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Fantasy Football Analytics to Know in Devy Leagues (2022)

Fantasy Football Analytics to Know in Devy Leagues (2022)

As I had alluded to in the article, Devy Do’s and Don’ts — analytics matter. For many reasons, they get a bad rap, but they all boil down to the same foundation. Analytics are assumed to be complicated, but I am here to tell you they aren’t. I will take you on a three-part series outlining which analytics will give you an edge for your devy squad.

First up, running backs.

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The Why

With all things, context is always required. Mainly to better understand the extenuating circumstances, such as Jameson Williams. His career numbers (our preferred usage) were awful, but his best season numbers were fantastic. Context tells you all the necessary information about that specific profile. It is easy to get bogged down with the copious metrics available while pinpointing the important ones will lead to success.

These metrics are not pulled out of a hat but shown through regression models (by people far more talented than myself) to have a high predictability of success for projecting rookies in the NFL. The crux of analytics in devy is helping pinpoint the players who have a higher likelihood of being drafted and being drafted with high draft capital. I’ll help you break down metrics and analyze the numbers.

The Running Backs Tea Leaves

Here are the metrics that I think are the most important for running back success.

Breakout Age Target share

As referenced in my previous article, “once a player logs a Dominator Rating above that threshold, that season qualifies as a breakout season. A breakout season is an essential box to check regarding a player being relevant for dynasty teams.” The previously mentioned threshold is a 15% dominator rating. Since 2003 only eight players have had a top-24 season without a breakout (the dominator threshold was 15%). Therefore, a college player breaking out fulfills his opportunity to have a top-24 running back season. It also increases his likelihood of being drafted in the first three rounds of the NFL draft.

Receiving Yards Market Share and Target share

Okay, I cheated on this one. I lumped two metrics into one because they are both equally valuable and rely upon the other. The secret has been out of the bag for a while regarding running backs as pass catchers, and the inherent fantasy advantage received when rostering one. Target share is a great measure to gauge how engaged a running back was involved as a pass-catcher on his team. Ideally, the career average would be over 8% by the time they enter the NFL draft. For devy purposes, I aim for over 10% but won’t fade a player with a 7%-8% Target share.

This tells me that the team is actively using this player as a pass-catcher, which could signal the coaching staff’s opinion on that player. Talented and dynamic players are used in as many ways as possible, which translates to fantasy success in the NFL. Receiving yards market share (RYMS) is the “control” group for Target share. This shows what percentage of the total receiving yards that player was responsible for.

I prefer this metric over Target share if I had to choose one, but I don’t, so I won’t. I like this metric because it is a pseudo efficiency gauge for how the player faired as a pass-catcher given the opportunities they saw with targets. If a player has a low RYMS but a high Target share, I can glean that this player is not a spectacular pass-catching back and vice versa.

If the Target share is lower on the spectrum, say 6% but has a high RYMS, then I can theorize that this player is a well-versed pass catcher. Traditionally, I look for an RYMS above 8%-10%. However, if a player has an RYMS below that threshold but has a Target share within the threshold above, I will not avoid that player.

Yards Per Team Attempt

This is my favorite metric I use: yards per team attempt (YPTA). It is essentially a fancy phrase for efficiency. I believe that efficiency is one of the more translatable metrics from college to the NFL. This is why I hold this metric in such high regard. YPTA is, as it sounds — how many yards a player gains per each offensive play. As one can imagine, the threshold for this number is low, and I prefer to go in phases.

In their freshman year, I want a player’s YPTA above 1-1.5, sophomore year above two, and junior year above 2.5. Then, when they enter the NFL draft, an average career YPTA above 2.5 is a good sign. Aside from efficiency, this metric helps show the player’s growth year to year, how involved they were in the offense and how productive they were.

Backfield Dominator

The last metric that I find very useful is Backfield Dominator (BFD). It is, as it sounds — the percentage of the backfield the player occupied compared to his teammates. The beauty of this metric is that it shows objectively how much a running back was used. The boost that gives allows the player’s workload to be quantified and projected into the NFL. Believe it or not, players in college who handle a more significant workload are less likely to be injured than players who handle a smaller workload when used as a workhorse in the NFL. The threshold that I look for is above 65% for a player’s BFD. As freshmen, I want to see a BFD above 45% and then their next season crest the 65% mark.

Words of Advice

The last key point for running back is finding running backs who are as close to 200 as possible. The size of a running back plays a huge role in that player’s ability in the NFL. More often than not, finding running backs close to 205-pounds will smash any size concerns.

The only warning I have when it comes to analytics is to be aware of the small sample size traps. Much like in the NFL, 25%-33% of the total games played is not enough to get an accurate picture of that player’s abilities.

I tend to go by this rule if a player has not played more than eight games in a season (around 60% of the games), and I tend to view that data with skepticism. It is easy to get overwhelmed with new things, especially when it comes to numbers and analytics. There is no hurry or need to dive headfirst and start making the wrong conclusions from the data available. If you have a question, ask for help. Most assume the “nerds” are just a bunch of *insert potty mouth word here* but by and large, we want to help you get better and understand more, or at least I do.

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Feel free to reach out to me on Twitter @TheFFSandman. If you DM me, I will respond to you as soon as possible.

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