141, 141, 135.
Those were the top three RBI totals from 2009, courtesy of Prince Fielder, Ryan Howard, and Albert Pujols. The top three for the ’09 Minnesota Twins is much less impressive (103, 100, 96, from Jason Kubel, Justin Morneau, and Joe Mauer), but that doesn’t mean that we don’t care about them. Morneau compiled his 100 from a strong first half and a rather weak second half, complete with missing the last three weeks of the season. Joe Mauer missed all of April, yet he nearly broke the 100 mark. Kubel played the whole season, but just barely had more RBI than the other two. Surely Morneau and Mauer were more efficient in driving in runners…right?
We can certainly argue over what defines a player as being “efficient” when advancing or driving in runners. For my research, I only focused on the act of advancing them, regardless of the means necessary to accomplish this. My friend Steven, as he mentioned a few posts back, prefers to think of efficiency as being able to move runners up without sacrificing outs. Honestly, he’s correct. A more valuable tool for measuring the worth of a player to his team would have been by looking at how a player put his team in a better position to win (look at the scoring expectancy matrix from my previous post for more information).
However, I deliberately ignored this. Why? Because I figured that if I didn’t, I’d know that someone like Nick Punto or Matt Tolbert would score poorly. They’re known for “doing the little things,” like sacrificing themselves to move a runner up a base. Was this the best thing for me to do? No. Yet, it is mistakes like this that causes a person to make adjustments for the future if he or she wants to continue doing research for a particular topic. Don’t worry Steven, the next time I do this, it’ll be much better.
Similarly, this was why I looked at the percentage of runners driven in by a hitter. Going back to what I said above, Jason Kubel appears to have had the most plate appearances out of the top three RBI hitters for the Twins last year. Upon a closer look, this turns out to be untrue, for Kubel actually finished with a fewer number of plate appearances as Mauer and Morneau. Mauer had 606, Morneau 590, and Kubel 578. Perhaps this means that Kubel was actually the most efficient in scoring runners last year.
I feel like I’ve teased you enough. Finally, I present to you the percentage of runners in scoring position driven in, along with the percentage of all runners driven in.
Surprise, surprise. As I mentioned before, your leader in this category is not Mauer, Morneau, or Kubel…it’s Delmon Young. I’m sure you’d prefer if I sorted these in order, so here you go, with each value reduced to 3 decimal places.
|1||Delmon Young||0.356||1||Joe Mauer||0.192|
|2||Joe Mauer||0.339||2||Delmon Young||0.183|
|3||Jason Kubel||0.335||3||Jason Kubel||0.183|
|4||Justin Morneau||0.304||4||Justin Morneau||0.171|
|5||Denard Span||0.276||5||Orlando Cabrera||0.169|
|6||Carlos Gomez||0.272||6||Denard Span||0.152|
|7||Matt Tolbert||0.254||7||Michael Cuddyer||0.137|
|8||Brendan Harris||0.252||8||Joe Crede||0.135|
|9||Orlando Cabrera||0.250||9||Carlos Gomez||0.129|
|10||Michael Cuddyer||0.249||10||Brendan Harris||0.125|
|11||Joe Crede||0.240||11||Nick Punto||0.125|
|12||Nick Punto||0.232||12||Matt Tolbert||0.116|
|13||Jose Morales||0.184||13||Brian Buscher||0.099|
|14||Alexi Casilla||0.183||14||Alexi Casilla||0.091|
|15||Brian Buscher||0.174||15||Jose Morales||0.088|
|16||Mike Redmond||0.111||16||Mike Redmond||0.071|
Delmon Young is a very odd hitter. He hits well with runners in scoring position, but not when runners are on base. He hits best in high leverage situations, but not late in games. I don’t quite understand it… As for other players, I’m a bit surprised to see Michael Cuddyer in the middle of the pack. It seems like the players are ranked in order of “ability” (batting average, OPS, whatever you like), excluding Cuddyer. Therefore, I ran a bunch of correlation tests to see what correlated best to these numbers.
In case you were curious, WPA stands for win probability added. WAR is wins over replacement (this is explained in two 7-part series, so you may want to save those for when you have plenty of time to spend). I’m sure you know that anything that has “w/ RISP” is “with runners in scoring position,” while anything that has “w/ RO” is “with runners on.” The bolded numbers are the best correlation between two statistics, while the boxed numbers are the best three correlations for my two statistics. I feel that it’s understandable that RBI and some variation of slugging percentage correlate best with these two statistics, since obviously you must have driven in runners in order to have a good RBI total, and a high SLG means you had more total bases, leading to more runners being moved around the bases and driven in (unless all players’ SLG were terrible with RISP or runners on base). However, since the correlations are only fairly strong (a value of 1 would be a perfect positive correlation and it’s preferred to be above .9), either there are statistics that I didn’t look at that would have yielded better correlations, or there isn’t anything available that would correlate well with this data. I’m leaning more towards the latter here.
I’m thinking of taking Steven’s advice to look at how these players would have done in situations that did not lessen the team’s chance of scoring a run. I’m sure that if I did that, then the correlation with my new data and a player’s WPA would correlate much better. Maybe some other stuff will have better correlations also when I adjust my data. Within the next day or two, look for my post(s) on the hitters’ ability to move runners up a base and how many bases they were able to move then over.