2007 Season Predictions - Page 3

Heltonfan · 03-01-2007, 09:22 PM

Quote:

Since you are on the topic of math, what is the standard deviation of the 1.4 wins below average? While I can accept the 1.4 as an overall mathmatical factual expected outcome, I have to think there are variations to that result. For example, if the standard deviation were, say, 0.5 wins, then being 3 games below average is about 3 standard deviations from the expected outcome. 3 standard deviations is rare, but not unheard of.

I don't know what the standard deviation is. That's a good question.

Let me rephrase: of course it's possible for a reliever to cost his team 3 games relative to average. In order to do so, though, a pitcher working 81 innings at an LI of 1.5 would need to have an ERA 2.2 runs worse than league average. In other words, throw an average AA pitcher into a big league setup role, and voila!
But in the real world, you're never going to find a situation in which -3 WAA is a reasonable outcome to expect from a 7th-inning guy. Teams just aren't that stupid. And established major league pitchers just aren't that bad.

Quote:

Of course it can't be blamed solely on Hurdle, and I haven't done so. Read what I wrote earlier, and you'll see I mentioned luck as a factor.

If our average annual Pythag differential is -4.3 games, as you posted earlier, and you're predicting a -5, then either you're predicting an unusually bad year from Hurdle or you're blaming him for the overwhelming majority of the Pythag variance.

Quote:

Assuming we play better at Coors (and we have a huge variance in winning % historically between home and road, including under Hurdle), we can be expected to win more than our fair share of blowouts at Coors. This may result in a natural inflation factor in our Pythag. wins.

I don't think that logically follows. Which isn't to say that I think it's illogical; it's just not an unavoidable logical conclusion. I'd want to really study this idea before ascribing any significance to it.

Edit: Sorry, Roxpert! I accidentally clicked the button to edit your post rather than reply to it. I'm trying to address everything you said, though...

Roxpert · 03-01-2007, 10:17 PM

Quote:

Originally Posted by Heltonfan

I don't know what the standard deviation is. That's a good question.

Well, I think that may be a key issue. If this lousy 7th inning pitcher can be expected to be 1.4 wins worse than average, and the standard deviation is 1.0, being 3.0 wins worse in actuality is only 1.6 standard deviations worse than the average expected. That's not so terribly unusual.

Quote:

But in the real world, you're never going to find a situation in which -3 WAA is a reasonable outcome to expect from a 7th-inning guy. Teams just aren't that stupid.

You may be right, but the math you presented doesn't prove that. Again, standard deviation may indicate the rarity of an actual 7th inning guy costing his team 3 more wins than an average guy. BTW, any team that has a manager who sticks with Shawn Chacon for almost an entire season as closer may indeed be that stupid.

Quote:

If our average annual Pythag differential is -4.3 games, as you posted earlier, and you're predicting a -5, then either you're predicting an unusually bad year from Hurdle or you're blaming him for the overwhelming majority of the Pythag variance.

It's not an "unusually bad year" in light of the fact that it has happened twice in just the last four seasons alone. As to how much of that is ascribed to Hurdle versus our roster makeup, alignment of the stars, or the new steroids rules (jk) is impossible to determine.

Quote:

Edit: Sorry, Roxpert! I accidentally clicked the button to edit your post rather than reply to it. I'm trying to address everything you said, though...

This site has had some technical problems in the past hour that made getting around nearly impossible. Seems fixed now.

hiaspire · 03-01-2007, 11:27 PM

Quote:

Originally Posted by Heltonfan

a team's record in one-run games can be estimated by the Pythag formula, using .865 as the exponent instead of 2.

So .865 gives the right answer but 1.24 doesn't? And my actual game stats from reality are probably coincidental in comparison.

Actual one-run games are more interesting to me. For a manager who gets constant heat, when I add things up Hurdle has a BETTER record in 1-run games than his overall winning percentage.

He's 95-110 in one-run games as I added them up at BR for a .463 winning percentage, compared to the .447 overall.

And that's WITH some of the famed reliever melt-downs that cost so many close games late quite extraordinarily, but also balanced with other strong bullpen finds like Fuentes.

Heltonfan · 03-02-2007, 09:18 AM

Quote:

Originally Posted by Roxpert

Well, I think that may be a key issue. If this lousy 7th inning pitcher can be expected to be 1.4 wins worse than average, and the standard deviation is 1.0, being 3.0 wins worse in actuality is only 1.6 standard deviations worse than the average expected. That's not so terribly unusual.

Here are the worst five relief seasons in the past four years by raw (non-leverage-adjusted) WAA:
Alan Embree, 2005: -1.95
Jaret Wright, 2003: -1.87
Travis Harper, 2005: -1.78
Jay Powell, 2003: -1.72
Leo Nunez, 2005: -1.58

Quick check of the LIs... none of those guys had an LI above 1.10. So no one in that group is even close to the -3 WAA mark. Factoring in leverage, the worst relief season in that timeframe would be.... you guessed it, Chacon. -2.70 WAA. So even that horror show falls short of the mark. A big factor here: my -1.4 WAA estimate for Herges, in addition to being predicated on pessimistic assumptions about his rate stats and his leverage, was also predicated on a horribly pessimistic assumption about his playing time (81 innings). Most of these guys didn't come anywhere near that. Chacon, for instance, closed for the whole season, but only had 63 IP.

Roxpert · 03-02-2007, 10:11 AM

Quote:

Originally Posted by Heltonfan

Factoring in leverage, the worst relief season in that timeframe would be.... you guessed it, Chacon. -2.50 WAA.

Well, that's very interesting, and it makes me think that your WAA stat may be under-reporting what actually took place. I could swear on my mother's grave that Chacon cost us WAAY more than 2 or 3 wins versus the average closer that year. Maybe it's a figment of my imagination, though, and you may be right. Anyone else think that Chacon was more than 3 wins worse than the average closer that year? If not, then what was all the fuss about back then in Clint keeping him in the closer's role almost all season?!?

Heltonfan · 03-02-2007, 10:13 AM

Quote:

I could swear on my mother's grave that Chacon cost us WAAY more than 2 or 3 wins versus the average closer that year.

Average closer != average reliever.

And just looking at this simplistically: Chacon converted 35 of 44 save opportunities. Among 2004 NL pitchers with 20 or more saves (i.e. guys who were in the closer role most of the season), the aggregate save percentage was 86%. So an average closer would have converted 38 of 44; Chacon is only behind by three. Now, granted, he stunk in non-save situations as well... but then, an extra blown save should by no means count as a full win below average.

It's interesting how our instincts always seem to tell us that things are more significant than they really are...

BigRapidsJackass · 03-02-2007, 11:38 AM

Once again, The Book shows us the way:

SI.com - MLB - The Book: Playing the Percentages in Baseball - Monday April 17, 2006 10:32AM

hiaspire · 03-02-2007, 11:52 AM

The Book shows the best way if you want to make it seem like there is little difference between reliever value by relying upon a 3-run cushion to base such opinion. Of course there is less difference with such a cushion and margin for error. That's not where a reliever's impact is most determined.

"It's interesting how stats seem to tell us that things are more significant than they really are..."

BigRapidsJackass · 03-02-2007, 12:20 PM

Aspire, it IS entirely irrelevant to a reliever's value.

The points The Book excerpt is trying to make:

1. The save is a very, very flawed statistic. (I think even you would agree with that.)

2. We tend to overstate the contribution, positive or negative, of a closer.

3. The worst part of the "save" as a statistic: it influences how managers use their bullpens. A designated closer will be used in a very low-leverage "save opportunity" with a 3 run lead in the 9th inning. Sometimes this will be the second day in a row the closer is used, and very often that will make him unavailable when a high-leverage situation rears its head tomorrow. And yes, as Aspire says, "most managers do it." Maybe they do it to keep their closers happy. Maybe there's some intangible team spirit value to that. But I doubt it.

Hey, if you'd asked me in September '04 how many wins Chacon had cost the Rockies, I would've said (off the top of my head), "At least 6 to 8." But the truth is -- even by the traditional measurement, "blown saves -- he only "cost" the Rockies 9 all year. And since we can assume that even the best relievers (not including the historically great seasons like Gagne's best) would "blow" 3 to 5, the difference between the best and the all-time worst just isn't as great as I imagined.

So nobody is saying that a good closer (or good setup men) is unimportant. We're just trying to get a handle on how important.

hiaspire · 03-02-2007, 12:42 PM

I can agree with some of that, but it certainly IS about a reliever's value when conclusions are made that they are over-valued or their contribution is overstated. That's directly related to their value for a team.

Someone said this as part of the arguement that Chacon was not as bad as it looked: "Chacon converted 35 of 44 save opportunities. Among 2004 NL pitchers with 20 or more saves (i.e. guys who were in the closer role most of the season), the aggregate save percentage was 86%. So an average closer would have converted 38 of 44; Chacon is only behind by three. "

At the time I wasn't saying, "Look at Chacon's saves, he's doing better than everybody seems to think." I know what I saw, and certainly the save statistic wasn't going to change my mind about what was obvious to nearly everyone otherwise.

Quote:

We tend to overstate the contribution, positive or negative, of a closer.

It doesn't show that at all IMO, other than illustrating the situation with recording 3-run saves and inferring that influences opinion. No matter that conclusion with odd circumstance big cushion supporting evidence, I'll definitely take one of the "trusted" proven strong closers when I'm up a run in the 9th with runners on base. That's what they need to look at instead when the games really matter and a stud reliever is nothing close to over-valued when these games are on the line. That makes all the difference in the world to your advantage in those critical moments where games could go either way easily.

That's VERY important unless you want to loose a lot of those heart-breakers late because you don't see as much difference between reliever options because you've read some stat that says relievers are over-rated.

Relievers have been absolutely critical and correlated very strongly to Rockies success over the years -- perhaps the GREATEST factor in determining team success. I get that you aren't saying they are unimportant, but I disagree with the conclusions that they aren't as important as most believe with their own eyes. We've seen otherwise time and time again. And arguements with 3-run cushions will not do much convincing otherwise IMO.

Roxpert · 03-10-2007, 07:01 PM

My Diamond Mind Projection disk arrived yesterday, and I have delved into it during the last 24 hours, simming 80 seasons. Unfortunately, I've done this so quickly that I haven't stored any stats other than the Rockies' win total and place in the NL West standings each season.

For half the simmed seasons, I used Tom Tippett's roster and manager settings for the Rockies, which are pretty good but not as accurate a reflection of how I think Clint Hurdle and Dan O'Dowd will manage the roster and player usage. So, for the other 40 seasons, I customized the Rockies' roster and manager profile. Of course, I kept all other rosters alone, defaulting to Tippett's projections.

Finally, for half of the seasons in each of the above two groups, I turned on "random injuries", and for the other half, I used "no injuries", which assumes everyone is healthy. The former may be considered a test of team "depth", while the latter may be viewed as a test of a team's frontline talent.

OK.....so with all that out of the way, are you ready to find out how the Rockies fared? Here are the results:

Overall mean wins over 80 seasons - 76.7 wins
Overall median wins - 76 wins
Overall standard deviation - 6.46 wins

In a normal distribution curve. 68% of a population lies within 1.0 standard deviations of the mean, 95.7% lies within 2 standard deviations, and 99.7% lies within 3 standard deviations, as you can read here:

Standard deviation - Wikipedia, the free encyclopedia

Soooo, by that rule of thumb, the DMB sim suggests that there is a 68% chance that the Rox will win from 70 to 83 games, and over a 95% chance the win total will fall between 64 and 90. Yes, you can drive a truck through the Rockies' possibilities this upcoming season, mainly due to what I found was a rather large standard deviation.

To illustrate further, the Rockies finished over .500 (82+ wins) 24% of the time, while also winning 70 or fewer games 19% of the time. The range of win outcomes was from 63 to 97.

In terms of the subsets, the Rox did best in the 20-game set using Tom Tippett's original settings, with no injuries. Assuming the Rox are healthy and use only the 5 starters projected by Tippett (along with his other roster and usage assumptions), the team won an average of 79 games and averaged a 3rd place finish.

The Rox did the worst with my customized settings and no injuries. My settings are meant to reflect not what I'd do with the roster, but what I think DOD and Clint will do with it. The Rox won an average of 74 games, finishing nearly in the baseement (median of 4.75 place). It appears that Tippett gets 5 more wins from this team than our "braintrust", but that's probably a function of sample size.

Finally, how often did the Rockies make the playoffs? Overall, the Rox qualified for the playoffs in 10.6% of the seasons (one year finishing tied for first whereby loser of playoff game is not the wild card). The team won the NL West championship outright 5 times, and tied another time. We qualified as the wild card in 3 seasons, so we made the playoffs (or tied for a spot) 9 times in the 80 simmed seasons.

My conclusion? We have an outside shot at contending this year, but overall it appears that the Rockies should be expected to win about the same number of games as last year. I'll officially up my earlier prediction in this thread from 73 wins to 76 wins, but it should be obvious now that almost anything can happen. Could make for an interesting (or frustrating) season.

Hope this was interesting to read.

Heltonfan · 03-10-2007, 07:37 PM

Thanks, Roxpert. Good stuff.

Quote:

Yes, you can drive a truck through the Rockies' possibilities this upcoming season, mainly due to what I found was a rather large standard deviation.

Just a dry technical note here: the expected stdev of wins, for a 76.7-win team, is 6.35. And since Diamond Mind's sim engine simply uses each player's mean projection (or at least I assume it does), rather than doing a PECOTA-like measure of reliability for each player (where some players have a wider range of outcomes than others), we should expect each team to have virtually the same stdev. And as expected, your sample stdev for the Rockies is awfully close to that 6.35 figure.

So the Rockies' stdev of wins is only "rather large" in the sense that the stdev of wins for any team is rather large. And that's a legitimate point; even a really bad team like the Nationals probably has a 3-5% chance to make the playoffs. But what you have isn't evidence that the Rockies are a high-variance team, it's merely confirmation of a statistical fact. You may already know this, of course, but I want to make it clear so that no one misinterprets your results.

Interesting that after all this, you end up at 76 wins for us, right in line with my projections. PECOTA has the Rockies at 80 wins, which is right about what we would expect, since PECOTA is using those absurdly generous MLEs and we have some key players whose projections benefit greatly from them (Iannetta: .291/.379/.481... I'd love to see it, but it ain't happening). So it looks like we've got a pretty strong consensus.

EDIT: Roxpert's year-by-year sim results can be viewed here, for anyone interested.

TheIncredibleRox · 03-10-2007, 08:17 PM

I could post projections from my spreadsheets. But they'd be incredibly similar to HF's (mainly because some of them indeed are his). Also, while it's more useful and accurate, there would be something bland about projections that just say "Holliday: 44 RAR" or whatever. And last of all, it's fun to allow some subjectivity in the picture... and I think this thread should be fun.

1B:
Helton: .311/.433/.526, 26 HR in 620 PA

I think thats damn reasonable, and we need it.
2B:
Matsui: .288/.324/.406, 8 HR 12 SB (7 CS) in 340 PA
Carroll: .277/.345/.399, 1 HR in 310 PA

SS:
Barmes: .277/.315/.407, 9 HR in 305 PA
Tulowitzki: .269/.321/.425, 11 HR in 330 PA

3B:
Atkins: .311/.411/.525, 21 HR in 630 PA. Starts slow then mashes down stretch

C:
Torrealba: .251/.309/.402 in 180 PA, traded at deadline
Lopez: .248/.316/.412 in 289 PA
Iannetta: .286/.376/.449 in 210 PA

Iannetta gets screwed and starts year in AAA for a bull**** reason.

LF:
Holliday: .316/.366/.602, 33 HR in 625 PA

CF:
Tavares: .301/.352/.401, 41 SB (11 CS) in 580 PA

A very nice little suprise

RF:
Hawpe: .280/.350/.489, 30 HR in 510 PA

Other OF:
Sullivan: .252/.301/.388 in 190 PA
Baker: .261/.306/.408 in 180 PA
Spillborghs: .280/.330/.420 in 190 PA. I like him, dunno why.

Starters:
Francis: 14-11, 4.22 ERA, 221 IP-- a very good year
Cook: 15-11, 4.30 ERA, 216 IP
Hirsh: 11-12, 5.30 ERA, 189 IP
Kim: 10-11, 5.15 ERA, 118 IP (18 starts, traded at deadline for not enough)
Buccholz: 9-11, 5.65 ERA, 125 IP (half year in pen, half in rotation)
Lopez: 3-7, 5.96 ERA, 85 IP (by May we wonder what we ever saw in him)
Jimenez: 4-2, 5.31, 88 IP (enters rotation in August and holds his own)

Relievers:
Fuentes: 3.11 ERA, 67 IP (when he should have thrown 90), 32 saves
Hawkins: 5.11 ERA, 70 IP (Jose Mesa '07)
Ramirez: 5.01 ERA, 66 IP
Corpas: 4.43 ERA, 65 IP
Martin: 5.89 ERA, 21 IP, DFA'd after May
Morillo: 4.45 ERA, 45 IP starts as intriguing mop-up guy, high K and BB rates
Rivera: 3.88 ERA, 44 IP doesn't break camp, but comes up late May and suprises

Overall record: 75-87

Some random notes:

--Fogg and Affeldt traded late spring, possibly even packaged together, for any out-of-options and somewhat intriguing RP who wasn't going to make another team. I didn't include whoever that may be in these projections.

--We are hurt by the fact that we like Rodrigo Lopez way more than we should, and hate BK Kim more than we should.

--I gave sort of a mid-line projection for Hawpe. But I think theres a loooot of variance possible there. I could see as high as .320/.410/.600, or as low as .260/.320/.420. I don't know why I just get that feeling with him.

--The team is hurt by: A) having a top-heavy rotation. Cook and Francis have stellar years, nobody else really suprises. B) No consistent, effective bridge to Fuentes. C) Mediocre (at best) offense from SS, 2B, and C.

Roxpert · 03-10-2007, 08:59 PM

Quote:

Originally Posted by Heltonfan

So the Rockies' stdev of wins is only "rather large" in the sense that the stdev of wins for any team is rather large. And that's a legitimate point; even a really bad team like the Nationals probably has a 3-5% chance to make the playoffs. But what you have isn't evidence that the Rockies are a high-variance team, it's merely confirmation of a statistical fact. You may already know this, of course, but I want to make it clear so that no one misinterprets your results.

Very revealing point you just made, Heltonfan. An average team's standard deviation as a percentage of projected record is typically high, and in fact higher than I and most others would intuitively surmise. The odds of being surprised, or disappointed, as a baseball fan traces to such volatility in possible results.

Perhaps that's exactly what the Monforts are waiting for.......an outlier year (on the upside) to bring back those "golden goose" revenue streams. Once that happens, maybe they'd be more willing to invest in the product. After all, even with what little the owners have done this offseason, there's a one in four chance we have a winning record, and about a one in ten chance we make the playoffs!

Why spend when sheer luck (i.e. mere variance from expected results) can also take you to the "promised land"?!?

Roxpert · 03-10-2007, 09:08 PM

TIR, indeed a consensus is emerging from the statistical side of things as to what the Rockies can be expected to do this year. Now that we seem to be in agreement about this being a mid-70's win team on paper, watch for the actual result to completely confound us, and for the non-statistically oriented fans to use such results to diminish or downplay the importance or validity of our work.

In short, all we are doing is "handicapping" the odds of possible outcomes, and we have no real corner on the market as to the "truth" of what will actually happen. If we did, then why would we bother to even watch the season!?! Just thought I'd mention this in case the typically anti-stat fans are thinking of rebutting us on this thread about our claim of having "absolute truth". We don't......but at least I have a much better sense of what to expect from the Rockies now that I've burned about 18 hours of my time since yesterday, LOL.

03-02-2007, 11:52 AM	#38 (permalink)
hiaspire Member Join Date: Nov 2006 Posts: 479	The Book shows the best way if you want to make it seem like there is little difference between reliever value by relying upon a 3-run cushion to base such opinion. Of course there is less difference with such a cushion and margin for error. That's not where a reliever's impact is most determined. "It's interesting how stats* seem to tell us that things are more significant than they really are..."* Last edited by hiaspire; 03-02-2007 at 11:56 AM.

03-02-2007, 12:20 PM	#39 (permalink)
BigRapidsJackass Veteran Member Join Date: Nov 2006 Posts: 1,147	Aspire, it IS entirely irrelevant to a reliever's value. The points The Book excerpt is trying to make: 1. The save is a very, very flawed statistic. (I think even you would agree with that.) 2. We tend to overstate the contribution, positive or negative, of a closer. 3. The worst part of the "save" as a statistic: it influences how managers use their bullpens. A designated closer will be used in a very low-leverage "save opportunity" with a 3 run lead in the 9th inning. Sometimes this will be the second day in a row the closer is used, and very often that will make him unavailable when a high-leverage situation rears its head tomorrow. And yes, as Aspire says, "most managers do it." Maybe they do it to keep their closers happy. Maybe there's some intangible team spirit value to that. But I doubt it. Hey, if you'd asked me in September '04 how many wins Chacon had cost the Rockies, I would've said (off the top of my head), "At least 6 to 8." But the truth is -- even by the traditional measurement, "blown saves -- he only "cost" the Rockies 9 all year. And since we can assume that even the best relievers (not including the historically great seasons like Gagne's best) would "blow" 3 to 5, the difference between the best and the all-time worst just isn't as great as I imagined. So nobody is saying that a good closer (or good setup men) is unimportant. We're just trying to get a handle on how important. Last edited by BigRapidsJackass; 03-02-2007 at 12:24 PM.

03-10-2007, 07:01 PM	#41 (permalink)
Roxpert Veteran Member Join Date: Nov 2006 Location: Denver Posts: 1,059	My Diamond Mind Projection disk arrived yesterday, and I have delved into it during the last 24 hours, simming 80 seasons. Unfortunately, I've done this so quickly that I haven't stored any stats other than the Rockies' win total and place in the NL West standings each season. For half the simmed seasons, I used Tom Tippett's roster and manager settings for the Rockies, which are pretty good but not as accurate a reflection of how I think Clint Hurdle and Dan O'Dowd will manage the roster and player usage. So, for the other 40 seasons, I customized the Rockies' roster and manager profile. Of course, I kept all other rosters alone, defaulting to Tippett's projections. Finally, for half of the seasons in each of the above two groups, I turned on "random injuries", and for the other half, I used "no injuries", which assumes everyone is healthy. The former may be considered a test of team "depth", while the latter may be viewed as a test of a team's frontline talent. OK.....so with all that out of the way, are you ready to find out how the Rockies fared? Here are the results: Overall mean wins over 80 seasons - 76.7 wins Overall median wins - 76 wins Overall standard deviation - 6.46 wins In a normal distribution curve. 68% of a population lies within 1.0 standard deviations of the mean, 95.7% lies within 2 standard deviations, and 99.7% lies within 3 standard deviations, as you can read here: Standard deviation - Wikipedia, the free encyclopedia Soooo, by that rule of thumb, the DMB sim suggests that there is a 68% chance that the Rox will win from 70 to 83 games, and over a 95% chance the win total will fall between 64 and 90. Yes, you can drive a truck through the Rockies' possibilities this upcoming season, mainly due to what I found was a rather large standard deviation. To illustrate further, the Rockies finished over .500 (82+ wins) 24% of the time, while also winning 70 or fewer games 19% of the time. The range of win outcomes was from 63 to 97. In terms of the subsets, the Rox did best in the 20-game set using Tom Tippett's original settings, with no injuries. Assuming the Rox are healthy and use only the 5 starters projected by Tippett (along with his other roster and usage assumptions), the team won an average of 79 games and averaged a 3rd place finish. The Rox did the worst with my customized settings and no injuries. My settings are meant to reflect not what I'd do with the roster, but what I think DOD and Clint will do with it. The Rox won an average of 74 games, finishing nearly in the baseement (median of 4.75 place). It appears that Tippett gets 5 more wins from this team than our "braintrust", but that's probably a function of sample size. Finally, how often did the Rockies make the playoffs? Overall, the Rox qualified for the playoffs in 10.6% of the seasons (one year finishing tied for first whereby loser of playoff game is not the wild card). The team won the NL West championship outright 5 times, and tied another time. We qualified as the wild card in 3 seasons, so we made the playoffs (or tied for a spot) 9 times in the 80 simmed seasons. My conclusion? We have an outside shot at contending this year, but overall it appears that the Rockies should be expected to win about the same number of games as last year. I'll officially up my earlier prediction in this thread from 73 wins to 76 wins, but it should be obvious now that almost anything can happen. Could make for an interesting (or frustrating) season. Hope this was interesting to read. Last edited by Roxpert; 03-10-2007 at 08:42 PM.

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03-02-2007, 11:38 AM	#37 (permalink)
BigRapidsJackass Veteran Member Join Date: Nov 2006 Posts: 1,147	Once again, The Book shows us the way: SI.com - MLB - The Book: Playing the Percentages in Baseball - Monday April 17, 2006 10:32AM

03-10-2007, 08:17 PM	#43 (permalink)
TheIncredibleRox Member Join Date: Nov 2006 Posts: 285	I could post projections from my spreadsheets. But they'd be incredibly similar to HF's (mainly because some of them indeed are his). Also, while it's more useful and accurate, there would be something bland about projections that just say "Holliday: 44 RAR" or whatever. And last of all, it's fun to allow some subjectivity in the picture... and I think this thread should be fun. 1B: Helton: .311/.433/.526, 26 HR in 620 PA I think thats damn reasonable, and we need it. 2B: Matsui: .288/.324/.406, 8 HR 12 SB (7 CS) in 340 PA Carroll: .277/.345/.399, 1 HR in 310 PA SS: Barmes: .277/.315/.407, 9 HR in 305 PA Tulowitzki: .269/.321/.425, 11 HR in 330 PA 3B: Atkins: .311/.411/.525, 21 HR in 630 PA. Starts slow then mashes down stretch C: Torrealba: .251/.309/.402 in 180 PA, traded at deadline Lopez: .248/.316/.412 in 289 PA Iannetta: .286/.376/.449 in 210 PA Iannetta gets screwed and starts year in AAA for a bull**** reason. LF: Holliday: .316/.366/.602, 33 HR in 625 PA CF: Tavares: .301/.352/.401, 41 SB (11 CS) in 580 PA A very nice little suprise RF: Hawpe: .280/.350/.489, 30 HR in 510 PA Other OF: Sullivan: .252/.301/.388 in 190 PA Baker: .261/.306/.408 in 180 PA Spillborghs: .280/.330/.420 in 190 PA. I like him, dunno why. Starters: Francis: 14-11, 4.22 ERA, 221 IP-- a very good year Cook: 15-11, 4.30 ERA, 216 IP Hirsh: 11-12, 5.30 ERA, 189 IP Kim: 10-11, 5.15 ERA, 118 IP (18 starts, traded at deadline for not enough) Buccholz: 9-11, 5.65 ERA, 125 IP (half year in pen, half in rotation) Lopez: 3-7, 5.96 ERA, 85 IP (by May we wonder what we ever saw in him) Jimenez: 4-2, 5.31, 88 IP (enters rotation in August and holds his own) Relievers: Fuentes: 3.11 ERA, 67 IP (when he should have thrown 90), 32 saves Hawkins: 5.11 ERA, 70 IP (Jose Mesa '07) Ramirez: 5.01 ERA, 66 IP Corpas: 4.43 ERA, 65 IP Martin: 5.89 ERA, 21 IP, DFA'd after May Morillo: 4.45 ERA, 45 IP starts as intriguing mop-up guy, high K and BB rates Rivera: 3.88 ERA, 44 IP doesn't break camp, but comes up late May and suprises Overall record: 75-87 Some random notes: --Fogg and Affeldt traded late spring, possibly even packaged together, for any out-of-options and somewhat intriguing RP who wasn't going to make another team. I didn't include whoever that may be in these projections. --We are hurt by the fact that we like Rodrigo Lopez way more than we should, and hate BK Kim more than we should. --I gave sort of a mid-line projection for Hawpe. But I think theres a loooot of variance possible there. I could see as high as .320/.410/.600, or as low as .260/.320/.420. I don't know why I just get that feeling with him. --The team is hurt by: A) having a top-heavy rotation. Cook and Francis have stellar years, nobody else really suprises. B) No consistent, effective bridge to Fuentes. C) Mediocre (at best) offense from SS, 2B, and C.

03-10-2007, 09:08 PM	#45 (permalink)
Roxpert Veteran Member Join Date: Nov 2006 Location: Denver Posts: 1,059	TIR, indeed a consensus is emerging from the statistical side of things as to what the Rockies can be expected to do this year. Now that we seem to be in agreement about this being a mid-70's win team on paper, watch for the actual result to completely confound us, and for the non-statistically oriented fans to use such results to diminish or downplay the importance or validity of our work. In short, all we are doing is "handicapping" the odds of possible outcomes, and we have no real corner on the market as to the "truth" of what will actually happen. If we did, then why would we bother to even watch the season!?! Just thought I'd mention this in case the typically anti-stat fans are thinking of rebutting us on this thread about our claim of having "absolute truth". We don't......but at least I have a much better sense of what to expect from the Rockies now that I've burned about 18 hours of my time since yesterday, LOL.