swyck wrote:If all the stats are low at more or less the same rate, then its still a useful guide to how players will do compared with each other.

Frankly I dont need a specific player to hit X HRs, I need my team of players to do better as a whole then the other teams of players. As long as I'm grabbing the better players all around I should be fine.

This is not true. Players that are outliers in the valuation curve are more valuable or less valuable based on how far they differentiate themselves from the mean. Grouping everyone closer to the mean takes away from this. Do it over 4 cumulative categories used in the standard 5x5 for hitting and you will be way off.

Besides, there is NO way to predict the outliers. Read Tom Tango's article on Hardball Times a few weeks ago. Individual predictions are not of great use. What fantasy players should focus on is picking a group of hitters (say 15 guys) who have an average HR (or BA, or RBI, etc. performance that will compete in the category. Eeven though the individual predictions for almost every one of those hitters will be off, the average performance wil be very, very close to what the predicted average performance was.

DK wrote:Here's my question about this year's PECOTA numbers; RynMan and I were talking about this earlier.

His name is Huston Street.

His numbers are pretty good in PECOTA, but his breakout/improve chances are both a tiny 1%, while his collapse rate is an astoundingly high 88%!

Does anyone have any idea why this is?

I noticed some other strange things like this as well. One of the Phillies top prospects Greg Golson is expected to be out of baseball by the time he is 24

DK wrote:Here's my question about this year's PECOTA numbers; RynMan and I were talking about this earlier.

His name is Huston Street.

His numbers are pretty good in PECOTA, but his breakout/improve chances are both a tiny 1%, while his collapse rate is an astoundingly high 88%!

Does anyone have any idea why this is?

Mostly because he already broke out last season, its the opposite of the Ugueto Effect. In order for him to breakout he would have to floating around the 1.10 ERA and 0.80 WHIP. He is a great young pitcher, but that isn't real likely.

DK wrote:Here's my question about this year's PECOTA numbers; RynMan and I were talking about this earlier.

His name is Huston Street.

His numbers are pretty good in PECOTA, but his breakout/improve chances are both a tiny 1%, while his collapse rate is an astoundingly high 88%!

Does anyone have any idea why this is?

For pitchers, the breakout/collapse/improve rates indicate how likely it is that his EQERA improves or declines by some corresponding percentage of his three-year EQERA. Street has had few professional innings, but over that small span, his EQERA has been much better than his peripherals would indicate. Hence, Street still has a good projection for 2006, but the odds of him improving on last years performance (EQERA wise) is very, very slight.

I have a semi-stupid question. When they are predicting improvement %, and breakout % and collapse %, is that prediction relative to their 2006 projections for the hitter? Or for the previous year's stats? Or some other metric?

Buster Douglas wrote:I have a semi-stupid question. When they are predicting improvement %, and breakout % and collapse %, is that prediction relative to their 2006 projections for the hitter? Or for the previous year's stats? Or some other metric?

They are based on improvement against the past three year weighted average for EqERA or EqR/27.

swyck wrote:If all the stats are low at more or less the same rate, then its still a useful guide to how players will do compared with each other.

Frankly I dont need a specific player to hit X HRs, I need my team of players to do better as a whole then the other teams of players. As long as I'm grabbing the better players all around I should be fine.

This is not true. Players that are outliers in the valuation curve are more valuable or less valuable based on how far they differentiate themselves from the mean. Grouping everyone closer to the mean takes away from this. Do it over 4 cumulative categories used in the standard 5x5 for hitting and you will be way off.

No, you're wrong here. If the counting stats are uniformly lowered by the same factor (say 7/8 to pick a number), a player would be the same number of standard deviations from the mean as he would have been before the scaling.

Thinking the Value remains the same is wrong. You miss the point if you think everyone is LOWERED by 7/8. They are not. Everyone regresses to the mean. So the guys at tha AVG stay at the AVG. The outliers above and below get closer.

You can ask others that do valuation, don't just take my word for it...

DK wrote:Here's my question about this year's PECOTA numbers; RynMan and I were talking about this earlier.

His name is Huston Street.

His numbers are pretty good in PECOTA, but his breakout/improve chances are both a tiny 1%, while his collapse rate is an astoundingly high 88%!

Does anyone have any idea why this is?

This is explained in the Statistical Introduction. Unlike the fantasy mags, you can't just jump right to the numbers with BP, if you want to understand their work. Read the Statistical Introduction and the section titled "Rearranging PECOTA""

swyck wrote:If all the stats are low at more or less the same rate, then its still a useful guide to how players will do compared with each other.

Frankly I dont need a specific player to hit X HRs, I need my team of players to do better as a whole then the other teams of players. As long as I'm grabbing the better players all around I should be fine.

This is not true. Players that are outliers in the valuation curve are more valuable or less valuable based on how far they differentiate themselves from the mean. Grouping everyone closer to the mean takes away from this. Do it over 4 cumulative categories used in the standard 5x5 for hitting and you will be way off.

Besides, there is NO way to predict the outliers. Read Tom Tango's article on Hardball Times a few weeks ago. Individual predictions are not of great use. What fantasy players should focus on is picking a group of hitters (say 15 guys) who have an average HR (or BA, or RBI, etc. performance that will compete in the category. Eeven though the individual predictions for almost every one of those hitters will be off, the average performance wil be very, very close to what the predicted average performance was.

Well, there's always going to be a certain error associated with projections, which we won't really be able to eliminate; though I don't understand some of your comments. No way to predict the outliers? This is a truer statement for some stats more that others, but declaring that Pierre is likely to be a SB-outlier can certainly be made from a sound statistical foundation. And individual predictions do have a fair amount of use, though their confidence intervals are perhaps larger than people realize. The suggestion that it's better to have average performers in each category rather than having certain categories covered by few sources (as is often done with SB) is true (as it's just simple statistics), but it's not really because we don't know who the outliers might be. (We're just taking on more risk, in the form of larger confidence intervals, by relying on the performance of those we expect to be outliers.)

swyck wrote:If all the stats are low at more or less the same rate, then its still a useful guide to how players will do compared with each other.

Frankly I dont need a specific player to hit X HRs, I need my team of players to do better as a whole then the other teams of players. As long as I'm grabbing the better players all around I should be fine.

This is not true. Players that are outliers in the valuation curve are more valuable or less valuable based on how far they differentiate themselves from the mean. Grouping everyone closer to the mean takes away from this. Do it over 4 cumulative categories used in the standard 5x5 for hitting and you will be way off.

No, you're wrong here. If the counting stats are uniformly lowered by the same factor (say 7/8 to pick a number), a player would be the same number of standard deviations from the mean as he would have been before the scaling.

Thinking the Value remains the same is wrong. You miss the point if you think everyone is LOWERED by 7/8. They are not. Everyone regresses to the mean. So the guys at tha AVG stay at the AVG. The outliers above and below get closer.

You can ask others that do valuation, don't just take my word for it...

Examine swyck's first sentence and assumption in the post you were reacting to.