A Closer Look, Placing The Steelers Rushing Data In Context

Earlier this morning, we did a side-by-side comparison between running back Le’Veon Bell and the newest Pittsburgh Steelers running back, LeGarrette Blount, to see how they stacked up against one another in situational football.

We looked at three key areas, drawing data from last season’s numbers in order to compare how each back performed in short-yardage, goal-to-go, and third-down situations with the ball in their hands.

Some of that data may have gotten lost in the body of the article, while some could use a bit more context, so I thought it would be helpful to now present the same information in a more organized manner using charts and offering more explanation behind certain figures.

The first set of data compares the two backs in goal-to-go situations. The fifth column is, obviously the average distance to go from the line of scrimmage to the goal line on the running back’s total goal line rushes.

Player Att Yds Avg Avg To-Go TD
Le’Veon Bell 20 29 1.45 3.2 8
LeGarrette Blount 6 18 3 3.67 4


It’s worth keeping in mind, of course, that Blount was not the workhorse back that Bell was asked to be in his rookie season, and in fact was part of a stable of three other backs.

Blount’s six goal line carries represent just 10 percent of the total goal line carries taken by New England Patriots running backs, led by the 13 carries by Stevan Ridley. Brandon Bolden added another nine carries.

Nevertheless, Blount was the most successful in terms of converting his carries into scores. Ridley had six touchdowns to Blount’s four, but in more than twice the amount of carries.

The second chart looks at the performance of the Steelers’ two backs in short-yardage situations, which for this purpose I have defined as any carry that takes place within three yards of gaining a first down or scoring. FD% represents the frequency with which the back converted a run into either a first down or a score.

Player Att Yds Avg Avg To-Go TD Long FD%
Le’Veon Bell 46 126 2.74 1.48 5 43 63
LeGarrette Blount 26 75 2.88 1.92 1 16 58


In this instance, while Blount took the highest number of carries in short-yardage situations on the Patriots, his total represents only about a third of the team’s total carries. In contrast, Bell’s number of carries represents closer to two-thirds of the Steelers’ total short-yardage carries.

It should be pointed out that Bell’s total in this situation is inflated by the 43-yard outlier. Blount’s figures are not nearly as subject to variability by removing outliers. Nevertheless, it is worth noting that Bell was more successful in converting on first downs or scores in short-yardage situations than was Blount, which can only partially be explained by the nearly half-yard greater average distance to go that Blount faced per carry. On the other hand, it should be noted that his conversion ratio improved in December.

Also in contrast to Bell, only about one-fourth of Blount’s short-yardage carries came on third-down or later, while over one-third of Bell’s carries came on later downs. In fact, the Patriots simply didn’t run as frequently on third- and fourth-and-short as the Steelers did.

In such situations, the Patriots ran a total of 65 plays, 36 of which were pass attempts for a throwing ratio of 55 percent. In contrast, the Steelers ran 64 such plays with 30 pass attempts, including Mat McBriar’s fourth-down pass, which translates to a throwing ratio of 47 percent.

That in part speaks to the data that we see below when we compare the performances of Blount and Bell on late-down short-yardage situations.

Player Att Yds Avg Avg To-Go TD Long FD%
Le’Veon Bell 16 73 4.56 1.38 0 43 69
LeGarrette Blount 7 18 2.57 1.57 0 6 71


Despite 65 total opportunities, Blount only received the ball on seven occasions on third-and-short, while Bell was handed the ball 16 times on 64 total opportunities. Much of that has to do with the Patriots’ offense, as well as the comparative trust that each team placed in their back in crucial opportunities.

Of course, it’s always essential to keep in mind that data extracted from different teams can never draw perfect correlations. They play behind different offensive lines with different coordinators and teammates who serve different roles. The raw data tells just a part of the story, but hopefully the information provided above helps enlighten the discussion some and provides a bit more context.

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