Fantasy football scoring systems typically provide for outsized rewards for touchdowns.  For that reason, we look at advanced metrics for running back performance around the end zone.  We call it Advanced Red Zone Efficiency, but in reality we are scoring efficiency within the 10 yard line.  Runs inside the 10 yard line are the most valuable out of any that a running back receives.

Our Advanced Red Zone Efficiency scores take into account two basic measures.  How many of an RBs carries inside the 10 were converted into TDs, and what percent of yards needed for a TD did the RB average (yards per carry divided by yards to goal).

The TD conversion number is easy to understand.  However, the YPC/YTG percentage is not as intuitive.  A simple explanation is that running backs get the ball in different places.  A running back like Michael Turner is going to get a lot of goal line work.  A running back like Jamaal Charles is going to get the ball further away from the goal line.  So converting their YPC into a percentage of yards needed to score allows us to level the playing field a little.

We then create a standard score for each of these measures we’re looking at and then combine them.  That combined number is our Advanced Red Zone Efficiency.

Similarity Scores were introduced by Bill James, the father of sabremetrics.  To see how James applied the concept you should really consult his work.  My use of Similarity Scores would probably be considered a bastardization by the sabremetric purists (the only people more annoying than baseball purists are sabremetric purists).

However, I obviously give James all credit for coming up with the concept of Similarity Scores.

Here’s how I apply them.  I take the most basic box score statistics like yards per carry (or reception, or passing attempt), total yards, TDs, and age, and I measure each player’s distance from each other player on these simple stat lines.  Once I have done that, I can generate a list of the top 20 most similar player seasons to any individual player.  So I can tell you the 20 most similar seasons to Jamaal Charles 2010.

I then use that information to look at the following year production (let’s call this Y2).  This is a roundabout way of looking at career trajectory.  The theory goes that possession receivers will produce similarly to other possession receivers that came before them.  Speed receivers will perform similarly to other speed receivers who came before them. 

We’re primarily interested in what happens to players at the beginning and end of their careers.  What can we expect from older players, and what can we expect from younger players.

In our Draft Guide we use Similarity Scores to come up with a projection for the upcoming year.  There are all sorts of caveats that should be offered with the Similarity Projection, the simplest of which is that it is a single thing to consider.

Planning your fantasy season around Strength of Schedule (SOS) is a little bit like counting cards at blackjack.  Card counters don’t win every hand.  They’re just trying to maximize their edge over the long run and get their money on the table when the odds are in their favor. 

Using SOS has the same benefits.  If you regularly and consistently pick players based on their seasonal SOS, and pick starts/sits based on weekly SOS, then you’ll be ahead over the long run.  You might lose some individual start/sits, but your goal is to get as many favorable matchups over the course of a season as possible

Our Methodology

Our system of using SOS relies primarily on fantasy points allowed by the opposing defense and then looking at the schedule in 3-6 game blocks. 

For purposes of visualization, we standardize our defensive ratings to make them simple to look at in bar graph form.  It’s easier to look at how many standard deviations a defense is above/below the mean, than it is to try to look at the difference between a defense that allows 15 points/game as opposed to one that allows 16 points/game.

For projecting individual weekly matchups we rely on both efficiency ratings for the defense, and efficiency ratings for players.  Basically how well did each do better than they were expected to.

((Player Efficiency * Defense Points Allowed) + (Defense Efficiency * Player Points Scored))/2 = Projection

After we have those projections we can look at players both from a start/sit standpoint, as well as finding players to target in trades.

Again, our SOS calculations aren’t going to be perfect.  For instance, it’s particularly challenging to forecast next season’s SOS based on last season’s defenses as defenses improve and deteriorate from year to year. 

However, our goal isn’t to be perfect, it’s just to get the maximum advantage we can.

Filtered Yards Per Cary, or Filtered YPC, is one of the advanced metrics that we’ll use sometimes to try to uncover hidden talent, or to identify guys who were the beneficiaries of good blocking or a good system.

Filtered YPC basically throws out all runs less than 4 yards based on the theory that blocking is going to get a ball carrier four yards past the line of scrimmage.  What he does after that is usually more based on his talent.

Filtering carries might seem stupid in that guys usually stay in the same system from year to year.  So if they got good blocking last year, they’ll probably get it again next year.  But what we’re trying to uncover is what coaches might see in evaluating their depth chart.  Are they leaving “yards on the table” because they’re sticking with a guy who doesn’t do anything past four yards?  Are there two fantasy backs with other similar metrics but who are very different in terms of Filtered YPC.

So we’re trolling for clues that a change in usage would result in a breakout for a back.  If we know a guy has talent based on a great Filtered YPC number, and we suspect that he might get increased carries, then we can potentially get a big value pop.

The Adjusted 40 Score is credited to Football Outsiders’ Bill Barnwell, who explains it here:

The 40-yard dash matters: When compared with all three metrics, the 40 time was the single most indicative measure of a running back’s future success. That’s not to say that a player can succeed strictly on the basis of a fast 40, but that a 40 tends to be the biggest tip-off of future playing time and success with that playing time.

We need to adjust 40 times for weight: Raw 40-yard dash times have a minus .36 correlation with DPAR, carries and yards; remember, a negative relationship here would indicate that 40 times (which are better as they decrease) are strongly correlated with those rushing metrics (which are better as they increase).

The thing is, not all 40 times are created equal. Brandon Jacobs‘ 4.56 40 is incredible when you consider his 267-pound frame. On the other hand, Ahmad Bradshaw‘s 4.55 40 was disappointing for a player who weighed in nearly 70 pounds lighter. Adjusting 40 times for weight helps translate a raw metric into something that’s more indicative of a player’s NFL potential.

Ready for a math headache? The formula for the adjusted 40 score is (Weight * 200)/(40 Time⁴). The multipliers are as such in the formula to ensure both accuracy as well as simplicity — the scores that result revolve around a 100-point scale. The average adjusted 40 score of all running backs is 98.5; for all drafted running backs, it’s 102.4; for all running backs selected in the first round, it’s 112.1. Consider adjusted 40 score to be a sort of speed score — a higher number is better.