top of page

An Introduction To Mold Scores; a Data Solution To Film Grinding

The process of evaluating football players is generally very time-consuming. For the devy community, this presents a large problem being that the player pool is so much larger. If you're a film grinder it could be 100s of hours depending on the workload. Which if that's your thing then great! I enjoy watching film as well, but a lot of people are unable or simply do not want to invest such a large amount of time into Fantasy Football.

Grab a 10% off discount on FTN's stellar set of tools to get you the edge and help you win big money all season long. Use our promo code: ASTRO

This issue was part of the influence toward me creating my Mold Score - a 4 part system to find how good a player is in different aspects of the game, and ultimately illustrating their overall talent level. The idea behind my Mold Scores was finding a WR's role through athleticism-adjusted production. For example, if you want to be a good deep threat in the NFL, then not only should you have good deep production in college, but you should also have the straight-line speed to back it up. Or maybe you're a big jump-ball receiver, then you would want to have a high maximum vertical reach with the player's frame and vertical jumping ability considered. With my 4 Mold Score types I believe that I create a much fuller profile portraying how talented a player actually is while identifying strengths & weaknesses.

After I have each individual mold, I combine them all to get the players' Mold Score, which weighs each type by its current importance to NFL Production based on my data set. Not only is it helpful as a predictive stat, having the separate categories helps understand more about the player easily. The 4 Mold types are Deep, YAC, Jump, and Separator, each representing a way that a receiver can win. As an example, here are AJ Brown's Mold Scores:

The yellow bar represents A.J. Brown in each category and the red bar represents the average score for the top 10 receivers since the 2018 draft class. And as you can see A.J. scored pretty well across the board. Now with this tool, I am able to find the Mold Scores of college receivers, essentially getting eyes on a player without watching them (*NOTE* I do watch film and have differing opinions to these at times but in general they are pretty accurate). But before we get into current college receivers I want to dive more into the details of Mold Scores.

My sample is small, being only since the 2018 draft class, the Mold Scores require advanced metric inputs that were unavailable prior to the 2017 college season. Because of this, it is very important to continue to update these yearly until I have a much more significant sample to go off of. The outcome measure for success is Pro Football Reference's NFL AV (Approximate Value). For all of my work you see in the future, all pre-draft models are based on AV, because I feel it is better at judging a players' talent, but all of my post-draft models are projecting PPR PPG. I will make a clear distinction between the two in the future, but I felt it was worth mentioning now. The r2 for my overall Mold score is a 0.29 which is pretty solid compared to other stats. Now, as with any stat, I do not suggest using Mold Scores alone for evaluation. In order to give this more context based on my sample, here are how some other stats matchup vs my Mold Score.

It might not be totally fair to compare Mold Scores to these just based on the fact it has so many more things going into it, but nonetheless, it is the most predictive of these in my sample. I will get to WAV% another time in an article, but it is basically my solution to Dominator %. So now that I have all of that covered I am going to show the top grades for each mold type and then the top 20 Overall Mold Scores from the 2018 draft class to 2020. Then I will go on to show my scores for the 2021 class, as well as preview some of the current top college receivers.

First up here is a slideshow of my Deep Mold Scores, followed by YAC, then Jump Ball, and then Separator. It took a lot of tweaking for me to get to this point with these but I'm very happy with the results overall. The YAC and Deep Molds can't get much better than where they are at currently, but there might be some room for improvement in the future with the Jump Ball and Separator Molds.

Now that we've seen each mold type individually let's take a look at the top Mold Scores as a whole. In terms of how each type is weighed, Separator is currently the most important type, followed by YAC and Deep which are about the same, and then Jump Ball which doesn't have a ton of correlation in my sample.

So a relatively mixed bag here but with some very strong signals. 1st would obviously be Ruggs as #1. Not only would I say don't give up on Ruggs yet, because it's been just one season, but the reason he has the top spot is the combination of him being ridiculously athletic as well as efficient production-wise. All my individual Mold Scores are based on efficiency stats only. For my whole evaluation process, bulk career production comes more into play in order to show what a player has done, but generally I feel as though my Mold Scores show how talented a player is. Which again is why I'm preaching that this should only be part of your process. Once you add in things like level of competition, market share, and breakout year (which by the way you should be using breakout year not breakout age but that's a subject for a different time), players like Ruggs and Andy Isabella start to fall. Although Ruggs doesn't fall much….but the subject of my pre and post-draft models are for a later date. What I really love about these results is that it likes players that most analytical models typically do not. The biggest examples of that being DK Metcalf and Terry McLaurin, who, off raw stats, had very underwhelming college careers, but my Mold Scores still loved them. Now let's check out how this looks with the 2021 Receiver Class.

So again this is what I mean by not using this stat strictly, first 5 look reasonable then you get the highly efficient athletic players. But this stat is not meant to be an overall all possible context considered model. These players that would obviously get knocked down by draft capital are the guys to be looking at as late sleepers though, depending on what their NFL landing spot was obviously. If you were following my account already during the pre-draft process, odds are you saw me talk about Kawaan Baker, in deep leagues he is an amazing buy at value that presents huge upside. From analytics to film I was in love with him throughout the draft cycle. His Mold scores definitely back that up scoring super well-rounded and still above average in every area. Definitely a good amount of sleepers to keep your eye on here with Marquez Stevenson too, I think he can work his way into the rotation, and he presents special teams upside as well. I also think you should be buying Amon-Ra right now, not much competition and he is such a safe player to feed targets to. But now last, but certainly not least, let's take a look at mold scores for current college 2022 & 2023 draft-eligible receivers.

For this part, I want to go through and give my thoughts on each player in the top 5 here, in terms of their scores and as prospects in general.

Garrett Wilson: Top Mold Score here with the top separator as well, which is the 5th best since the 2018 draft class. I think Wilson is better at YAC than the formula gives him credit for, but other than that I feel as though this is a good judgment of him. For me, Garrett Wilson has already solidified himself as one of the top receivers in college football, super-safe player.

Reggie Roberson: One of the fastest receivers in college this coming season, and his deep mold reflects that. What is most surprising is his Jump Ball score. I have seen him go up and get it in before but wouldn't classify it as one of his strengths. Not a super high-end prospect, but one with a very high ceiling and could garner decent draft capital if he puts together a good season.

Bru McCoy: Former top-end recruit that has shown flashes of great athletic ability in his limited time. Was highly efficient last year and that reflects with his score, but I expect a pretty significant drop-off next year from these scores. I don't think he is nearly as good of a separator as it is giving him credit for, and without that, his profile isn't that great.

Chris Olave: I'm definitely lower than consensus on him. These scores do reflect his game decently well, but I do believe though that his separator is naturally inflated a bit playing in that offense (same for Wilson). I doubt Olave is ever anything more than WR2 for a team in the league, safe but limited upside in my opinion.

Marvin Mims: Only 2023 Receiver in the top 5. I think I'm slightly higher than the consensus on him, but I'm definitely not in love. This season will prove a lot for him in that regard, if he can come in and command the target share in that loaded Oklahoma receiver room then he's someone we all need to be taking a bit more seriously.

And lastly for all my fellow stat guys reading that would like to implement these into their database, here is a link to my spreadsheet:

Thank you all for reading, this is the first of hopefully many articles of mine you’ll be seeing here. For any questions please feel free to dm me on Twitter @bigWRguy


Rookie Guide Banner Ad Network.jpg
bottom of page