after per game rather than their best season. Uh, and what that's kind of doing is it's just penalizing a lot of these running backs that usually in their final season, after doing nothing throughout their college career, like finally take over a backfield as a fourth year or a fifth year senior and become very productive. Like Mike Washington would be the prime example of that. Or an Emmett Johnson, for example, right. Uh, so I kind of coined this — I just said that these are one hit wonders, uh, is the term I use throughout the article. Um, and I kind of dive into the history of those. But yeah, there are a lot of like bust profiles that are very specifically — you do nothing until your final year and then you have a really productive final year. Uh, just doing it in that way both sort of controls for age, at least the experience level of your production, and were you able to actually produce on multiple different versions of a team? Right. Uh, running back is such an environment dependent position, even at the college level — yeah, your blocking, your team's game scripts, all of this is gonna factor so much into your production. It's so volume dependent that if you couldn't produce it on at least multiple different versions of your team, of your backfield, there's probably some signal to that, that you needed like the perfect storm of backfield competition, of scheme, of offensive line play to actually produce. So yeah, it penalizes those one hit wonders in that way pretty heavily.
Jeff: So taking a little bit of a step back — you've got the class, you've ranked all three positions in these articles, you've used your model, you've used your other sources and your own eyeballs and judgment. Who, I mean, obviously there's key players — Jeremiyah Love, I assume, is your RB1 because he is everybody's RB1, there's no reason for him to not be the RB1. So we don't need to really necessarily hit those kinds of guys. But who is it that maybe in that second or third tier of guys who really rises up, uh, in your class and the view of them because of some of the metrics that they have and what your model has to say about them? You can talk about any position here or any folks, just kind of a free for all from the three positions.
Ryan: Sure. Uh, so at running back, I'm guessing the guy I am gonna be most above consensus on, just because of the model, is gonna be Jonah Coleman. So he is the RB3 in my rankings. Uh, and in just overall like pre-draft dynasty rankings, I have him I think at the 1.11, 1.12, around there, and like very close with Jadarian Price — I think I'm relatively a little bit lower on him than at least the NFL and maybe like the broader dynasty community. Uh, the reason for that with Jonah Coleman is kind of twofold. Uh, one is that he was very productive across multiple seasons, which is something that you can't say for a lot of the running backs in this class, right. Uh, so kind of wherever he went, and especially if you go season by season and like break down his efficiency against the other players on his team — like he has always looked pretty strong as a runner, as a pass catcher. The targets per route run in his final season was definitely there. Uh, and yeah, he and Jeremiyah Love are the only two running backs in this class to average 90 or more yards from scrimmage per game across multiple seasons like that. That's something that my model's really gonna like. Uh, so yeah, he's up there for me. Uh, obviously like the, the fear with him is he can fall in the NFL Draft. The athleticism is a question mark. Like the obvious downside comp to me is like Zach Moss, which is maybe the NFL just decides this guy is not fast enough, uh, or explosive enough to be worth giving a featured role to, and he kind of spends his career as a theoretically very fantasy friendly backup. Uh, I don't think that's gonna happen. It is totally within the range of outcomes though — this class is very weak. Like that, yeah, I just always have to hedge this anytime I say I like a guy in this class.
Jeff: Yeah. In this class is the important words — in this class I like this guy. Yeah.
Ryan: But yeah, but the upside for him is genuinely like a three down bell cow that a team could just give like yeah, top-12 running back type of workload to. I can totally see that for him as well. So yeah, Coleman is probably my pre-draft running back kind of flag plant. Uh, at the wide receiver position there, I'll give you two names. Uh, this is at the top of the class obviously, but it's a bit against consensus — I have Jordyn Tyson as my wide receiver one.
Jeff: Yeah. Yeah.
Ryan: Uh, the reason for that is mainly because he just has the most impressive production profile to me. Uh, we're recording this, uh, about an hour before the Jordyn Tyson pre-draft workout happens here on Friday, April 17th. Um, so we'll see how the draft capital and everything goes with that, that I think it really hinges on. Yeah, just his health and how that looks for teams. But yeah, his production profile is excellent. Uh, he has one of the best freshman seasons in this class, uh, by yards per route run, excluding screens. As an 18-year-old, he's on a top-six list that includes George Pickens, Brock Bowers, Amon-Ra St. Brown, uh, and then has, of course, the knee injury — uh, tears, not breaks — uh, destroys three ligaments in his knee.
Jeff: You tear them, snap them, but you don't break 'em.
Ryan: Uh, and but then comes back in 2024 and has the most impressive season by yards per team pass attempt of the entire class after that knee injury. Uh, breaks — well, injures his collarbone towards the end of that season, probably the reason he doesn't declare early, and then in 2025 keeps up the raw production at least until he has his hamstring injury. Uh, obviously is dealing with Sam Leavitt taking a step back, playing through injury himself as well. The efficiency comes down in 2025. The raw production comes down overall in 2025 post-injury, but he just hit like the highest production peak of anybody in this class. Uh, even accounting for strength of schedule and all these other things we've discussed, especially accounting for age. So pre-draft Tyson is my wide receiver one. The top three are very close to me — between him, Tate, and Lemon, I honestly, I don't usually do this, but they may just shuffle based on landing spot after the draft. I think they're all comparable prospects to the point where that would be okay with me. 
Uh, but another wide receiver kind of a little further down that I'm gonna be way above consensus on is gonna be Elijah Sarratt. Uh, so I understand all of the kind of concerns that like the film side of the community has around his athleticism — can he separate, is he just like a contested catch type of guy that is benefiting from playing with Mendoza and in the Cignetti offense his whole career? Like I get all of that, but his production profile is just on a totally other level compared to every other day two or beyond wide receiver in this class, to the point where I can't ignore that. He ranks as my WR7. I only have him behind the guys that are expected to go on day one. Uh, but yeah, just across his entire career, even when he was at James Madison, uh, it's a little tougher in a non-power conference of course, but even if you compare him to non-power conference players before age 21, he's on a top five list by yards per team pass attempt with Michael Gallup, with Courtland Sutton — two of the only non-power conference wide receiver hits we've had recently. Uh, and then goes to Indiana, keeps up his efficiency that he had at the much lower level, which is just impressive to me. Uh, was behind only Jeremiah Smith in first downs per route run this past season among college receivers. So yeah, just a lot of the per route efficiency, the overall production looks really strong for Sarratt. I recognize that this is like a 50/50 bet at most. This can totally be like Denzel Mims all over again type of deal. But I like him in like the early second round of dynasty rookie drafts right now as kind of a risk/reward swing.
Jeff: Yeah. Upside here. I think both those guys are who you mentioned, right? I mean, to me the reason you put Tyson in front of the other two is because he seems to have that bigger production ceiling. He had it in college. I've seen a lot of chatter about the injuries. Of course, as you know, we'll know a lot more in an hour and a half of real time this morning. Uh, so this will be out long after we know what happens in Tempe. But I don't love that the narrative around Tyson has been about injuries, as though he's the only wide receiver in this class who can get hurt. Uh, and I think maybe because some of the people leading this charge were really high on Ricky Pearsall a couple years ago, and that has not panned out very well so far. But that nonetheless is, is a little unfair, I think, to Tyson. I mean, injuries are not necessarily habitual. They sometimes they're just a matter of bad luck. Uh, and you also know it wasn't just the injuries in Arizona State — his quarterback regressed, the offense regressed, the defense couldn't get off the field. I mean, these are the kinds of things that come back hurting somebody who may very well be the actual best player in the draft from at least a fantasy perspective. Not maybe a real football perspective, but from a fantasy perspective. And of course, that's what we care about. But before we move to tight ends, I did wanna address something — it's later in the show sheet, so I'm going outta order, but that's you, it's normal. Um, you talked about for Tyson, you said excluding screens. And you use that — you either exclude screens or you look a lot at screens — at a number of your different profiles. What is it about screens that makes you look at them differently than other routes and other production?
Ryan: Yeah. So first I'll say, within my actual model, I am not excluding screens. Uh, I found that it was basically the same whether you included them or excluded them across most stats. So erring on the side of like, let's not make things too complicated and overfit things a ton — the actual model has screen plays and such included in it. Um, but yeah, when I am evaluating a certain player, I might look at, okay, what did he do with screens and without screens? Because, uh, for Jordyn Tyson, that's actually a pretty good example of this. Yeah, it makes sense that the coaches are going to kind of manufacture like these easy button screen touches for Jordyn Tyson — he's clearly the best player, the most dynamic receiver on the team. That's not necessarily gonna be the case in the NFL. Uh, Tyson's yards after the catch metrics are actually pretty bad for, given the amount of screen work that he got, right. So yeah, when he is on an NFL team, we can't like count on — oh, he's actually gonna get the Rashee Rice treatment, the four screens a game that just juices his PPR fantasy points. Right. Uh, so that's part of it — that with a lot of these profiles, while in college they may just kind of automatically absorb all this screen work 'cause there's no other real good alternatives on their team. That's way less likely in the NFL. Uh, and the other part of it is just if we're trying to evaluate how good you are at earning a target, at like running a route against a defender, uh, creating separation, getting open, earning a target — then yeah, your production on screens isn't telling us much about like that aspect of playing the position. And that's like really at the end of the day what you need to do to be a good fantasy receiver — you on an every down basis, you have to go out and like run a competent route and earn a target and catch it and score fantasy points. So yeah, it's not like the number one thing to me, but it is something I look at if I am looking at a list of players by yards per route run — like, let's see what happens when we remove screens from this. Uh, it's just like a kind of another thing to consider.
Jeff: Is there anyone in the wide receiver class who, because of a heavy reliance on screens, concerned you? Anyone that concerned you because of that sort of screen usage or screen dominance?
Ryan: Uh, the poster child for this is gonna be Zachariah Branch in this class. Uh, it's extremely like bleak when you just look at the percentage of his production that came on screens. Uh, so I've got the list — highest percentage of targets that were screen targets, uh, in your college career. This is among power conference wide receivers that have been drafted since 2015. Zachariah Branch leads all of 'em with 43%. 43% of his college targets were just screen targets. Uh, the next seven names on that list are Ray-Ray McCloud, Anthony Schwartz, Amari Rodgers, Kadarius Toney, Rondale Moore, Dominic Lovett, Wan'Dale Robinson. And you'll notice a lot of those guys were like roughly day two players around where Branch is probably going to go. Uh, yeah. For, at like that outer extreme for me, that just kind of says — I think in Branch's case, it's partially that he's just not big enough, not physical enough to kind of win in the way that a typical receiver does. Also because like, hey, he was the number one ranked prospect in his recruiting class, all these coaches kind of probably had like some pressure on them to like, we need to use this guy in some way. Uh, he certainly with the ball in his hands — not saying it's that he's bad or whatever, but that skillset doesn't translate to this is gonna be a high volume fantasy wide receiver most of the time. Uh, so yeah, pretty big red flag for Branch in that case.
Jeff: And before we move on to the tight ends, uh, anyone else in the receivers or among the running backs who aren't faring as well in the metrics that you are really paying attention to and that you may be more down on than consensus as a result of that?
Ryan: Uh, yeah, it's a hard question 'cause I feel like I'm down on a lot of this class, but yeah, to —
Jeff: We all are. We all are, Ryan. It's okay. You can be part of the Debbie Downer Club with me and everybody else. It's okay.
Ryan: Yeah. Uh, to pick out a couple of guys — at the running back position, Mike Washington is probably gonna be the biggest one. Uh, he is my RB4 in my rankings, but I really wanna put Emmett Johnson ahead of him. I really wanna put Nick Singleton ahead of him. Uh, this is just based on projected draft capital, is like the only thing that's keeping him up here. Uh, pretty much in every way. Uh, so we already talked about how he was a one hit wonder. Uh, he got outperformed by Seth McGowan, a day three running back in this class, the year before. Uh, was much older than everybody else when he was having his productive season. Um, all of those are poor indicators. His per touch stats are really rough, especially missed tackles forced per touch, uh, is the second worst mark among day two running backs dating back to the 2015 class. Uh, right between Tevin Coleman and Matt Jones, which are not guys you usually wanna be between — not a lot of hits at the bottom of that list. Uh, even like, kind of his calling card — like the people that like him, I get this when you watch him for sure, is that he does create big, explosive plays. Uh, even if he doesn't look like a 4.3 guy on tape, that that is in his skillset. Uh, but even his explosive run rate over his entire career is like really, really low — 12th percentile among day two running backs. Like it just wasn't happening, uh, before that final season. Uh, even in that final season, it wasn't that strong. So yeah, he's just a guy where all of the data kind of says that yeah, he's not that good of a running back. Uh, I get it, the athleticism is great. It is sort of partially predictive at the extremes for running backs, but we also have so many, like — Isaac Guerendo, uh, even Isiah Pacheco — like it got him work, but where has that gotten him now? It's gotten him to being a backup. So yeah, my comp was like Isaac Guerendo essentially. I could see him develop as a receiver. And most importantly, I could see a team say this is gonna be our plan at running back this year. And that very well could be way more valuable than whatever Emmett Johnson or Nick Singleton are getting themselves into after this draft. So he's gotta be my RB4 for that reason. But like, yeah, if I was an NFL GM, he would be much further down my board. Uh, what did you ask for? Another wide receiver that I'm —
Jeff: Yeah, if you have one — if there's another one you were down on, uh, maybe more than consensus.
Ryan: Um, let's see. There's, yeah. As I said, I'm down on like every wide receiver. Uh, Chris Bell is maybe a name to bring up here. He's been kind of a trendy sleeper at different points. Of course, I've been told — and I will say this, I do not pay, and you can feel free to throw out my opinions for this reason, I will not be offended at all — I do not pay attention to college football before January, February, really, before I get into like this rookie evaluation mode. I'm totally focused on the NFL. So I'm told that Chris Bell was considered like a very likely or potential round one wide receiver, uh, months ago, right before the ACL tear. Uh, I just don't see that at all in his profile. Uh, I rank him as my WR10. I've got guys like Chris Brazzell, Germie Bernard ahead of him. Uh, I just don't see it with Bell. Uh, most of the production was happening like later in his career at age 20, age 21. Uh, he's still only like sixth or seventh best in adjusted yards per team pass attempt among all of these. I just kind of, yeah, I didn't really see like the ceiling to his profile. Um, so yeah, he's one I'm gonna be down on. It also of course doesn't help that, uh, you're coming in like much later into an NFL preseason. Then it's like, how likely are you actually to climb a depth chart in year one? Like we saw that with Jonathan Brooks — like, not very likely. Uh, I learned that lesson the hard way a couple years ago. So yeah, he's one that I just don't see it with. I know he has his fans. Um, and then like, yeah, pick another day two wide receiver's name out of a hat. I probably don't like them that much. Uh, Ted Hurst — I had kind of similar issues with him. Like, even against worse competition and not producing really at all until later in his career.
Jeff: In his career. Even though, like you would think that if you're gonna get drafted on day two, you would be able to produce it at Valdosta State as a freshman or as a sophomore, right. Like, I was shocked to see that he really didn't, uh, in those seasons.
Ryan: Um, yeah, just kind of all these guys — Malachi Fields, Zachariah Branch, Skyler Bell is like probably the biggest example of like, you didn't produce until you were at a really small school much later in your career. Like you couldn't, uh, yeah, climb the depth chart at Wisconsin in any meaningful way, when there were no like really meaningful receivers ahead of him in his second and third year there.
Jeff: Well let's go tight end real quick here. You know, who is shining for you in terms of the metrics that you're looking for, and then who's got your concerns? Who are the red flags for you?
Ryan: I'll give you a few that I, so I'm like weirdly more into the tight end class — there are so many of these like kind of day two, day three, borderline tight ends that I'm intrigued by, uh, at least some of their production metrics, uh, by reception share. The guys that I'll point out that are past like the top two that everyone constantly debates and talks about — Max Klare had an excellent reception share in his second to last year before he went to Ohio State. Right. Uh, of course, insane target competition there — Jeremiah Smith, Carnell Tate. Like I wouldn't expect him to produce a lot there. But yeah, all of his kind of market share metrics were incredible before going to Ohio State. So I'm intrigued in that way. I think he's at least plausibly like a Y-tight end, as an inline player too, so that helps. So he's my TE3. Uh, Sam Roush is a guy that no other data person is into — I am the only data guy that likes Sam Roush. I have kind of been learning, but his reception share was also really strong, uh, at Stanford across a couple of different seasons. Uh, before age 20, he's on a list with Brock Bowers, Sam LaPorta, Jake Ferguson, Hunter Henry, Oronde Gadsden. And then the two misses are Ja'Tavion Sanders and Jaylen Samuels — to hit an 18% reception share before age 20. Uh, and then yeah, it's kind of in his final couple years, even competing against Elic Ayomanor, uh, had like pretty strong reception shares. The efficiency was not there. That's what every data guy hates, is that by yards per route run, targeted passer rating, all of these — it's really rough. But it's freaking Stanford. That offense was insane. It was like the same complaint people had with Elic Ayomanor. Uh, and sure, partially that — yeah, it turned out that Ayomanor hasn't really done much in the league yet. But yeah, I am okay to like, excuse that away if he's actually commanding volume. He's freaking huge, like obviously fits in as an every down tight end. So he's a fun one. Uh, and then Tanner Koziol — I say he looks like a giraffe when you watch him play. And so I totally get why the NFL is a little suspicious of this guy, but he has two of the top seven seasons by tight end reception share since 2017. Joining him on that list is Harold Fannin in 2024, uh, two Trey McBride years, uh, Tyler Warren's senior year, and Michael Mayer in 2022. So like a really productive list of NFL tight ends. Uh, Koziol did it at two different schools — in a power conference and in a non-power conference. Uh, some of his other stats are interesting too. So those are like three guys that are intriguing to me that I'm gonna be above consensus on. Uh, in terms of like below consensus for tight ends, uh, Michael Trigg is probably the biggest one. And I kind of said why earlier. Um, his missed tackles forced stats are awesome, uh, but he just didn't do much until like very, very late in his career. There's effectively no examples of someone as old as him to not hit two yards per route run until then and then do it at 23 going on to become successful in the league. Like the only comps are Luke Schoonmaker and Cade Stover, essentially from the past few years. So that's like a little bit rough for me. Uh, all the character stuff is just like annoying with him too. Uh, his vertical was one of the worst ever recorded in my database as well. There's like no successful comps really until you go back to, like, Randy McMichael or Jermichael Finley, who were like the closest you could get in terms of having a vertical as bad as Trigg did at his pro day. Uh, so yeah, but he's someone I'm lower on. He's like my tight end 10. Uh, I have him ranked at like the early fourth round of rookie drafts, but that's someone that a lot of data people, I think, are more into than I am.
Jeff: There is one other stat I did wanna cover with you because we haven't really mentioned it. We've talked about screens, but it's slot concentration and why that would be a marker for you if a player does a lot of work in the slot. Uh, and then is there, for lack of a better word, a good value for slot concentration? Or is it just entirely dependent on the offense that they are a part of?
Ryan: So I'll say a couple things. Uh, number one is that, as we mentioned earlier, kind of the trend in the NFL right now is heading towards 12 personnel. Uh, of course there are still teams that are gonna primarily be in 11. There are spots where these guys can be close to every down players. But good to know that like the background is there are fewer and fewer teams that we can expect to have a full-time fantasy viable slot receiver that never goes to flanker, never goes out wide into receiver sets. Right. Uh, so that's good to think about. Another good thing to think about is that the, uh, just the hit rate on guys that are pretty much exclusively playing in the slot in college is really, really poor after round one. Uh, there have been 50 wide receivers drafted on day two or later that had over 70% of their career FBS targets in the slot. Uh, out of that group there are exactly two 1,000 yard receiving seasons, uh, from Hunter Renfrow and Christian Kirk. Uh, and there's actually a 1,000 yard rushing season, which was Antonio Gibson, which is what makes that stat really funny. Uh, but yeah, like the names on that list are just really rough. There are just so many of these guys that, if primarily all you could do in college was be in the slot, that's probably also true of you in the NFL if you're not like a day one level prospect. Uh, and that yeah, that lowers your fantasy ceiling. If a guy is primarily producing in the slot, that should lower your confidence on his evaluation of his production from like an analytics perspective. Uh, so this probably most applies to Makai Lemon, and I will say in round one it's less of a big deal than it is in round two and beyond. But yeah, like a lot of these late round one, early round two busts have had a lot of their career receiving yards come in the slot, or specifically come on slot fades as well as on screens. So the list I had for this — even if you just look at round one wide receivers since 2015, by highest, uh, yeah, percentage of their receiving yards on screens and slot fades — it's Jaylen Waddle. Uh, obviously great player, worked out. Kadarius Toney, like perfect cautionary tale for this. Uh, Jordan Addison — good player, not really like amazing fantasy asset at the next level. Uh, he's with Justin Jefferson and all that, but not like a next level amazing producer or anything. Makai Lemon's right after him. Uh, Jameson Williams — the weirdest prospect ever — after him. Treylon Burks, the other —
Jeff: The other cautionary tale —
Ryan: For yeah, like the fake like slot and screen production. And then Jerry Jeudy, right? So it's just like a very up and down list. It should just lower your confidence in a guy's production profile. Uh, once you flip over into round two, it gets awful and it becomes like every single like analytics hype train prospect is just like, shows up on that list. That's where your Elijah Moores and your Parris Campbells show up. Like all the guys that we've gotten hyped about over the years. Uh, Wan'Dale Robinson, who eventually kind of came around this past year, but early career did not have the fantasy production commensurate with his college production. You've got AJ Brown and Luther Burden as your hits from kind of that slot heavy round two receiver group. Uh, but yeah, overall it just, it's kind of rough. Like it should just lower your confidence in the eval. It's why, uh, Makai Lemon is my wide receiver three right now in my rankings. He could totally be my wide receiver one post draft. The overall profile is really strong — not on the level of like a Jaxon Smith-Njigba, for whom I would've just said whatever, the profile's so strong, I don't care. Uh, but yeah, for Lemon, it's just a little bit of added uncertainty. Um, and everyone else after him that's slot heavy, kind of on day two and later — it just, you need to understand the ceiling is probably a lot lower in the NFL for these guys.
Jeff: Yep. All really good stuff. Um, you know, we've thrown a lot of math at folks today, a lot of numbers, a lot of concepts about stats. Do you have any sort of capstone words of wisdom for how dynasty managers are supposed to use this information, how they're supposed to handle it, how they're supposed to absorb it, and what it all means for them?
Ryan: I think the biggest thing when you're playing Dynasty or you're drafting off a set of rankings or a model or what have you, is just understanding number one — tiers, right? Like I have my rankings tiered, uh, and that you are meant to use the tier. Uh, I am totally cool with if your like, risk tolerance is a little bit lower than mine. Mine is generally pretty high. Then I could understand where you'd say, well, Carnell Tate's in the same tier here as Jordyn Tyson. I think Tyson is a riskier prospect for injuries or what have you. I'm just gonna stick with Tate, uh, or especially pre NFL Draft when Tate's draft capital is like the most locked in — I totally get that, right. Uh, but yeah, generally that extends into everything that I am doing in my analysis, is with a range of outcomes in mind, right? I want to do the best I can to tell you what the range of outcomes is for a Jordyn Tyson, uh, for a Jadarian Price, for whoever, right. Uh, and I might be wrong at times, of course, but it's not so much like just an ordinal ranking — this guy is better than this guy, you should always know that he's gonna be better than this guy. It's just, I'm doing my best with all the information we have to project like the ceiling, the floor. How can this go well, how can this go poorly, and put those into rankings based on how I value these profiles in Dynasty, that might be different than some people. Uh, I'm a quarterback hater in Dynasty. I'm gonna have Fernando Mendoza at the 1.05 in rookie drafts, kind of no matter what happens with those other three wide receivers. I'm gonna have all of them above him just 'cause of how I view the position and risk and upside and everything. Right. So that's like, yeah, I do the work and I show as much of my work as possible to, uh, give you those tools to bring it into your process and how you value some of these different positions or archetypes.
Jeff: Uh, that's awesome. Thanks so much, Ryan. Remind everybody one more time where they can find you and your excellent work.
Ryan: You can find me over on Twitter at @RyanJ_Heath and then you can find all of my written work, uh, but especially my yeah, pre-draft profiles of the running back, wide receiver, and tight end class over at fantasypoints.com. All three of those are totally free reads. And then yeah, as we get into best ball, redraft season, all of that as the summer goes on, all my stuff will still be over at fantasypoints.com. That's where you can always find me.
Jeff: All right. Thanks so much, Ryan, and thank you for tuning in on YouTube or listening on your favorite podcast platform. This has been exceptional stuff today, and hopefully you enjoyed it, learned a lot from it, and you can take some very good actions in your rookie drafts, uh, from everything you've heard today. So please like, please subscribe. Uh, the best thing you can do to help this podcast grow right now — just go over to Apple Podcasts, give us a five star rating, and drop a really nice review. That helps us a lot. If you're watching on YouTube, please comment — I do respond to every comment that comes on for the show. And we will see you next week for another great episode of Dynasty Compass.
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