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On Sunday, we examined how good the St. Louis Cardinals were at stealing bases. (Not very.) On Monday, we looked at how the Cardinals performed at taking the extra base on a ball in play. (Not well.) Today, we're going to put it all together.
It makes intuitive sense to say that taking an extra base is taking an extra base, whether it occurs on a pitch or on a ball in play. Stolen bases get more attention because they are a stat that reflects an exciting play in field, as anyone who experienced the buzz in old Busch Stadium when Vince Coleman was on second base can verify. Fans were excited to see Coleman steal, not watch him zip from first to third on a single. But taking the extra base on a base hit to the outfield can be just as advantageous for a player's team as swiping a bag. The flip side of the base running coin is that making an out on a stolen-base attempt can hurt a team as much as making an out while attempting to take the extra base on a hit.
Fangraphs has created a metric that puts all of base running on the same scale, from stealing bases to advancing two bases on a single. The stat is called Base Running Runs (BsR). It merges Weighted Stolen Bases (wSB) and Ultimate Base Running (UBR) into one single stat, which places a run value on each base-running event. Fangraphs uses BsR in its Wins Above Replacement (WAR) calculation.
The wSB metric is fairly easy to understand. Fangraphs awards 0.2 runs per stolen base. The negative impact of a caught stealing depends on the run-scoring environment of a given season. Last year, it was -0.377. A player with a wSB of zero is exactly league average. A negative wSB is below average; above zero is better than average. The full glossary entry, complete with formulas, can be found here.
UBR uses run expectancy to value a player's actions on the base paths. From the Fangraphs UBR glossary page:
Runs are awarded to base runners in the same way they are rewarded to outfielders on "arm" plays. The average run value in terms of the base/out state is subtracted from the actual run value (also in terms of the resultant base/out state) on a particular play where a base runner is involved. The result of the subtraction is the run value awarded to the base runner on that play.
If you didn’t understand that, a simple example should explain it clearly:
Let’s say that there is a runner on second and one out. A ground ball is hit to the SS. Let’s say that on the average, in that same situation, the runner advances safely to third and the batter is thrown out 20% of the time, he stays put 70% of the time, he gets thrown out at 3rd 5% and beats a throw to third 5% of the time (batter safe on a FC). And let’s say that average base/out run expectancy (RE) of all those results, weighted by their frequency of occurrence, is .25 runs (all the numbers are made up). If the runner advances and the batter is thrown out, and the resultant RE is .5 runs, then the runner gets credit for .25 runs (.5 minus .25). If he stays put, and the average RE of a runner on second and 2 outs is .23 runs, then gets "credit" (he gets docked) for -.02 runs (.23 minus .25). So basically a runner gets credit for the resultant run value of what he does minus the average weighted resultant run value of all base runners in that situation.
So how did the Cardinals' 2014 base running rate by wSB, UBR, and BsR? The Cards posted a -6.3 wSB collectively in 2014, which the third-worst in the NL. Their -4.5 UBR was also third from the bottom. Overall, St. Louis was the worst base-running team in the National League, with a -10.3 BsR
I put together another table. This one has wSB, UBR, and BsR. Some of the BsR totals appears to be off by one tenth of a point, when compared to the wSB and UBR totals. I believe this is due to Fangraphs rounding to the nearest tenth (since this happens to me on occasion) but am not 100% certain.
2014 | wSB | UBR | BsR |
Kolten Wong | 2.1 | 3.6 | 5.7 |
Peter Bourjos | 0.4 | 1.9 | 2.3 |
Mark Ellis | 0.3 | 1.0 | 1.3 |
Pete Kozma | 0.0 | 0.4 | 0.4 |
Greg Garcia | 0.0 | 0.3 | 0.3 |
Shane Robinson | -0.4 | 0.3 | -0.1 |
Matt Holliday | -0.3 | 0.0 | -0.2 |
Randal Grichuk | -0.8 | 0.0 | -0.8 |
Daniel Descalso | -1.1 | 0.2 | -0.9 |
Yadier Molina | -0.6 | -0.3 | -0.9 |
A.J. Pierzynski | -0.5 | -0.5 | -1.0 |
Matt Adams | -0.6 | -0.7 | -1.3 |
Matt Carpenter | -1.0 | -0.5 | -1.4 |
Tony Cruz | -1.3 | -0.4 | -1.6 |
Oscar Taveras | -0.6 | -1.1 | -1.7 |
Jhonny Peralta | -0.7 | -1.5 | -2.2 |
Jon Jay | -0.5 | -1.8 | -2.2 |
Allen Craig | -0.5 | -2.8 | -3.3 |
Given the previous two posts and the Cards' poor overall showing, it's not surprising that St. Louis only had five (really, though, just three) above-average base-runners in 2014. Jason Heyward posted a 3.0 BsR in 2014, a -0.5 in 2013, and a 7.9 BsR in 2012. It's safe to say he'll be an upgrade on the base paths compared to Craig and Tavaeras. Nonetheless, the Cardinals are not a good base-running team and Heyward isn't going to be enough to change that this season.