RE24 gets it name for the number of runs expected from the 24 base-and-out situations possible for a hitter (zero, one, two outs and eight different baserunner arrangements). More value is given to the hitter that hits a double with the bases loaded than the one that hits a 2-out double with no one on base. Fangraphs has an excellent matrix that shows the base/out scenarios and their run expectancy values.
|Runners||0 Outs||1 Out||2 Outs|
|1 _ _||0.831||0.489||0.214|
|_ 2 _||1.068||0.644||0.305|
|1 2 _||1.373||0.908||0.343|
|_ _ 3||1.426||0.865||0.413|
|1 _ 3||1.798||1.140||0.471|
|_ 2 3||1.920||1.352||0.570|
|1 2 3||2.282||1.520||0.736|
Therefore if you have a bases-loaded with no outs situation, it can be expected that you would score a little over 2 runs from that scenario. But if a hitter comes to the plate with the bases empty and two outs, the number of runs expected drops down to less than 0.1 runs. Here is an example for you:
Anthony Rizzo steps to the plate with men on 1st and 3rd with 1 out; the run expectancy for the situation would be 1.140. If Rizzo takes a walk to load the bases, still with just 1 out, the run expectancy for that situation is now 1.520. So now we subtract the resulting state of the bases from the initial state.
1.520 – 1.140 = 0.38 RE24 for that one plate appearance. RE24 is, as simply put as possible, an accumulation of all the individual values of each of a batter’s plate appearances throughout the season. If a run or runs are scored on the play, then you would add the number of runs scored at the end of the equation. Ok, I will give you another example:
Jorge Soler steps to the plate with men on 2nd and 3rd and 2 outs, a run-expected number of .570. He puts one in the gap for a 2-run double: what was Jorge’s RE24 for that play?
Resulting situation = 0.305
Initial situation = 0.570
Number of runs scored = 2
Equation: 0.305 – 0.570 + 2 = 1.125 RE24 for that play.
Get it now? Kind of a fun math story problem, but obviously those hitters with more at-bats will have more chances to accrue RE24 totals. Each scenario has a value and how a hitter impacts that scenario is measured. Fangraphs gives a rule of thumb for hitters:
With those numbers in mind, let’s take a look at the Cubs leaders and bottom-feeders for this statistic.
The top 6 are a mixture of “duh” and “well isn’t that surprising….”
1. Anthony Rizzo: 36.84
2. Luis Valbuena: 18.48
3. Chris Coghlan: 11.97
4. Starlin Castro: 10.57
5. Jorge Soler: 7.01 (in 24 games)
6. Travis Wood: 3.33
Now that says a whole world of interesting things about the 2014 Cubs. First of all, Castro’s total was surprisingly low and Jorge Soler’s was (even with a small sample size) very inspiring. Travis Wood’s inclusion anywhere near the top, however, was rather depressing.
The bottom 6
1. Mike Olt: -7.91
2. John Baker: -9.03
3. Arismendy Alcantara: -10.95
4. Javier Baez: -12.46
5. Junior Lake: -13.09
6. Nate Schierholtz: -16.84
Sadly, these were not overly surprising totals for these guys. The bottom of the list is made up of free swingers that struck out a ton, which would only hurt their RE24 totals. That’s because their strikeout-heavy ABs only serve to diminish run expectancy.
Joe Maddon addressed this issue in his introductory press conference so it’ll be interesting to see whether and how he’s able to have an impact on some of these players at the bottom of the list. Or, for that matter, how he’ll be able to manipulate different base/out situations to put the Cubs in the best position(s) to score runs.
RE24 might be a bit of a fringe stat as far as the average observer is concerned, but it may be something to keep an eye on as we follow the growth of this team and the effect of its new manager.