Re: John Sickels' Rankings

Quote:

Originally Posted by

**dougdirt**

Seems about right. Reds have a league average system at this point, which is impressive considering they don't have a single first round pick prior to 2011 in the system due to all the graduations and trades of the last couple years, and haven't really had a super high-profile international signing in five years (outside of Chapman of course).

Re: John Sickels' Rankings

Quote:

Originally Posted by

**Benihana**
Seems about right. Reds have a league average system at this point, which is impressive considering they don't have a single first round pick prior to 2011 in the system due to all the graduations and trades of the last couple years, and haven't really had a super high-profile international signing in five years (outside of Chapman of course).

Agreed.

In light of the MLB performance of guys like Cozart & Frazier, I think he vastly under-rated them last year, but looks about right this year.

Re: John Sickels' Rankings

Quote:

Originally Posted by

**kaldaniels**
Intersting points being raised here.

Is it better to have 1 man on 2nd with Votto up, or men on 1st and 2nd with Ludwick (or whoever is cleanup) up? It may be a situational thing.

My head tells me that if they are conceding a walk to Votto you should take that most everyday of the week though my heart wants to see Votto hit.

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.

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.

Re: John Sickels' Rankings

Great discussion and information on run expectancy. I was wondering if there is a site(s) or stat which shows runs scored vs runs expected to be scored as a measure of skill/speed of a baserunner. Namely the runner's hits/ walks were expected to bring x number of runs, he actually scored y runs in season a. Is there anywhere tracking if the individual exceeds his expected runs over the year? If so is there an adjustment made for teammates who hit into double plays? Should there be?

Re: John Sickels' Rankings

Quote:

Originally Posted by

**AtomicDumpling**
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

Thanks for catching that.. Obviously, that mistake was not intentional.

Quote:

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)

I guess my point is that the runner at 1st no outs 0.941 expected runs also benefits from all stolen bases.

That makes this analysis a little bit flawed. (Using run expectancy)

I'm making up numbers here.. but let's say you have a sample of 100 guys at 1st base, no outs in your data where you

calculate run expectancy. If all 100 of them stole second successfully, wouldn't the run exepectancy for this sample

be higher than .941? Because the guy started out at 1b.. the run gets counted when computing run expectancy.

If you had a second sample of 100 guys at 1st base.. All of them get caught stealing.. When you calculate run expectancy

of this sample for runner at 1b, no outs, wouldn't it be zero runs expected?

I guess that's my point. The stolen bases are already factored in, thus you can't use Run Expectancy to calculate the benefit of the steal.

If I am wrong on this, please explain, but I think since actual game data is used to calculate run expectancy, the SB (and the caught stealings) are already factored in.

That's why I think one needs to have a run expectancy calculation with only station-to-station samples vs a calcuation of the various stolen bases/caught stealing scenerios. Maybe there's not enough data to accurately calculate this though.

Re: John Sickels' Rankings

Quote:

Originally Posted by

**klw**
Great discussion and information on run expectancy. I was wondering if there is a site(s) or stat which shows runs scored vs runs expected to be scored as a measure of skill/speed of a baserunner. Namely the runner's hits/ walks were expected to bring x number of runs, he actually scored y runs in season a. Is there anywhere tracking if the individual exceeds his expected runs over the year? If so is there an adjustment made for teammates who hit into double plays? Should there be?

Good question,

There are several such stats out there. Perhaps the best is the Ultimate Base Running (UBR) statistic on Fangraphs. It is defined here: http://www.fangraphs.com/blogs/index...unning-primer/

Essentially it gives the runner credit or blame for taking extra bases or getting caught trying. It does NOT include stolen base attempts. It is a measure of how many extra runs he scored vs the number of expected runs based purely on his speed and aggressiveness on the basepaths.

Fangraphs also has a wSB stat that accounts for a players positive or negative contributions on stolen base attempts.

You can see these two stats under the Advanced tab on a player's FG page like this one for Brandon Phillips: http://www.fangraphs.com/statss.aspx...91&position=2B

You can see there that Brandon has been an above average baserunner in terms of taking extra bases, but has been only very slightly above average as a base stealer.

UBR is built into a player's WAR score. WAR is the sum of a player's UBR (baserunning proficiency) plus his wRAA (Weighted Runs Above Average to measure his hitting and base stealing proficiency) and his UZR (Ultimate Zone Rating to measure his defensive proficiency).

If you really want to go crazy with baserunning stats go to a player's expanded baseball-reference page and check out the baserunning section. You can find out more than you will ever be able to handle. You can see how often he took an extra base as a runner.

Here is Brandon Phillips' expanded B-R page: http://www.baseball-reference.com/pl...br01-bat.shtml

Refer to the baserunning section of that page. As an example of what you can learn, in 2012 there were 16 occasions when Brandon Phillips was a runner on 2nd base when the batter hit a single. He scored from 2nd only 9 of those 16 times and advanced to third the other 7 times.

In his career, Phillips has stolen 2nd base 115 times and was caught 48 times for a success rate of 70.6% (not too good). He has stolen 3rd base 38 times and caught 11 times for a success rate of 77.6% (pretty good). He has also been picked off 30 times (wow!). He has also been thrown out 52 times when attempting to take an extra base on one of his hits, attempting to tag up on a fly ball, doubled off on a liner or attempting to advance on a wild pitch or passed ball.