Tango on Baseball Archives

Wolverton - Wavin' Wendells - Outs on Base (March 12, 2004)

--posted by TangoTiger at 05:21 PM EDT

Posted 11:09 p.m., March 12, 2004 (#1) - Robert S
Interesting piece.

Eddie Rodriguez, the D-Backs' recently fired 3rd base coach, had a reputation as being a "waver," too. Apparently, it was well-deserved despite Brenly's recent claims that every single batter was "just slow out of the box and needed to hustle."

Posted 3:12 a.m., March 13, 2004 (#2) - MGL
There's something obvious missing from this analysis -- the benefit of aggressive base running. If a team takes a lot of risks on the basepaths, they'll make more outs, sure, but they could also take more extra bases. The value of those extra bases is missing from the Cost columns above.

I'm shocked that this statement is presented as if it were an afterthought. There is absolutely no reason to think that extra outs on the bases is a bad thing (it might be, it might not be). It is entirely possible that the average team is way too conservative on the bases (that would be human nature - the psychological "dynamic" of baserunning is completely different from that of basestealing) such that teams with higher than average OS's may be running the bases MORE optimally. Just becuase it so happens that basestealers seem to run themselves into a near break even situation, that is not necessarily the case with baserunning. Getting thrown out on the bases, particularily at home, has such a stigma attached to it, that it is very possible (even likely) that the average team does not attempt to take the extra base nearly as often as they should. If that is the case, then the teams that were running the bases most optimally WOULD have the highest number of OS's. In fact, if Wolverton had presented the base stretching opportunities and the successful stretches as well as the OS's, you would see how conservative baserunners and coaches are (there are relatively few O'S compared to the number of opportunities and even comapred to the number of successful stretches). I have long suspected that the average baserunner/team was MUCH too conservative on the bases, and this study does nothing to address that issue. In fact, it confounds it. Without some kind of analysis on the cost/reward ratio of a team OS versus opps and success rates, the data presented in the article does not pass the "so what" test...

Posted 10:32 p.m., March 14, 2004 (#3) - Wayward
MGL, I agree with you; this data is not quite useful without the flip side of the benefit.

This reminds me of the study done recently about going on 4th down in football. IIRC the study showed that teams were far too conservative and I would, with no data whatsoever to support me, think that baseball baserunning is the same way.

Any feel for the order of magnitude of the effect of optimizing baserunning?

Posted 10:53 p.m., March 14, 2004 (#4) - tangotiger
As a general rule, I usually find these optimization things are on the order of 0.5 to 1.5 wins. By themselves, you might say "no big deal". But, add them up, and a good sabermetrician should be able to add 5 wins to a team just on optimization alone (i.e., helping the manager). (He should be able to add another 10 to 15 wins in helping the GM). At 2 million$ / win of value..... it's just crazy that not more teams pay for this.

Posted 11:29 p.m., March 14, 2004 (#5) - MGL
Tango, you are quite optimistic as far as what a good saber could add to a team! You should be my agent! Baserunning, basestealing and closer usage are probably the most valuable things in terms of optimization for a team. The jury is still out on bunting, BTW. It is NOT true that the bunt is generally a bad play.

Optimizing a lineup is ususally not worth that much either. Occasionally it makes a big difference, but usually one reasonable linuep is within a couple of runs of another.

As far as optimizing closer usage (by eliminating some of the low leverage innings the closer usually pitches, like 3 run leads in the 9th when at home, and adding some high leverage non-traditional innings, like tie games in the 8th and 9th, and using your closer for 2 innings more often), it is not clear to what extent "disrupting" traditional closer usage patterns might actually "cost" a team runs and wins.

As far as player acquisitions, trades, and valuations for salaries and contracts, that's where the "money" is. Then again, I believe that the market is much more efficient and teams are much smarter than they used to be. 10-15 wins is an awful lot of wins. I'm not even sure what you mean Tango. Do you mean that the average non-sabermetric team can increase their WE by 10-15 games on the average given the same payroll by using sabermetric analysis to evaluate players?

Posted 11:36 p.m., March 14, 2004 (#6) - MGL
Wayward, I really have no feel for how sub-optimal baserunning currently is and how many runs/wins a team could add by optimizing it. If I had to guess, I would also say .5 to 1 win per year, which is a lot for one single thing. Also, any time you can optimize something and there are probably few if any hidden costs, it is a "gift horse." For example, with optimizing bullpen (closer) usage and even lineups, there are many potential hidden costs which are hard to put a finger on.

Contrary to what Wolverton says in his article, you CAN figure out to what extent teams are optimizing their baserunning or not, and if not, how much they are costing themselves, as well as what the proper baserunning strategy should be. It is a little tricky, but it can be done. That is one of the things that Tango and I are working on for our book, and should be fascinating (as well as the bunting and other stuff)...

Posted 12:12 a.m., March 15, 2004 (#7) - Kyle S
Idea I just had that seems to fit here, so I'll throw it out and let you guys make fun of me. I was looking over Sean Forman's lecture notes he has on his SJU website where he discusses bunting. He mentions that bunting from 2nd to 3rd with no outs decreases expected runs in either case (success/failure). As an afterthought he mentions that while bunting might decrease the expected run value of the inning, it increases the likelihood of one run.

Yeah, this is obvious. It's also obvious that expected runs still depend on the hitter - ie if your pitcher is up, it's likely that bunting has higher ERV than not bunting. However, what's being left out of this analysis that is implicit is the concept of risk.

in economic terms (i'm an economics student, as I suspect many primates are), risk describes the shape of your utility function. to a layman, it maps exactly how much "utility" (whatever that is) one gets from additional units of a good. mostly, utility curves are convex.. each additional dollar brings less happiness than the one before it, for example. similarly, the utility function of runs scored is nonlinear: the first run (or the go-ahead run) is much more valuable than the 2nd (or insurance) run, and so on.

It seems to me that a reasonably sophisticated analysis could take this all into account to try to answer questions like: do we bunt the guy to 2nd if the game is tied in the 8th? when is "expected run value" not very helpful? et cetera. Does this all seem out of line, or should i start putting more serious thought into it?

Posted 4:22 a.m., March 15, 2004 (#8) - MGL
Kyle, actually it's not that complicated. We use RE (run expectancy) as a proxy for WE (win expectancy) anyway. Early in a game they are about the same. Later in a game, we want to use WE exclusively. There is no particular reason why we can't use WE and WE tables (and we should). It is just that it is easier to work with RE and generate RE tables. Figuring what strategy is the most optimal in baseball (e.g., bunting or not) has nothing explicitly to do with "risk and utility functions." It is simply that alternative which yields the highest WE (best chance of winning the game). Of course, there are sometimes hidden costs when it comes to analyzing strategy alternatives. That is not the case with bunting, although there are some game theory issues which come up.

BTW, it is not the chance of "scoring 1 run" which is relevant in close games, it is the chance of scoring "at least 1 run." There is a big difference. For example, if we put a man on second with 1 out, on the average, a team will score exactly 1 run 23% of the time. With a man on first and 0 outs, it is 18% of the time. It might seem that the former is better than the latter in a tie game in the bottom of the 9th or later. It is not. We are not concerned about the "chances of scoring exactly 1 run." We are concerned with the chances of not scoring, or the converse, the chances of scoring at least 1 run. For that, it is 43% with a runner on first and no outs and only 40% with a runner on second and 1 out. So in the bottom of the 9th of a tie game, without knowing anything about the batter, pitcher, linuep, etc., we would NOT accept an offer to move a runner to second and take an out. The WE tables confirm this. With a runner on first and no outs in a tie game in the bottom of the 9th, the WE is .715 and with a runner on second and 1 out, it is .703.

That still doesn't tell us whether it is correct to bunt or not in the bottom of the 9th in a tie game or at any point in the game for that matter. First, we need to know what the average WE is after a bunt attempt, and of course that varies with the bunter, the pitcher, and how the defense is playing. Then we need to know what the alternative would yield - what the average WE is if the batter swings away. That is real complicated. We need to factor in the hitting skill (hitting projection) of the batter, the pitcher, and rest of the run environment (park, weather, etc.). On top of that we need to adjust that hitting skill for the fact that the defense is maybe (probably is) expecting the bunt. As it turns out, the final 2 numbers (WE bunting and WE not bunting) are awfully close, a lot closer than most sabers think, such that whether bunting is "correct" or not depends on a dozen factors or so and is not that easy to figure out.

The final "answer" will be in a "rule of thumb type table," that looks something like Tango's "walk Bonds or not" table - yes, no, or "use your intuition (flip a coin)," with the rules of thumb criteria being "good, bad, or average hitter, lineup slot, good, bad or average pitcher, low, med, or high run scoring environment (park, weather), good, average, or bad bunter (speed/skill of bunter), position of defense (expecting a bunt or suspecting a bunt), and inning/score of game"...

Posted 9:16 a.m., March 15, 2004 (#9) - tangotiger
MGL, batting order optimization can add 0.5 to 1.5 wins. As long as the #2 hitter continues to be an average hitter, teams have alot of places to improve upon.

And yes, giving the exact same payroll, a good sabermetrician should be able to add 10 wins to his GM. This means that there's 20 million$ being poorly allocated. So, a well-run sabermetric team with a 70$ million payroll is equivalent to a poorly-run nonsabermetric team with a 90 million$ payroll. And I think I'm being conservative.

Posted 11:58 a.m., March 15, 2004 (#10) - J Cross
well, in their essay on catcher's value (BP2004 book) in the running game they concentrate on preventing steals and rank catcher by steals prevented but talk about the extra outs as an afterthought. As far as I could tell they didn't combine prevented steals and extra outs into a value number because the value of these extra outs depends on the base/out situation and whether the team was playing for one or more runs. Still it seems ridiculous to ignore them completely. It's really a cop out considereing that this study used play-by-play data and could have made an attempt to figure this out.

They ranked Piazza as the worst catcher based on career numbers because he's allowed an extra ~400 steals compared to an average catcher (I forget the exact number but that's somewhere in the ballpark) but ignore the fact that by their calculation he had an extra ~150 outs above the average catcher because runners ran against him so often. 400 extra steals and 150 extra outs might not be so bad. In total I'm guessing it's not bad enough to support the statement that their study suggests moving Piazza to first is a good idea (although I think that moving him to first is a good idea for other reasons).

btw, I also don't trust their added outs numbes or know how they got them. One year that gave Hatteberg 8 CS but 22 added outs so I think they either messed up or I'm missing something. I'll re-read the essay tonight.

anyway, my point is that the analysis coming out of BP lately (eg "waving wendell" and "tall catchers") hasn't been very impressive. I think the forumlas they used for their fantasy forecast manager are just wrong. What's going on? I'm getting a little disillusioned with Prospectus. Can't wait for the Tango/MGL book.

Posted 12:22 p.m., March 15, 2004 (#11) - Kyle S
MGL, win expectancy sounds pretty close to what I was talking about, but I don't see how it can't include some measure of risk. My point was that in a tie game in late innings, given the choice between (15% chance of no runs 80% chance of 1 run and 5% chance of 2+ runs) versus (30% chance no runs 40 % chance 1 run 30% chance 2+ runs), although the run expectancy of the 2nd situation might be higher (i have no idea, i pulled those numbers out of the air), the first run is most important.

It seems like win expectancy accounts for this, so it doesn't matter. Perhaps we're saying the same thing - as the first instance has a higher chance of scoring "at least one" run so you would take it. I'll trust you since you've actually done the math.

Posted 12:28 p.m., March 15, 2004 (#12) - tangotiger
J, you're going to have to wait a while. I think MGL and I have good intentions, and we had great momentum up to a point. The outline we have written out, along with the ideas for research, is really something great to work from. But, we have let other things take precedence.

Right now, I'm having the most fun working on the Fans' Scouting Report. I think there's great payoff there. Just wait until I roll out the "Similarity Scores" for fielders! For example, Derek Jeter's most similar fielding comp is Bobby Abreu. There are NO similar fielders to Vlad. That's what YOU fans say. This sabermetric stuff to me is a hobby and it's supposed to be fun. And, this Scouting Report is loads of fun. Is Mark Ellis' UZR real? Well, you fans think he's a GREAT fielder, so this makes it more reliable. But, Eckstein is average according to the fans. So, maybe his UZR should be regressed more heavily.

The only way to get back into the book is to really shut down everything. No more Primate Studies, no Fanhome, no Clutch, no web altogether. I can shut all that, except Studies. I find I gain so much talking with you guys at Primate Studies that I'm not sure it's worth it.

I wrote a Markov Chain Batting Order program. It's really cool (programmatically, I take great pride in it), and I did it a few months ago. I needed it for one chapter in the book. There's a bug in it, and after a day, I stopped looking for it. I was going to get back to it, as I usually like to relax for a couple of days before going back into it. But, I have not. I went on to something else, because it's more fun for me to do so.

So, who knows what we'll do.

Posted 12:31 p.m., March 15, 2004 (#13) - tangotiger (homepage)
Kyle, the above link probably is saying what you are saying. It's not a question of the measure of risk, but rather what are the probabilities of a given situation, regardless of how much spread there is in possible outcomes.

Posted 3:16 p.m., March 15, 2004 (#14) - David Smyth
---"well, in their essay on catcher's value (BP2004 book) in the running game they concentrate on preventing steals and rank catcher by steals prevented but talk about the extra outs as an afterthought. As far as I could tell they didn't combine prevented steals and extra outs into a value number because the value of these extra outs depends on the base/out situation and whether the team was playing for one or more runs."

My understanding of why Woolner chose to focus on SB prevented is mainly that he thinks it's a better indicator of ability, in terms of future value. He believes that, with the large amount of info available to the runners, that any weird performances (such a lots of attempts on a guy with a great arm, or vice versa) will not carryover. It's an interesting idea, but then he goes ahead and ranks catchers' careers using the same concept, which doesn't seem to make lots of sense. Sort of a "lazy" piece of work by Woolner, and also not well-written...

Posted 2:31 p.m., March 16, 2004 (#15) - Rally Monkey
There are NO similar fielders to Vlad. That's what YOU fans say.

Interesting. If I had to pick the most similar, it would be his new OF teammate, Guillen. Decent speed, a few too many e's, great arm. I only rated the Angels from last year, though.

On the markov chain batting order, there is one that comes with the software for APBA baseball.

Optimizing a lineup is ususally not worth that much either. Occasionally it makes a big difference, but usually one reasonable linuep is within a couple of runs of another.

MGL, last summer you were arguing pretty strongly for optimizing lineups. What's changed?

Posted 9:47 p.m., March 16, 2004 (#16) - tangotiger
The APBA one I think comes from Mark Pankin, and he's the guru of batting orders.

Posted 9:55 p.m., March 16, 2004 (#17) - MGL
MGL, last summer you were arguing pretty strongly for optimizing lineups. What's changed?

Sometimes it makes a big difference, sometimes it doesn't. Sometimes it makes a small difference and sometimes it doesn't. Not much more I can say. Without looking at a year or 2 worth of team lineups and then comparing them to an "optimal" lineup, I can't even begin to say with any certainty how sub-optimal lineups are on the average. If I had to guess, I would say that the average linuep is less than 5 runs per year sub-optimal. That doesn't mean that there is an occasional really bad linuep. Some things just have to be looked at on a case by case basis...

Posted 8:18 a.m., March 17, 2004 (#18) - tangotiger
I agree that it's a case-by-case basis. Any team that doesn't have one of their 2 best hitters as the #2 hitter is almost definitely suboptimal, and you can gain at least 5 runs. I would say this is the case for most teams.

Posted 2:40 p.m., March 17, 2004 (#19) - AED
I've got a fairly detailed program to optimize lineups. Looking at a sample of about 5 teams last season, the mean improvement was 0.1 runs per game. Bullpen usage can typically be improved by 3 wins, though of course it depends on the manager's tendencies. Other tactics, like bunts, steals, etc. can profit a team another win or so. So I think Tango's estimate of about 5 wins for optimizing an average team is correct.

Posted 2:46 p.m., March 17, 2004 (#20) - tangotiger
[Spam between posts #14 and #15 was deleted]

Posted 2:51 p.m., March 17, 2004 (#21) - tangotiger
AED, very interesting. 0.1 RPG = 16 runs per season. That's on the high-side of what I was expecting. MLB is in worse position than I thought! Can I take a guess that in your 5 teams, all of them had a #1 and/or #2 hitter that is considered at best average?

As a rule of thumb, your 3 best hitters should hit somewhere 1,2,4.

Posted 9:28 p.m., March 17, 2004 (#22) - MGL
AED, I am surprised also. Can you tell us the 5 teams and the lineups you optimized? I'd like to check it on my sim as well. I think the bullpen usage (I assume you pretty much mean the closer) is high also (3 wins). Can you tell us how you arrived at that?

Posted 10:38 p.m., March 17, 2004 (#23) - J Cross
As a rule of thumb, your 3 best hitters should hit somewhere 1,2,4.

Is this true if the pitcher is hitting 9th or only if your worst hitter is hitting 7th or 8th?

Posted 1:27 p.m., March 18, 2004 (#24) - FJM
Most teams try to put their best overall hitter in the #3 spot. Are you saying that the typical lineup is seriously suboptimal for that reason alone? Why is it better to have your best hitter in the cleanup spot as opposed to #3?

Posted 1:53 p.m., March 18, 2004 (#25) - tangotiger
If you check out the Primate Studies index, I have a "workshop" on batting orders. If you have 2 or 3 hours, I suggest reading that.

Posted 5:15 p.m., March 18, 2004 (#26) - Rally Monkey
Why is it better to have your best hitter in the cleanup spot as opposed to #3?

The number 3 hitter is least likely to lead off an inning. The ideal #3 hitter has a high slugging percentage but not one of your best OBP. I read this in one of the old baseball abstracts. Bill tried to optimize the lineup by getting a high OBP leading off innings 1 and 2. After 2 innings, its pretty hard to predict who leads off an inning. If your #3 leads off the second inning, then you probably don't have to worry about scoring runs.

Garret Anderson would be a good #3. Too bad the Angels plan on batting Vlad #3 and Garret #4. I wonder how many runs this will cost.

Posted 5:34 p.m., March 18, 2004 (#27) - J Cross
So, the Sox shouldn't have switched Manny to 3 and Nomar to 4.

Posted 5:36 p.m., March 18, 2004 (#28) - tangotiger
Off-hand, I'd say put Nomar 2 and Manny 4.

Posted 6:52 p.m., March 18, 2004 (#29) - MGL
From playing with lineups on my sim a million times, I would have to say (asuming that the answer lies in the sim) that "rules of thumb" don't work very well when it comes to individual lineups. For example, you can often put a poor, but fast hitter at the top of the linuep and you are still reasonably optimal. K. Robinson batting number one for the Cards works about as well as Renteria even though Edgar is vastly the superior hitter...

Posted 7:00 p.m., March 18, 2004 (#30) - Rally Monkey
According to the APBA program, switching Vlad and GA is worth about .01 RPG. Switching Erstad to #9 and Kennedy to #2 is worth another .01

The optimal lineup shocked me. It adds .06 RPG, or 10 per year. Here it is along with my projected OBP for each player:

Glaus .381
Vlad .421
Salmon .360
GA .332
Kennedy .342
Guillen .328
Erstad .325
Molina .296
Eckstein .353

Makes me nostalgic for the days Brian Downing led off.

Posted 10:19 p.m., March 18, 2004 (#31) - tangotiger
Could you also list their SLG? My rule of thumb would have the largest gap for the #4 hitter in SLG-OBA, and smallest for the #1 hitter, all the while having the top OBA*1.8+SLG for the #2 hitter, with #1 and #4 close behind.

Posted 11:08 p.m., March 18, 2004 (#32) - MGL
Rally, I don't understand you comments. Is the lineup you posted the optimal lineup (according to APBPA)? Adds .06 rpg as compared to what? Switching Kennedy to 2 and Erstad to 9 from the linuep you listed? or from what lineup? So the listed linuep is NOT the optimal one?

Posted 11:35 p.m., March 18, 2004 (#33) - MGL
The key to using a sim to estimate optimal lineups in real life is having reasonable projections for each player. Without that, the sim is near worthless for optimizing lineups. Does APBA set the stats for each player or does the user? If the former, do they use a good projection engine? If it is the user, what do you use for the projections? Does it allow you to set each component or just OBP and SLG (or something like that)?

I ran your lineup thru my sim and it generated 4.978 rpg versus a typical RHP. I then used an internet version of the real projected ANA lineup, which is (the numbers are their lwts per 150 projection):

Erstad -13
Eck -19
Vlad 35
GA 2
Salmon 3
Glaus 23
Guillen -4
Molina -36
AK -14

This generated 4.867 rpg versus the same pitcher, a difference of 18 runs per 162, which is huge. Then again, I don't consider the above linuep to even be reasonable (having 2 of your worst hitters hitting 1/2), although I'm sure that Scocsia does.

I think this is a relatively rare example of a big difference between a manager's lineup and the optimal one (on paper).

Let's see if I can tweak your lineup to make it better...

I didn't try all the combinations, but I couldn't do any better...

Posted 12:24 a.m., March 19, 2004 (#34) - J Cross
Theo has a simulator. He said that the Sox were projected to win 100.6 games and the Yankees 100.7. But this is the lineup the Sox are planning on using (I think):

Damon
Mueller
Ramirez
Garciaparra
Ortiz
Millar
Nixon
Varitek
Reese

How different would the following lineup be?

Nomar
Ramirez
Ortiz
Nixon
Millar
Mueller
Varitek
Reese
Damon

Posted 3:18 a.m., March 19, 2004 (#35) - MGL
Off the top of my head, it looks pretty ugly batting a good and fast hitter last and behind the only real lightweight in the lineup, but you never know...

The first lineup scores 5.178 rpg (versus a RHP) and the second scores 5.143, which is 3 runs worse per 120 games (typical number of games verus a RHSP).

Versus a LHP, the first lineup scores 5.617 and the second scores 5.658. The thing about optimal lineups is that there is usally one for RHP's and one for LHP's, especially if a team has several LHB's like Boston (and maybe different ones for GB or FB pitchers, a la Mike Gimbel)...

Posted 8:40 a.m., March 19, 2004 (#36) - tangotiger
You definitely want a diff lineup or LH/RH and GB/FB. Heck, since it's all done by computer anyway, I'd have a different one by park.

Of course, the devastating pyschological impact of moving Manny from 2 to 4 to 2 might be something from which he would never recover. Funny how these world-class athletes are the most susceptible to things that would never bother a kid in high school.

Posted 11:31 a.m., March 19, 2004 (#37) - J Cross
Wow. That discussion of Batting Orders by LW is pretty dense. Correct me if I'm wrong but from what I understand you would take each players linear weights in a lineup slot compared to an average player in that lineup slot and find the lineup that maximizes the sum of these values? (MGL's sim isn't available to open) In order to do that you used empirically determined linear weight values of events for that spot in the lineup?

Here's my hangup. In a typical lineup you wouldn't want a homerun hitter in the top 2 slots because he doesn't have enough runners on base (and also had great hitters behind him) and you wouldn't use the #9 hole as a second leadoff hitter because a) there are bad hitters in front of him so a HR has high relative value compared to a hit or walk and b) the best hitters aren't up until 3,4,5.

BUT if you both place you best hitter in the 2 hole AND place a "second leadoff hitter" type in the 9 hole then don't you both give the 2 hitter situations with more runners on (and fewer great hitters behing him) thus increasing the value of his HR's and give the 9 hitter's obp more value? So, could a combination of two things that are bad in a typical lineup be good when used together?

The LW or events per batting order slot are true for the average lineup, right? Wouldn't they be different in any given lineup?

Earlier in this thread Tango mentioned using the highest slg-obp hitter in the 3 hole b/c the 3 hitter is least likely to lead off an inning. Isn't the fact that the 3 hitter leads off fewer innings than the 2 hitter mostly a function of how lineups are typically constructed and not something inherent to the structure of the game?

Posted 11:46 a.m., March 19, 2004 (#38) - Rally Monkey
The lineup posted in #30 is .06 rpg better than the lineup they will probably use:

Eckstein
Erstad
Vlad
Anderson
Glaus
Salmon
Guillen
Molina
Eckstein

Posted 11:50 a.m., March 19, 2004 (#39) - tangotiger
Wouldn't they be different in any given lineup?

YEs, but I don't think much. In my batting order sim, one thing I wanted to do is figure out whether the structure of the batting order has more impact than who the players are in those lineups, to determine the LWTS by batting order.

Posted 12:12 p.m., March 19, 2004 (#40) - J Cross
Is your batting order sim really a "sim" or more of an equation? I understand wanting to use an equation so that you know WHY a hitter is better suited for a given role but shouldn't you compare the results of your sim to something like a diamond-mind sim?

Posted 12:52 p.m., March 19, 2004 (#41) - tangotiger
I have a Markov Monte Carlo sim. It's just a couple of steps from being "perfect", but those last 2 steps are a time-killer. Tippett at DMB did a similar one last year. Mark Pankin has the best one that I know of. Ben Baumer might have one, but I'm not sure if he uses Markov or not.

Posted 1:09 p.m., March 19, 2004 (#42) - J Cross
Oh, okay, well that should take care of my hangups. From what I remember of the description of Baumer's "Pinch Hitter" is was using Markov.

Posted 2:34 p.m., March 19, 2004 (#43) - tangotiger
I think Nate Silver also has one from a blurb I saw on BP.

***

If ever you try to write one, you will have to think of having 4,5, or 6 dimensional arrays, and making it recursive. As a programming challenge, it's great. But, it's a huge time killer. And debugging it is a b-tch, especially if you are doing it on the side, a half-hour at a time.

Posted 4:38 p.m., March 19, 2004 (#44) - J Cross
I think I'd have to learn how to write a computer program first... but then.

Posted 5:08 p.m., March 19, 2004 (#45) - MGL
Don't know how much difference it makes, but if you use a Markov type sim, you have to at least include the speed of the players on the bases.

Mine is a "true sim" which actually "plays" the game, using log5 matchups between the batters and pitchers, pinch hits, plays the infield in, steals, errors, wp, etc. Don't know how much, if anything, all these "extras" affects the optimization of lineups. I assume that programs like DMB are also "true sims"?

Posted 1:25 a.m., March 20, 2004 (#46) - AED
MGL, the five teams I checked lineups for were the Yankees, Diamondbacks, Cardinals, Astros, and I'm not sure of the other. For the first three, I used their typical lineup; the Diamondbacks seemed to use a different batting order every single game so I did my best guess of their 'usual'.

The bullpen analysis was done for only a couple teams, since it took a lot more work. The Diamondbacks had 2-3 very good relievers, but gave almost all of their "tied game" work to someone else. Maybe other teams were less blatantly inefficient, in which case the number of wins gained would be less.

Posted 2:23 a.m., March 20, 2004 (#47) - MGL
AED, for a team that has more than one excellent short reliever (or more importantly, no one reliever who is a lot better than the others), they will pretty much use them optimally be default. IOW, in almost all high leverage situations, one good releiver or the other is probably going to pitch. The only time a team shortchanges itself in terms of sub-optimal use of their best reliever(s) is when they put in a reliever who is substantially worse than their best reliever in many high leverage situations (and presumably "waste" their best reliever in many low leverage situations - like ahead by 3 runs in the 9th at home). For example, when the Yankees had Rivera and Wettelend, they pretty much had a great releiver pitch in all high leverage situations. Ditto for Wagner and Dotel on the Astros and probably some other teams as well.

As far as I can tell, the biggest gain from a non-traditional use of the closer comes from using him in the 8th or the 9th in tie games and then using him for another inning if the game is still high leverage. If you aren't going to use him for 2 innings no matter what, then the gain from optimizing his use is not that great. What happens in that case is that a lot of the times you bring him in in the 8th in a fairly high leverage situation, you will not use him in the 9th in an even higher leverage situation. Some manages and pitching coaches will tell you that they don't like using their closer for more than one inning no matter what, so who knows....

Posted 3:03 a.m., March 21, 2004 (#48) - MGL
The Diamondbacks had excellent relievers in Valverde (ERA=2.15), Mantei (ERA=2.62), and Villareal at times (ERA=2.57). Yet the bulk of the work in tie games went to Oropesa (ERA=5.81). Granted that this may be an especially egregious case, and part of Valverde's low ERA was due to batting average on balls in play, but it isn't the case that managers with 2+ good short relievers will have close to an optimal bullpen usage.

Posted 7:27 p.m., March 21, 2004 (#49) - AED
wow, I was posting much too late... That last post (#48) was me, not MGL. sorry!

Posted 9:43 p.m., March 21, 2004 (#50) - MGL (the real one)
That freaked me out! I didn't remember posting that! I've done that before, BTW. Anyway, if a manager has 2 good relievers and insists on giving high leverage work to an inferior third one, that is just plain crazy (grounds for immediate firing in MGL's book).

One must be very careful how they characterize the quality of a reliever. You cannot characterize them as good or bad by their ERA after the fact. Your best releiver is one who has the best projected ERA at any point in time, certainly not the one who has the best actual ERA at any point in the season. That is the biggest mistakes that managers make - going with the "hot hand" in their bullpen. If you want to talk about whether ARI used their bullpen optimally or not, first you have to establish who were their best releivers going into the season (projections, projections, projections) and then updated as the season progressed. Any time we evaluate decisions based on quality of players we MUST always think in terms of the projections for the players in question at the time the deicision is made. All too often many otherwise intelligent analysts on Primer make that mistake. They either use short-terms stats, after the fact stats, or cherry pick some stats to support an opinion about a particular decision. If you are going to talk about a decision (whether it was a good or bad one) from a sabermetric perspective, you must use a sabermetric analysis at the time the deicison is made as the context for the analysis. A perfect example of that is the OAK signing of Dye, who has turned out to be bust (and injured) of course. Hardly anyone ever discusses "at the time of the signing, what was Dye's short and long term projection (VORP or whatever)?"

AED, you just did it yourself, assuming you are quoting their respective 2003 ERA's (although you did qualify that with the BIP thing).

BTW, Oropesa's ERC last year was 3.85, which is about average for a short reliever. He did suck though prior to that. He would not have even been pitching in my bullpen in 2003 let alone in high leveage situations. Even Mantei who was once good and had a real good ERC last year, sucked in 2001 and 2002 (was hurt I guess). Funny, Valverde and Villareal also sucked in 2001 and 2002 and they too had terrific 2003's. It's a good thing I wasn't in charge of the ARI bullpen last year. I wouldn't have had any of those guys (except maybe a healthy Mantei) pitching for me. Anyone know what the 2003 Pecota projections were for those 4 pitchers?

Posted 1:58 a.m., March 22, 2004 (#51) - Danny
A perfect example of that is the OAK signing of Dye, who has turned out to be bust (and injured) of course. Hardly anyone ever discusses "at the time of the signing, what was Dye's short and long term projection (VORP or whatever)?"

Actually, I think the reason many people, including myself, think that was a bad signing is that Dye was signed the offseason after his terrible leg injury in the ALDS. Signing a player to a 3 year, $32M deal without having seen how he will recover from a serious leg injury seems like a mistake. Of course, no one could have predicted Dye being one of the worst players in MLB in 2003.

Anyone know what the 2003 Pecota projections were for those 4 pitchers?

Mantei: 47 IP, 47 K, 25 BB, 4.14 ERA
Oropesa: 42 IP, 32 K, 23 BB, 5.05 ERA
Villarreal: 80.7 IP, 58 K, 41 BB, 4.77 ERA
Valverde: No Projection

Posted 10:33 p.m., March 23, 2004 (#52) - AED
MGL, I used those numbers because they were the easiest to find. Here are the 2003 PECOTAs:
Mantei: 4.14
Oropesa: 5.05
Valverde: none
Villareal: 4.77
(Valverde was listed in BP2003, but had been injured in 2002 so they didn't make a projection for him.)

But I wasn't thinking of the PECOTAs, as much as the fact that the Diamondbacks themselves have touted Mantei as their ace closer and Villareal and Valverde as top prospects, while they released Oropesa after 2002. So they sent the reliever with the worst PECOTA, the worst actual 2003 stats, and the least confidence into tie games.

I could be wrong, but I don't think this reliever pattern is all that uncommon. It seems that a fairly typical pattern is to use the top relievers only when winning or to get them innings.

Posted 2:11 a.m., March 25, 2004 (#53) - Robert Dudek
MGL,

You mean if your scouts told you that Valverde was ready to come up mid-season you wouldn't have promoted him? I don't believe it.

Posted 10:37 p.m., March 25, 2004 (#54) - MGL
You mean if your scouts told you that Valverde was ready to come up mid-season you wouldn't have promoted him? I don't believe it.

I'm not sure what you mean. My projection for him going into 2003 was not very good. His MLE's showed a pitcher with a great K rate and a horrendous BB rate. Everything else was OK. Plus he only had 52 IP's in AA and AAA prior to 2003. The key to his success was clearly going to be his control. I assume he has excellent stuff (I don't recall seeing him, but his K rate is so high, he must). His control was much better in the majors last year, but there is still room for improvement there. We expect his "hits allowed" to regress quite a bit in 2004 (DIPS) as they were ridiculously low in 2003.

The answer to your question is that:

1) It depends on what his stats at mid season looked like. I would simply update his projection.

2) Once I had a scouting report on him, I could tweak the projection (basically adjust the "mean" towards which I regress).

3) I would have to ask the scouts about his control - e.g., has someone been working with him on his mechanics to improve his comtrol?

4) I have no problem deferring to the scouts on a young prospect, as my projection is not going to be very reliable in the first place, especially if I have only 52 innings of history (MLE's), and I cannot "project" development in pitchers.

Why did you ask about "mid-season?" That is what confuses me about your question.