A long-known fact of fantasy football, and football in general, is that the running game is heavily influenced by the play of both running backs and offensive lines. A good running game requires solid sets of both positions–with a bad line, a good back will get tackled before he can do anything and with a good line, a bad back won’t be able to make the most of what’s allowed for him. We understand the situation, but still struggle to move past it, as the rushing production conversation practically follows a script at this point:
- A back either exceeds or falls short of some marker of success, usually in terms of yards per carry.
- The second party counters that the success/failure is due to his well/poorly-rated blockers
- A circuitous and wordy series of “nuh uh” and “yeah huh” follow
- The conversation ends, after (almost always) going nowhere
What we need is a better way to evaluate the performance of both units, and this need for quantitative evidence has been the primary focus of my study. Originally, I set out to provide these stats for all starting and contributing backs, but I gradually realized that such a task would be impossible for me to undertake with the time I allotted myself. Still, I believe I’ve gone a long way to aid our understanding of rushing production from a grand scale. Additionally, I can pick spots in which to evaluate how the RB-OL balance sits for specific players. Most importantly, though, I’ve come up with even more ways to investigate just how each position affects the running game.
In what will probably be an ongoing series, this first part will be focused on introducing the main concepts of my study while also providing nuggets that I hope prove useful in some sense for the RB-OL discussion. For those (very rightfully) curious and/or skeptical of how I went about attaining these numbers, read through Part Zero of the series first, in which I explain my methodology and caveats (of which there are many). With all that said, let’s start off with the bread and butter of the study.
Running Back and Offensive Line Generated Yards
The simplest objective way to examine the issue at hand is to see how many yards each unit generated. Despite easily taking the largest portion of my time to record, the formula to find these measures is elementary:
Rushing yards = RB-Generated Yards + OL-Generated Yards
I dive much more in depth into just how the recording goes, but the gist of the two numbers is easy to understand: OL Yards measures how many yards the OL would block for a replacement-level back on a given play, while RB Yards measures how many yards the back adds on top of that, or above a run-of-the-mill back. These stats can most simply evaluate how much production the units offer, and these results are the most valuable of the entire study, as I’ll explain later. All you need to know for now, though, is that these two numbers are the building blocks of the study.
Hole Identification and Hit Rate
This measure originated in the charting I did while scouting running back prospects, a simple-yet-objective set of ways to measure a back’s effective vision, patience, quickness, agility, and functional strength. Identification Rate asks how often the runner finds a hole that the line blocks for him while Hit Rate asks how often the runner makes it through that hole once he’s found it:
ID Rate = Holes identified / Total holes
Hit Rate = Holes hit / Holes identified
Thus, the former measures intangible aspects (vision, patience) while hit rate measures physical attributes (quickness, agility, strength).
Now we have two numbers to see how well a player finds holes and gets through them. Great! Let’s put them together. Success Rate reports the overall ability of a player to get through a hole that the OL opens for them:
Success Rate = Holes hit / Total holes
Heading into the study I wasn’t too sure about how much Success Rate really mattered to production given RB-GY, but after 120 sampled games, it has proved to play a vital role.
RB Powers and Eludes (and Broken Tackles)
Simply put, these stats measure each time a back breaks a tackle via power and elusiveness, respectively. There’s not a lot more to these numbers. I chose to name them “Powers” and “Eludes” because I needed something simple to type. Sue me. I found it most logical to combine the two stats into a simpler “Broken Tackles” catch-all:
Broken Tackles = Powers + Eludes
The early indication from my current sample is that Broken Tackles matter the same amount as Success Rate, give or take.
The next logical step for me with these numbers was to combine them with each other (and a couple other simple stats) to get solid efficiency measures. If we looked solely at these (non-Rate) numbers on their own, we’d be able to take away almost nothing aside from the raw volume a back receives.
RB/OL Generated Yards per Carry
These two measures are the easiest ways to get to the point of the argument and will likely be used the most often to evaluate a unit’s output. However, both stats have shortcomings. RB-GY are well-influenced by OL play, because it’s much harder for a back to create while getting met in the backfield as opposed to in space. Meanwhile, OL-GY only measures part of the OL-quality equation. We’ll get to that. But first, let’s look at our optimized RB stats.
Percent of Yards Contributed
At this point, we’ve got to make some concessions. Imperfect stats shouldn’t be used to say things they don’t really say, and with what I’ve gathered to this point, there is no single stat that’s perfect to describe a back’s contributions to productivity. Thus, I will not be using a single number to do so. On the other hand, I’ve still got some tricks in my bag.
Percent of Yards Contributed is the best to measure the balance between RB and OL production. The formula is simple:
Percent of Yards Contributed = RB-GY / Total Yards
With this stat, you can essentially say, “(Player) contributed (PYC)% of his rushing yards.” It will at least show you if one unit is putting in a lot more to the effort than the other (though we can build on that in the future). Interestingly, I suspect the average for backs with PYC will creep toward 50%, so it might be the case that RB and OL play are truly a 50-50 split toward production (down the line, I will disagree with this notion). Nonetheless, with a decent sample, PYC can show just how much weight each unit is pulling in the run game.
Yards generated per hole effectively examines how much a back can do given each instance he’s provided an opportunity. It’s probably the closest thing we’ve got to a one-shot number, but it should not be used as such. It’s much better to measure creativity than a back’s all-around game, but it still doesn’t master creativity because other aspects of the game can creep in to the score. Let’s hone in on creativity while we’re here, though.
From this point on, we will deviate from trying to describe a back’s ability with an all-in-one number. Now, we are separating his attributes into different categories and stats, and trying to evaluate those individually. Identification Rate, Hit Rate, and Success Rate all came up in this past, which are all used to describe specific parts of a player’s game. Now, we move on to the new, more general aspect of creativity.
Because different runners gain yards in drastically different ways, this number does not measure strength, speed, or any other specific trait. Instead, it measures how much a player can create with the style and skills he chooses to use in order to create. The difference between this stat and the one before it is that the former also partially incorporates the player’s ability to hit the hole, which is a separate trait (hole-hitting ability) that we are leaving to Success Rate to measure. Simply put, if a runner gets stopped in the hole prior to hitting it, he missed out on yardage because of his inability to hit a hole, not his inability to create.
With GY/Hole Hit, we have cut vision and hitting ability out of the equation. So, when a guy gets to a hole, what can he do? This is what GY/Hole Hit focuses on, and it focuses very well, as we’ll see later. Adding that to Success Rate, we’ve got a very solid hold on two general ideas that can, together, paint a pretty full picture of a back’s ability to produce. We will build (and focus) on these in the future, but we have a couple other stats to get through.
Self-explanatory, Btk/Tkl is the number of times a player breaks a tackle for every time he gets tackled successfully. I originally thought this would be the best way to measure tackle-breaking ability, but like RB-GY, we need to better account for stuffs where RBs are helpless.
Broken Tackles/Hole Hit
This time around, we skip broken tackles per hole because, again, that is partially effected by hole-hitting ability, while we just want tackle-breaking ability once the back has opportunity. Thus, we turn to each time a player hits a hole. This measures how many tackles a player breaks once they’re in space and takes the bias away from players with good offensive lines.
OL Hole Rate
Hole rate follows an obvious formula:
Hole Rate = Total Holes / Carry
It measures the percent of carries in which the line opens up a hole for the back. What the back does with the hole (if he doesn’t identify it, if he misses it, etc.) is up to the back, we are only concerned with the line. As I mentioned above, OL-GY only gets to part of the blocking equation. That stat is a sort of weakest-link measure, as once any one defender has gotten through, the line stops generating yards. Hole rate acts as more of a group grade and shows how well the whole unit opens up lanes and creates opportunities for the back. Still, both are basically of equal importance as my math has shown me (and as I will explain in the future).
In this introductory section of my study, I detailed each defining stat of the project. I tried to explain the theory as to why each was used. I refrained from providing actionable, or even helpful, information. Well, sometimes stuff takes time to get into. But since you read this far, here are some nuggets (to varying degrees of use):
- Running back creativity is the single most important aspect in rushing production. I’ll provide math to show you why in the future.
- Of the five backs I looked through long enough to feel comfortable evaluating, Ezekiel Elliott scored the best, with ease.
- That’s surprising because LeVeon Bell was in that group, too. His running style does factor into the equation, but not unfairly so.
- Offensive lines contribute close to half of rushing yards, but don’t effectively matter as much. In other words, relative skill differences matter more for backs than lines when we’re looking at rushing production.
- Still, backs will more-than-likely drown behind a bad offensive line. You can bet on an article about Leonard Fournette arriving in the future.
I’ll dive deeper into all these topics with math at my side in the future, but in the meantime, sit back and let this information sink in, because it’ll be the basis for a lot to come.
Finally, if I get enough demand, I will go back and chart some specific players’ performances, so definitely let me know if you’d like to see how someone specific fared.
I’ll be dropping some stats as I record them on Twitter, so if you’re interested in that sort of thing, make sure to follow me @twitrsports.