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Postby The Loveable Losers » Mon May 29, 2006 9:59 am

The_Met_Threat wrote:
The Loveable Losers wrote:
The_Met_Threat wrote:What about Jason Bay... is the power for real, will he get the bonds treatment because of no protection in that crap pittsburgh lineup? maybe you could look at stuff like px, fb%, babip etc.


Before I start this post I apologize for the lack of apostrophes...my apostrophe key wont work right now.

Never been too crazy about the px statistic. Dont get me wrong - I think it is a very worthwhile stat as far as measuring true power but as fantasy owners we care very little about doubles or triples - just like chicks we dig the longball. Px if I remember right tracks all type of power. Its definitely worth looking at things like fb% and in Bays case lineup protection though.

I avoided Bay like the plague in every league in which I played but that had nothing to do with thinking he wasnt a great player. His issue for me is that he had never run like this in the past and while he put up 22 sbs last year he did it in 23 attempts. Once teams start paying attention to him hes going to get a few less sb attempts not to mention that there's no way he keeps his sb% up as high as it was...I think the highest in history with a large enough number of sbs to be considered is Eric Davis and his was only around 80% or so. That means he is a 30-35hr 14-18sb type guy on a bad offensive team. VERY good guy to have but not for where he was likely to be drafted.

I may have to take a look at Bay...he would be an interesting one to examine. I might do Soriano too just because of all the hubub right now over people being 'wrong' to think he wouldn't hit 280-290 in RFK while driving in and scoring close to 100 runs despite playing for a bad offense in a bad park.


Actually i believe the best sb% in the game with a certain minimum is Carlos Beltran.


Should have mentioned I was talking about career numbers. I'm sure there have been lots of people that had single seasons like Bay and Beltran did...it's just not sustainable over an entire career. The number is in a statistical reference book and it had Davis at the top...I think it required something like 150 or 250 minimum stolen bases.
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Postby The_Met_Threat » Mon May 29, 2006 8:42 pm

The Loveable Losers wrote:
The_Met_Threat wrote:
The Loveable Losers wrote:
The_Met_Threat wrote:What about Jason Bay... is the power for real, will he get the bonds treatment because of no protection in that crap pittsburgh lineup? maybe you could look at stuff like px, fb%, babip etc.


Before I start this post I apologize for the lack of apostrophes...my apostrophe key wont work right now.

Never been too crazy about the px statistic. Dont get me wrong - I think it is a very worthwhile stat as far as measuring true power but as fantasy owners we care very little about doubles or triples - just like chicks we dig the longball. Px if I remember right tracks all type of power. Its definitely worth looking at things like fb% and in Bays case lineup protection though.

I avoided Bay like the plague in every league in which I played but that had nothing to do with thinking he wasnt a great player. His issue for me is that he had never run like this in the past and while he put up 22 sbs last year he did it in 23 attempts. Once teams start paying attention to him hes going to get a few less sb attempts not to mention that there's no way he keeps his sb% up as high as it was...I think the highest in history with a large enough number of sbs to be considered is Eric Davis and his was only around 80% or so. That means he is a 30-35hr 14-18sb type guy on a bad offensive team. VERY good guy to have but not for where he was likely to be drafted.

I may have to take a look at Bay...he would be an interesting one to examine. I might do Soriano too just because of all the hubub right now over people being 'wrong' to think he wouldn't hit 280-290 in RFK while driving in and scoring close to 100 runs despite playing for a bad offense in a bad park.


Actually i believe the best sb% in the game with a certain minimum is Carlos Beltran.


Should have mentioned I was talking about career numbers. I'm sure there have been lots of people that had single seasons like Bay and Beltran did...it's just not sustainable over an entire career. The number is in a statistical reference book and it had Davis at the top...I think it required something like 150 or 250 minimum stolen bases.


I know, i was talking about career numbers. Beltran has around 87%, davis has 84.
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Postby The Loveable Losers » Mon May 29, 2006 8:47 pm

The_Met_Threat wrote:
The Loveable Losers wrote:Should have mentioned I was talking about career numbers. I'm sure there have been lots of people that had single seasons like Bay and Beltran did...it's just not sustainable over an entire career. The number is in a statistical reference book and it had Davis at the top...I think it required something like 150 or 250 minimum stolen bases.

I know, i was talking about career numbers. Beltran has around 87%, davis has 84.


Ahhh, the reference book I was reading was probably published before Beltran got to that point. 87% is just sick...even the Oakland A's would green light a guy like that. :D
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Postby The_Met_Threat » Mon May 29, 2006 9:21 pm

The Loveable Losers wrote:
The_Met_Threat wrote:
The Loveable Losers wrote:Should have mentioned I was talking about career numbers. I'm sure there have been lots of people that had single seasons like Bay and Beltran did...it's just not sustainable over an entire career. The number is in a statistical reference book and it had Davis at the top...I think it required something like 150 or 250 minimum stolen bases.

I know, i was talking about career numbers. Beltran has around 87%, davis has 84.


Ahhh, the reference book I was reading was probably published before Beltran got to that point. 87% is just sick...even the Oakland A's would green light a guy like that. :D


Too bad Willie won't. :~(
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Postby Philliebuster » Wed Jun 07, 2006 9:33 am

LL, i'd be interested to hear your take on Mr. Huff, what do the numbers say oh wise one.
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Postby The Loveable Losers » Wed Jun 07, 2006 10:22 am

Sorry about the two week hiatus here.

There are a couple projects that I am trying to find answers to right now which may take me a bit. One of them has to do with properly evaluating middle relievers. The tricky part - and the worthwhile part in my opinion - is trying to predict the most unpredictable part of the ledge - the wins. To that end I am going to look into usage patterns, team run differential and possibly some other things as well. While usage patterns are hard to pinpoint what I hope to find is a way to at least predict how many wins you can expect out of a guy like Scott Shields or Scott Linebrink - guys that are used exclusively in close games in the late innings.

I think that there should be a way to at least estimate wins expected based on team runs per game (the more a team scores the higher the chance of a come-from-behind victory) and team run differential (the smaller the run differential the higher the chance of coming in to a close game). I'm still in the idea stage here and I'm going to have to crunch a large amount of data to test my theories but I think it would be worth it to at least have an idea of how many wins you can expect from a reliever. MR wins are highly underrated in standard Yahoo roto leagues (1250 max IP) as a MR that wins even 6 games in a typical 75 inning work load has just matched the win production of a full time SP that wins 18 games. I would guess that MR's that can win 6 games are more common than SP's that can win 18 simply because the MR's are pitching a single high leverage inning - they only have to have 1/6th the chance of getting a win as the SP to break even. I want to be able to quantify the percentage chance that a high leverage reliever on a given team will get a win which will allow us to quantify the value of a MR to your wins column.

The other project is something I just came up with last night. I'm working on a couple new formulas (similar to my pWhip formula you can read following the articles list link in my sig) for predicting player performance. These two are more benchmark numbers that allows you to compare players than predictive numbers but I think they'll be useful.

One is going to compare the ratio of k + hr to ab's. The higher this ratio the less volatile a player's batting average should be since the majority of outs are 'being decided at home plate'. I'll be looking for a league average and an average of likely rostered players for different league sizes which will give us different benchmarks to compare volatility in batting average. Obviously the larger time period you look at the better this number will work...looking at guys like Pujols or Soriano (who probably won't keep up their current hr paces) and using only this year's data would be a mistake with this number (as it is with many numbers).

The other number is a bit trickier. I want to come up with some sort of a formula based on the ratio of a weighted difference between hr's and k's to the hitter's ab's (and possibly the hitter's expected BABIP). The goal here would be to find one of two numbers...if I can find universal weights for hr's and k's then the number is going to show us the positive (or negative) affect that the plays determined at home plate have on the hitter's average. If I find universal weights with which I am happy I will try to express this formula as a 'batting average supported by plays determined at home plate'. Obviously I could just take hr/(k+hr) to determine the actual batting average on plays determined at home plate but that's not the what my first goal would be.

My first goal would be to put a number on here of what a player with this type of hr's and k's compared to a certain number of at bats is likely to hit average-wise. The universal weights may not be easy to find though and in that case I would have to use the hitter's own projected BABIP as the determinant for the weights to use. This would allow us to show accurately how positively or negatively the plays at the plate should affect the hitter's average but is less useful because it's a lot more cumbersome. I'd almost rather have less accuracy in the number (within reason) to have a more useful number here.

So it may be a while before we see any new player articles. The MR study and these formulas are going to take a lot of research and effort but what may come out of them is worth the time.
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Postby The Loveable Losers » Thu Jun 15, 2006 2:39 pm

Well it took awhile to say the least. I had to put quite a bit of preliminary thought into the concepts involved in projecting wins and then spend almost as much time playing with the full pitching data from the 2003-2005 seasons to get at the numbers that I wanted but I finally got there.

Projecting Wins

Excerpt:
If you have the roster space for a Scott Shields or any other MR that projects to at least match if not better the IP / win ratio of a replacement level starting pitcher then it makes a lot of sense to pick them up. Since their ratios (k/9, era and whip) are usually superior to all but the best starting pitchers even a slightly worse IP / win makes them a positive play. When the IP / win is in favor of the middle reliever it becomes a no-brainer - a quality middle reliever is usually better for your end of the year bottom line in wins than a mediocre starting pitcher.


The excerpt there is more to put the entire exercise into a direct fantasy context though...the actual article is fairly detailed and basically gets you to the point of having the IP / win number that you need to make informed decisions.
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Postby The Loveable Losers » Thu Jun 15, 2006 3:37 pm

garf112 wrote:excellent work on the MR wins.

On your second project, isn't a players batting average dependent on more than the number of times he strikes out and homers? You would need to factor in his gb/ld/fb rates. I think I'm understanding what you are saying, but hasn't most of this work been done?


All of this work has been done. That second project is just a different way of looking at that same information - it's determining what a hitter with certain k/hr/ab ratios would hit if he was average in the gb/ld/fb rates. The reason this is significant is that it tells you what type of average the non-luck portion of his game is able to support.

I may can that part of that project altogether though for lack of a meaningful way to express the numbers. However I definitely am going to be taking a look at the (k + hr) / ab%'s and how those affect the variability of a hitter's average. If a guy has 40% of his at bats determined at home plate I would expect the average to be less variable than a guy that has only 20% of his at bats determined at home plate. This isn't a radical new concept...more of a different metric to examine with a hitter. I'd probably call the number 'batting average variability' or something along those lines and measure it based on comparison to the average...letting you know what risk there is associated with a hitter being able to post the expected batting average.
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Postby The Loveable Losers » Thu Jun 15, 2006 4:00 pm

garf112 wrote:If he was at HIS average for gb/ld/fb? or at the league average? I was under the assumption that a hitter DOES have control over those percentages and tends to hit roughly the same amount each year, with some peaks and valleys added in.


League average. The number isn't meant to represent what we expect from the hitter as far as batting average goes. It's meant to express what batting average you would expect from a player with a .300 BABIP that put up those same k/hr/ab numbers.

The reason it's designed that way is so we can see how well the batter's plays determined at home plate support a good batting average. By expressing it versus the league average you do two things - you standardize the number and you make it easier to determine as well since you don't have to determine the expected BABIP for each hitter. It's not intended to use in projecting batting average...it's more to give a second view of the batting average variability. The (k + hr) / ab% gives us the range of values while the batting average using the league average gb/fb/ld percentages lets us know how good the hitter is at keeping his outs in the field and his hits out of the park.

The one thing I'd consider too for the k + hr / ab% is trying to find different weights for the k's and hr's too...a k is much less important than a hr and needs to be represented as such.
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Postby The Loveable Losers » Thu Jun 15, 2006 4:05 pm

By the way, the two players that pop right into my head when I think about this project are Adam Dunn and Ichiro Suzuki. Dunn would have a very low expected average but at the same time have a very low variability (since every at bat for him seems to end in a home run or a strikeout). Ichiro on the other hand would have a decent expected average but a VERY high variability - he rarely strikes out or hits a home run.

That variability has been on display with both of them. Dunn always plods along within about .016 points of his career average. Ichiro on the other hand can fluctuate about .035 points either way over the course of a season.
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