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Old-Timey Member
Posted
Why does everything think Nick Markakis is still good? I don't get it.

 

Because you didn't play the game, man.

 

Posted

 

Its not hard to think that Saunders is more valuable than Upton at this point taking salary and control into consideration.

Posted
I have a feeling that AA will trade Dickey for a #2 (I pray for Cueto) AND still sign a #1 (Shields). Move Stro and Hutch into #4/5 slots with depth in case those guys falter.
Posted
I have a feeling that AA will trade Dickey for a #2 (I pray for Cueto) AND still sign a #1 (Shields). Move Stro and Hutch into #4/5 slots with depth in case those guys falter.

 

No one is dumb enough to make that trade,

Old-Timey Member
Posted
I have a feeling that AA will trade Dickey for a #2 (I pray for Cueto) AND still sign a #1 (Shields). Move Stro and Hutch into #4/5 slots with depth in case those guys falter.

 

What exactly does Dickey for Cueto accomplish for Cincinnati?

Posted

Ken Rosenthal ‏@Ken_Rosenthal now24 seconds ago

Melky wants 5 years, according to exec from club with interest. Sound crazy? Cruz, 34, and Markakis, 31, each got 4 years. Melky is 30.

Posted

In regards to the Jays strength in right-handed power: Over the past two seasons, if you look at .ISO for qualified RHH with at least 6 WAR, Jays have three of the top nine in their lineup:

 

01 | .270 | Edwin

02 | .254 | Trout

03 | .251 | Stanton

04 | .248 | Miggy

05 | .246 | Goldschmidt

06 | .239 | Bautista

07 | .211 | Upton

08 | .209 | McCutchen

09 | .200 | Donaldson

10 | .199 | Byrd

Posted

So, I've been analyzing team performance between successive seasons (eg. dWin% = Win% of season 2 - Win% of season 1) and been checking on how much of an impact general managers have on this. When doing a linear regression analysis between win% of the 2nd season and win% of the first season, the effect was, of course, significant (p<0.05). However, after accounting for GM of the team, while still significant, the predictive value of the model actually improved. So, I thought that maybe I should check the WAR differential (dWAR; yes, just as creative as dCorsi) between seasons among each of the GMs since 1980 and add up the results to see how GMs have done. I adjusted for marginalization of win%, since it's harder to improve from 85 wins to 90 wins than it is to improve from 75 wins to 80 wins.

 

Here are the top 10 GMs since 1980 according to this measure:

 

1. John Schuerholz*(111.3 total dWAR)

2. Brian Cashman (89.3 dWAR)

3. Pat Gillick (83.9 dWAR)

4. Theo Epstein (51.7 dWAR)

5. Billy Beane (49.4 dWAR)

6. Frank Cashen (42.2 dWAR)

7. Walt Jocketty (41.5 dWAR)

8. Dan Duquette (40.4 dWAR)

9. Ned Colletti (38.2 dWAR) (Yeah, this surprised me, too)

10. Bill Stoneman (36.2 dWAR)

 

Plus:

 

18. Andrew Friedman (18.0 dWAR)

 

Worst 10:

 

1. Chuck LaMar (-39.5 dWAR)

2. Andy MacPhail (-39.0 dWAR)

3. Cam Bonifay (-38.6 dWAR)

4. Woody Woodward (-37.8 dWAR)

5. Bill Bavasi (-37.7 dWAR)

6. Harding Peterson (-32.5 dWAR) (Doesn't include his early years, so it may not be representative of his full career)

7. Joseph Klein (-32.2 dWAR)

8. Allan Baird (-31.4 dWAR)

9. Syd Thrift (-31.0 dWAR)

10. Randy Smith (-30.6 dWAR)

 

Just because I felt like adding them:

 

11. Mark Shapiro (-30.3 dWAR)

12. Jim Bowden (-26.5 dWAR)

 

Main caveats with this analysis:

 

1) Doesn't account for ownership/salary, which can influence a GM's decision (Hi Florida/Miami Marlins!).

2) Doesn't account for draft picks made by GMs. This can, especially, influence the dWAR of GMs with shorter than average career lengths.

3) Survivorship bias weeds out the bad GMs, which can cause issues with studies like this one.

 

I'm hoping to work on this some more, since I find it pretty interesting.

Posted
So, I've been analyzing team performance between successive seasons (eg. dWin% = Win% of season 2 - Win% of season 1) and been checking on how much of an impact general managers have on this. When doing a linear regression analysis between win% of the 2nd season and win% of the first season, the effect was, of course, significant (p<0.05). However, after accounting for GM of the team, while still significant, the predictive value of the model actually improved. So, I thought that maybe I should check the WAR differential (dWAR; yes, just as creative as dCorsi) between seasons among each of the GMs since 1980 and add up the results to see how GMs have done. I adjusted for marginalization of win%, since it's harder to improve from 85 wins to 90 wins than it is to improve from 75 wins to 80 wins.

 

Here are the top 10 GMs since 1980 according to this measure:

 

1. John Schuerholz*(111.3 total dWAR)

2. Brian Cashman (89.3 dWAR)

3. Pat Gillick (83.9 dWAR)

4. Theo Epstein (51.7 dWAR)

5. Billy Beane (49.4 dWAR)

6. Frank Cashen (42.2 dWAR)

7. Walt Jocketty (41.5 dWAR)

8. Dan Duquette (40.4 dWAR)

9. Ned Colletti (38.2 dWAR) (Yeah, this surprised me, too)

10. Bill Stoneman (36.2 dWAR)

 

Plus:

 

18. Andrew Friedman (18.0 dWAR)

 

Worst 10:

 

1. Chuck LaMar (-39.5 dWAR)

2. Andy MacPhail (-39.0 dWAR)

3. Cam Bonifay (-38.6 dWAR)

4. Woody Woodward (-37.8 dWAR)

5. Bill Bavasi (-37.7 dWAR)

6. Harding Peterson (-32.5 dWAR) (Doesn't include his early years, so it may not be representative of his full career)

7. Joseph Klein (-32.2 dWAR)

8. Allan Baird (-31.4 dWAR)

9. Syd Thrift (-31.0 dWAR)

10. Randy Smith (-30.6 dWAR)

 

Just because I felt like adding them:

 

11. Mark Shapira (-30.3 dWAR)

12. Jim Bowden (-26.5 dWAR)

 

Main caveats with this analysis:

 

1) Doesn't account for ownership/salary, which can influence a GM's decision (Hi Florida/Miami Marlins!).

2) Doesn't account for draft picks made by GMs. This can, especially, influence the dWAR of GMs with shorter than average career lengths.

3) Survivorship bias weeds out the bad GMs, which can cause issues with studies like this one.

 

I'm hoping to work on this some more, since I find it pretty interesting.

 

Good work. I think you have something worth publishing here even if you publish in its current form as a conversation starter

Community Moderator
Posted

You would need to account for salaries and roster age.

 

Personally, I think the whole method is flawed and incredibly biased based on the state of the team before/during the GM's first season (or when they left the team). Example - your #1 dude took over as GM for the 1982 season. The 1981 was strike shortened... obviously he would get mad "dWAR" just for this coincidence. Same for #7 Jocketty taking over a team for the 1995 season.

 

In its current state, this is no measure at all of GM competence or skill.

 

A GM could take over a team while it's solid and get fired 15 years later during a rebuilding cycle, and he'll come out looking like a turkey even if he kept them competitive for a decade.

Posted
You would need to account for salaries and roster age.

 

Personally, I think the whole method is flawed and incredibly biased based on the state of the team before/during the GM's first season (or when they left the team). Example - your #1 dude took over as GM for the 1982 season. The 1981 was strike shortened... obviously he would get mad "dWAR" just for this coincidence. Same for #7 Jocketty taking over a team for the 1995 season.

 

In its current state, this is no measure at all of GM competence or skill.

 

A GM could take over a team while it's solid and get fired 15 years later during a rebuilding cycle, and he'll come out looking like a turkey even if he kept them competitive for a decade.

 

I adjusted for the 1981/1994 seasons by giving them less weight relative to the other seasons.

 

As for your other critiques, I understand what you mean about the difficulties of measuring GM competence (or skill). A lot of factors outside their control can influence their decision-making, such as ownership, team state, etc. I think it's possible to factor in these things, but very difficult to do.

 

As a matter of fact, I came across this by accident. My intention was for something else entirely, but did this analysis just for the heck of it and was interested in what I found. Possibly the best way to determine whether this is a measure of GM competence is by determining how reliable this measure is. Still a lot of work needs to be done on this metric.

 

Thanks for the critique, btw!

Posted

So uhh... it turns out that Jonah Keri is actually way dumber than I thought he was.

 

He just released the first part for his trade value rankings for this year:

 

http://grantland.com/features/2014-mlb-trade-value-rankings-part-1/

 

After a brief glance, they think Hamels has more trade value than Edwin and Jose, Machado, Beltre, Russell, and a host of others (and yes they claim to take contracts into account).

 

They didn't even have Bautista ranked in the top 50 last year.

 

Really bad job by a site that I very much expect better from.

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