Thread: John Sickels' Rankings View Single Post
01-29-2013, 09:55 PM   #139
AtomicDumpling
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Join Date: Mar 2007
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Re: John Sickels' Rankings

Quote:
 Originally Posted by REDREAD Here's what run expectancy tables say: 0 outs: runner at 1st: .941 runner at 1st and 2nd: 1.556 1 out: runner at 1st: .441 runner at 1st and 2nd: .642 2 out: runner at 1st: .061 runner at 1st and 2nd: .015 (I found this very interesting) The big problem I have with run expectancy tables is this scenerio: let's say Billy singles with no outs, and then steals 2nd base and then scores. That counts as a run for runner at 1st, no outs, even though Billy's stolen base actually helped the run score (This is how I understand it). Therefore, IMO, doing the math to determine the SB% success rate to steal is flawed. Ideally, you want run expectancy for a runner at 1b with no attempt of stealing, bunting, hitting to the 2b side to advance the runner. It would be interesting to see run expectancy when no "smallball" tactics are employed vs when they are. Maybe the numbers don't change, but RE is flawed for figuring out how valuable a SB is, in my opinion. Not to pour salt on any wounds, but I also feel that slow runners with high OBP are overrated. The assumption is that a slow guy at 1b scores at the same rate as a Billy Hamilton/Drew Stubbs does. That is not true. Of course OBP is important, but speed/baserunning also is important.
Correction: Your numbers for the 0 out scenario are correct, but the other two scenarios are off.

0 outs:
runner at 1st: .941
runner at 1st and 2nd: 1.556

1 out:
runner at 1st: .562
runner at 1st and 2nd: .963

2 out:
runner at 1st: .245
runner at 1st and 2nd: .471

Code:
```1B	2B	3B	0 outs	1 outs	2 outs
x	x	x	0.544	0.291	0.112
1B	x	x	0.941	0.562	0.245
x	2B	x	1.170	0.721	0.348
1B	2B	x	1.556	0.963	0.471
x	x	3B	1.433	0.989	0.385
1B	x	3B	1.853	1.211	0.530
x	2B	3B	2.050	1.447	0.626
1B	2B	3B	2.390	1.631	0.814```

In your scenario with Hamilton hitting a single with nobody out, then stealing 2nd base, then scoring would chart like this:

Hamilton singles and steals scenario:
0 outs and Hamilton at the plate -- 0.544 expected runs (starting point at beginning of inning)
Hamilton singles, runner on 1st with no outs -- 0.941 expected runs (Hamilton added 0.397 expected runs by hitting a single 0.941 -0.544 = 0.397)
Hamilton steals second, runner on 2nd with no outs -- 1.170 expected runs (Hamilton added another 0.229 expected runs by stealing 2nd)

So you can see that the run expectancy matrix does give Hamilton credit for the stolen base.

You can take the amount of value added by the stolen base (in this case 0.229 extra runs) and use it to calculate the success rate required to break even. If the base stealer's expected chance of success exceeds the break even rate then it is a good gamble to attempt the stolen base.

You are correct that the run expectancy matrix assumes that runners have average speed and that the batter is an average hitter. The run expectancy tables are derived from averaging every MLB play, there are no charts available for each individual player, and even if there were the samples sizes would be too small to have value.

So if the runners or batters are above average in skill you can expect the true run expectancies to be higher. The pitcher and defense are also assumed to be average in the charts. The charts give a us a good idea of the relative values of all the base-out states and can be used as a guide for strategy, for example, would a bunt be wise or should I risk taking an extra base.

Your assertion that a fast guy is more likely to score from first than a slow guy is obviously correct. You can measure this to some degree by calculating the extra expected runs gathered by a runner who took an extra base, tagged up on a fly ball, beat out a double play, or stole a base.

For example, say Billy Hamilton singles with no outs like before, then Phillips singles to left field and Hamilton is able to advance all the way to 3rd base instead of 2nd base like an average runner would:

Hamilton takes extra base scenario:
0 outs and Hamilton at the plate -- 0.544 expected runs (starting point at beginning of inning)
Hamilton singles, runner on 1st with no outs -- 0.941 expected runs (Hamilton added 0.397 expected runs by hitting a single 0.941 - 0.544= 0.397)
Phillips singles to left and Hamilton advances to 3rd leaving us with men on 1st and 3rd and nobody out -- 1.853 expected runs

Slow Runner (Hanigan) does not take extra base scenario:
0 outs and Hanigan at the plate -- 0.544 expected runs (starting point at beginning of inning)
Hanigan singles, runner on 1st with no outs -- 0.941 expected runs (Hanigan added 0.397 expected runs by hitting a single 0.941 -0.544 = 0.397)
Phillips singles to left and Hanigan advances to 2nd leaving us with men on 1st and 2nd and nobody out -- 1.556 expected runs

So now we can see that Hamilton taking the extra base is worth 1.853 - 1.556 = 0.297 extra expected runs. Incidentally, that extra value is the same as if he had stopped at second on the hit, then stolen 3rd base. Those extra bases that Hamilton's speed allows will add up to a lot of extra runs for the Reds over the course of the season -- provided he can get on base at a high enough clip. It takes quite a lot of speed-generated extra bases to make up for a lesser OBP, especially when you consider that not getting on base in the first place costs the team an out. Staying on first base instead of stealing second base deprives the team of the extra expected runs, but it doesn't cost the team an out. Getting thrown out trying to steal second base not only deprives the team of the .229 extra expected runs, it also deprives the team of the .397 expected runs the runner earned by hitting the single.

Hamilton gets caught stealing with nobody out scenario:
0 outs and Hamilton at the plate -- 0.544 expected runs (starting point at beginning of inning)
Hamilton singles, runner on 1st with no outs -- 0.941 expected runs
Hamilton gets caught stealing second, no runners on and one out -- 0.291 expected runs (Hamilton just cost the team 0.650 expected runs and an out.)

What if the leadoff hitter got on base with a walk or a single, then the manager decided to bunt him over?

Bunt scenario:
0 outs and Hanigan at the plate -- 0.544 expected runs (starting point at beginning of inning)
Hanigan singles, runner on 1st with no outs -- 0.941 expected runs
Phillips sacrifice bunts and Hanigan advances to 2nd leaving us with a man on 2nd and one out -- 0.721 expected runs

This means that even though the sacrifice bunt was successful it still resulted in a reduction in expected runs. That's right -- the successful bunt hurt the teams chances of scoring. (Sometimes a sac bunt can slightly increase your chance of scoring a single run, but greatly reduces your chances of scoring multiple runs.) So when bunting your only chance of coming out ahead is if the defense screws up and fails to get an out somewhere. Of course there is also the chance the bunt fails altogether and you fail to advance the runner while still making an out, or the bunter can get himself into a two strike count while attempting to bunt. The odds are heavily against you when trying to bunt, especially if the defense is expecting it.

Last edited by AtomicDumpling; 01-29-2013 at 10:10 PM.

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