1086: The Truth About Draft Capital

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Speaker 1: This is the last with your host JJ zacheris j J Zacherison. What's up everyone, It's JJ zacharyesin in this episode ten eighty six of the Late Round Fantasy Football Podcast. Thanks for tuning in. All of you have heard me talk about draft capital on this show, especially this time of year when it comes to the ZAP model. When it comes to forecasting prospects of the next level, draft capital is the single most important input to consider, and there's a lot of reasons for that. For one, better players generally get drafted earlier. NFL teams they might be stupid sometimes, but they're spending millions and millions of dollars in an attempt to find the right prospect at each draft pick. They're clearly going to be better at picking those players than most. But also, when a team makes an investment, that player is likely going to have more immediate opportunity or opportunity in general. When we're playing fantasy football, volume is everything, and if that player has higher draft capital, there's a higher likelihood to see that volume. Now, clearly it's not that simple, but those are two key reasons as to why draft capital gets the signal that it does. In models, and it's why it's important. But with all that being said, with all this talk about draft capital being the thing that we should care about most, you probably think that it's close to the only thing to care about. But that's not the case at all. On today's episode, the Truth about Draft Capital, Why it's important, but why it's not everything. Now, before I get to the analysis, I wanted to send a quick reminder about the Late Round Prospect Guide. It's launching in less than a week. The guide is over one hundred and seventy pages that covers everything that goes in the ZAP models. There's rankings, there's prospect profile write ups for every running back, wide receiver and tight end at the combine. There's year two profile right ups for the guys entering their second season in the NFL, and more. You can still pre order it right now for fourteen ninety nine over on lund dot com. In six days, that's gonna rise to nineteen ninety nine, so get on that lateround dot com. To help explain the truth about draft capital, I, of course, when into the ZAP Moodel's database. That database has every running back, wide receiver, and now tight end who is either drafted or at the NFL combine since twenty eleven. As I talked about on last week's Mailbag episode, the ZAP model looks to predict the player's B two s, or his best two seasons in PPR points per game across his first three years in the league. Minimum seven games played in a season for it to count, and it throws out the final week of the regular season, so we're only looking at fantasy relevant games to wrap your head around B two s. Imagine a running back scored ten, twelve, and fourteen PPR points per game over his first three years, and he never missed a game, His B two s would be thirteen. It would average his best two seasons of twelve and fourteen. That's what the ZAP model is attempting to forecast, is trying to predict which players will score highest and be and it gives a player some prospect score a ZAP score to help with that. Now. I bring that up because when talking about how important draft capital is, B two s is how I'm gonna measure that importance. You can do this in a ton of different ways. Best season PPR points per game across his first three years, how many top twelve top twenty four seasons the player had I just do it via B two S, and since B two S features three seasons of data on today's show, I'm looking at players who are drafted from twenty eleven through twenty twenty three. That way, they've had a chance to play those three years. Now, I think it's human nature for your brain to go into this linear mode when we talk about draft capital. Maybe not totally linear, but let me explain what I mean. You hear someone say a wide receiver was drafted sixteenth overall. Then you compare that player to someone who went thirty second overall, and then you compare a third player who went forty eighth overall. Those are all wide receivers who went sixteen picks one after another. There were sixteen selections between each pick. But performance versus draft capital doesn't behave in a linear way. For running backs and wide receivers, the positions that we're going to focus on today, it's a downward slope where the first part of the first round that slope is really steep, but then it starts to level out and at some points draft capital is actually completely irrelevant. Now, I want to start with running back first because quite frankly, it's an easier position to model in general compared to wide receiver. When it comes to big investments at running back in the draft, they almost always give us good fantasy production, which is why if Jeremiah loves draft capital just keeps going up, he's actually gonna end up in the legendary performer category in the model this year. I didn't think that was gonna happen at first, but we know that top half of the first round running backs have been unreal over the last fifteen or so years in fantasy football. Since twenty eleven, here are the guys draft in the top sixteen. Trent Richardson, Melvin Gordon, Todd Gurley, Ezekiel Elliot, Christian mcac affy, Leonard Fournette, Saquon Barkley, Bjeon Robinson, Jamier Gibbs, and Ashton Genty and probably Jeremiah Love. All of those guys scored roughly seventeen PPERO points per game or more in one of their first three seasons, except Gent who's only played one season. Even Trent Richardson got there as a rookie. Needless to say, it's not surprising that when you look at the correlation between draft capital and B two S for first round running backs. There's decent correlation. But let's take a step backwards first. Like I said, this database has every running back who was at the NFL Combine or drafted since twenty eleven. Anyone who goes undrafted just gets a default draft capital of undrafted their draft pick is all the same. The R squared between draft capital, their raw pick, and B two S is aboutzer point four to five, which means draft capital explains roughly forty five percent of the variants in B two S outcomes across this entire sample, which is fairly strong correlation for fantasy football purposes. But that's across the whole. I made a thread on Twitter last week about prospecting through data, and one of the things that I brought up in that thread was R squared analysis. You hear data people like myself talk about R squared all the time, and people will email me or hit me up and they're like, hey, JJ, what's the R squared of your model? Now, for those of you who think I'm speaking a different language right now, are squared. It's a statistical measure that tells us how much of the variation in one variable can be explained by another variable. When R squared is one, it means it can explain everything. When it's zero, it means there's no linear relationship between those two variables. So in this case, we're looking at draft capital versus B two S, So we're seeing how much of the variation in a player's NFL production can be explained by a variable. In this case, that variable is draft capital. But people will say, hey, JJ, what's the R squared of your model? And my answer is that doesn't matter without context. If I tell you that the R squared from my model is point four two, you might be like, oh, that's actually not that bad. But actually that's really bad because that's worse than the R squared of just plain old draft capital. And anyone can improve that are squared by adding certain data points. For example, if I removed all undrafted players, the R square between draft capital and B two S lowers to about point thirty nine. Now, just so we're all on the same page, think about why that might be the case is because I'm removing a bunch of undrafted players who are almost definitely gonna do nothing in the NFL, which means they have super late draft capital, they're undrafted, and B two s's of zero one maybe two points. That improves your correlation when they're in the data set. Having the undrafted players in the model improves that correlation. If you change that sample, then are squared changes. For example, first round running backs. I told you that top half first round running backs have been really good since twenty eleven, and they have. That means that the back half after the first round has crappier running backs. Then we'll see some sort of correlation for first round running backs when looking at draft capital versus B two S right, And that's exactly what we see when looking only at first round running backs in is twenty eleven, the R squared between where they were drafted and how they performed in B two S has been point five to six, which is stronger than all of these running backs when you look at round one through the undrafted guys. And that should hint to us that later first round running backs might not be that productive, or I should say they've seen a dip in production compared to the guys drafted in the front half of the first round, because if they were just as productive, the correlation for first round running backs wouldn't be very strong as you'd expect. As you move through the draft round by round, that correlation weakens. Running back is really top heavy. The top guys in the position are doing so much work. They're almost always hitting Round two running backs. In is twenty eleven, they've had an R scored of points round three point one one, And as you approach day three, you start to get into numbers that are essentially just non existent where you can just throw out draft capital and just pick who you want. You can choose two end points here to make your story, to create that narrative, like, for instance, if you look at running backs, pick between picks seventeen and fifty. Since twenty eleven through twenty twenty three, we've had twenty five of them. You know what the correlation between draft capital and B twos among those twenty five running bax is again, pick seventeen to pick fifty, it's point zero zero two. That's nonexistent correlation. What that tells you is that historically there hasn't been much of a difference in production for running backs drafted mid round one through mid round two. But if you add in those top sixteen running backs whoa all of a sudden, that equation changes because remember those guys are doing a lot of the heavy lifting. The R squared goes from non existent to very existent. It shifts a point twenty five. With thirty four running backs now in the sample, Like I said, you can pick and choose your end points here. Like, for instance, pick thirty three through pick one hundred, essentially Day two picks the R squared point zero seven. That's not very strong at all. Pick fifty to pick one hundred, the R squared is zero point zero zero, non existent. It doesn't matter. Now, this isn't to say that draft capital is irrelevant for those players. All things being equal, you'd still probably want the player who goes earlier in the draft. And again, I'm just choosing end points here. You can capture different players at different draft capitals and make it say one thing or another, but one thing here is super clear. The further you move through the draft, the less draft capital matters. Now, another way to approach this topic is through binning. We can just take all the Round two running backs and group them together, and then we can do the exact same thing with Round three running backs, and then we can just compare those two groups, and I think that's probably the analysis that you see most And there's a chance that it's contradicting what you're currently hearing me talk about, but it's not because binning does a different job than our squared analysis does. Our square to saying how smooth this production shift from one draft pick to another. When we're binning, the group of players within that bin can still be pretty chaotic. Like if we were to compare round two to round three players. That means that we're looking at all players drafted between pick thirty three and sixty four and we're grouping them together. But the players within that group could produce in wildly different ways, like a player pick sixty fourth can outperform a player pick thirty third, But when they're bin together, that's not discovered when we group them up, because they're all just one group. When you approach this type of analysis via binning, you'll likely find some differences. For instance, the average B twos among round two running backs has been about ten point seven. For round three, it falls to nine point six. That's not amazingly significant, but it's significant enough. Meanwhile, running backs get fourteen or more PPR points in B two s at a thirty five percent rate out of round two. Out of round three, that's twenty two percent. They get to twelve or more points at a forty four percent rate versus a twenty seven percent rate. You get the picture. In general, a player drafted in round two is gonna be better than a player drafted in round three. But those are also pretty arbitrary thresholds, and far too often, way too often, you get people looking at players who are fifteen to twenty picks apart, and they automatically put that better draft capital player ahead in their rankings. And it's because of draft capital, but realistically it's not that significant in the grand scheme of things. Really, the takeaway here is that draft capital works more in tiers than it does as a precise ranking system, because when you treat draft capital too literally, you end up viewing pick sixty four as meaningful better than pick sixty five. And when you look at the RS squared among Day two running backs, it tells us that production in that range is far more random than that. And then as you get to day three there's some correlation that does exist. Picks one hundred plus to the end of the draft, it's about point one five, which does mean a fourth rounder, for instance, has a little bit more likelihood to hit than a seventh rounder, But when you get into round five, round six, there's really no difference between those types of players and a round seven running back. The TLDR here is at the top of running back draft classes, Oftener doing the heavy lifting. When it comes to draft capital being a huge point of emphasis, you should almost blindly follow and just draft top half of the first round running backs because they hit at such a ridiculous rate in fantasy. After that, don't be too certain about players. Make sure you're looking deeper than just draft capital. Even at running back, where I think the consensus believes that draft capital is absolutely tied to production no matter what, that's just not the case. Now. The same general trends can be found at wide receiver, except it's not as clear cut. It's a little bit more wild wild west. Across the entire sample of players, we see an R squared of point four to eight. Technically, that's better than what we see at running back. Again, that's looking at all round one through undrafted players since twenty eleven, but there's a lot more nuance to the wide receiver stuff. Remember how first round running backs saw really strong correlation because the top of the position has just been so good. Well, since twenty eleven, that hasn't been the case. At wide receiver. The R squared for first round wide outs is just point zero eight. Late first wide outs have been decent compared to early first round ones. Now. Fortunately, it seems like teams have gotten a little bit better about this in recent years, but it's still not nearly as strong as it is at running back. When running backs get drafted early, they almost always produce. There's literally zero correlation for round two wide receivers, and then it's the same for round three, And when you combine the two, the R squared is point zero five, which at face value tells you that there's very little correlation when it comes to day two wide receivers in general. With that being said, round two wide receivers do outperform Round three wide receivers. Their B two s is about two point three points higher. They hit ten, twelve and fourteen p Piero points in B two s at higher rates across the board, but those rates aren't unbelievably significant, and the average for the round two guys, it usually comes down to floor rather than ceiling, and in fantasy football, ceiling is typically the thing that we're chasing. But this continues to play into this idea that draft capital isn't linear and round selection is still relatively arbitrary. Just because a player goes thirty third overall doesn't mean that you should take him in your rookie draft, no matter what, over someone who goes fifty third overall. In fact, this data is telling you that there historically hasn't been that much of a difference between those two players at wide receiver. Now, the interesting thing is when you look at draft capital from twenty eleven to twenty twenty three and you find the R squared for players drafted in the top one hundred versus B two s and then players drafted on Day three, which I'm just signaling as anyone drafted after pick one hundred because it's just cleaner. Keep in mind, for all drafted players that are squared is point three to nine, very similar to running back. We're removing the undrafted guys, but for top one hundred picks at running back, draft slot explains roughly fifty percent more of the B two s variants than it does at wide receiver, meaning running back correlation with top one hundred picks is much much stronger, and that shouldn't be that surprising because of what running back is doing in the top half of the first round. Not to be fair, things have gotten a little bit better at wide receiver during the twenty eighteen to twenty twenty three time frame. Within that range, things have gotten a little bit better. But the reason the wide receiver correlation across the entire sample is just as strong as it is at running back but it's so much weaker with top one hundred picks is because wide receiver is not very good on Day three. Day three running backs at least will give us something a little bit more frequently that can add more variance to the R squared analysis. But you'll often get a lot of zeros from Day three wide receivers, and when guys hit, they'll typically really hit, but there's not enough of them to really drive down that R squared. But look, we've talked a lot about these different areas of the draft and are squared and binning. What am I really getting at here? Well? I think people need to know that while draft capital is really really important. If you're choosing between two players who are in the vicinity of one another, don't let draft capital overtake your decision making. The NFL is better at identifying tiers than ranking players within those tiers. Teams can identify which players belong in some draft range, but the exact order of those players is actually really really noisy. So if you like a player who has picked fifty fourth overall more than a player who has picked thirty fourth overall, go with the guy who has picked fifty fourth overall on your rookie draft. Not only is it more fun to follow your own evaluations, but matth actually backs you up with that move. Realistically, small draft capital differences are usually meaningless. A fifteen to twenty pick difference inside the same tier historically hasn't explained much about player outcomes, and keep in mind round boundaries they're pretty arbitrary. Pick thirty three versus pick thirty five, versus pick forty versus pick fifty. They all often behave more similarly than the round two or round three labels imply, which is precisely why I've always used raw draft pick within the ZAP model. Now, look, if you want this position. By position, I'd say the following top half of the first round running backs. They're extremely safe bets and they drive a large portion of the draft capitol's predictiveness power at the position. Running back starts to flatten after that top sixteen, top twenty range. Meanwhile, at wide receiver, the evaluation with draft capital is a little bit looser. Day two wide receivers often behave like a large talent pool rather than some ranked list. You should generally prefer a player drafted in round two versus round three, but again, you don't need to force the issue with arbitrary thresholds. Great wide receivers they're found throughout Day two lead with your analysis. You shouldn't just rank these guys based on draft capital because it's not nearly as linear as you think. And that's just the truth. That's it for today's show, though, thanks to all of you for listening. If you had subscribed to the Late Round Fantasy Football podcast, make sure you are by stitching for it pretty much anywhere podcast can be found, and follow me on Twitter and on Blue Sky at Late Round QB. I'll be back on Wednesday live on YouTube with a new Late Round Fantasy Football show and it's just me. I'm doing a solo show because David Kitchen is gone this week on vacation. After that, later in the week, I've got a late Round Perspective episode for you guys. Thanks for listening, greatly appreciate all of you. I'll talk to you soon.