TPS Advanced: Run Percentage

Averages are important. We wouldn’t have a lot of our main-line sports stats without them and it’s really easy to throw them out as a reference point in basic sports conversations. Michael Jordan averaged 37 points a game for a whole season! Aaron Rodgers averaged 9.2 yards per attempt in his first MVP campaign! See? Really easy.

But he dictionary definition of the term “average” reveals one flaw that comes with trusting this kind of number too much. “Average” is defined as “a single value that summarizes or represents the general significance of a set of unequal values.” (Emphasis mine)

The idea that the values we’re averaging out are unequal is extremely important to understand, because they can be incredibly misleading as a result.

For example, last year, Ty Montgomery averaged an amazing 5.9 yards per carry on 77 attempts, significantly better than Eddie Lacy, who averaged 5.1 yards per carry on 71 attempts.

However, one of those aforementioned unequal values pops up in a big way in Montgomery’s stats. One of his 77 carries was a 61-yard sprint against the Chicago Bears.

Remove that play from the equation and his average drops all the way to 5.2 yards per carry. Still good, but only slightly better than Lacy’s 5.1 yards per carry.

It’s important to go beyond just the raw numbers when evaluating a player’s performance, and that’s exactly what our next advanced stat, Run Percentage, hopes to do.

What does it mean and why do we like it?

The meaning of this stat is simple: we’re looking at the percentage of carries in which a player runs for a given amount of yards.

Unlike the other “advanced” stats we’ve rolled out so far, this metric doesn’t involve any sort of extra calculation or evaluation. All we’re doing here is looking at how often a player produces a run of a certain length.

Looking at run production this way eliminates unnecessary weight given to long runs. Ideally, a runner will be productive on each opportunity, and allowing long runs to weight an average obscures our ability to really see how effective he is as a rusher.

What does it tell us about the Packers?

The data from 2016 reveals quite a bit about the Packers’ running game. According to the numbers, Ty Montgomery and Eddie Lacy produced pretty similar results, except in one key area. Montgomery was notably less likely to get stopped for a loss than Lacy, producing runs for zero or negative yardage on around 14% of his carries as opposed to 18% for Lacy.

The numbers also show us why the Packers’ confidence in Aaron Ripkowski as a runner is well placed. Though he had just 34 carries, he produced runs of at least five yards 41% of the time, by far the best rate on the team among running backs.

Finally, the numbers give us a much better look at how effective Aaron Rodgers is as a runner. Looking at runs play-by-play as opposed to as a raw box score, it’s easy to remove kneel downs from the equation, leaving Rodgers with 51 true rushing attempts. He made the most of those opportunities as well, running for 10 yards or more on more than 25% of his carries.

Take a look at our full data here and be sure to check back on our 2017 stats to see how this year’s version of the Packers performs week to week.