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#1
Posted 19 March 2018  01:08 PM
Assuming
i) the Pythagorean theory of winning percentage, and
ii) the Twins score the same number of runs in '18 as they did in '17 (788),
then a .05 (not .5) decline in ERA results in additional win.
Last year, the Twins' ERA was 4.59. So, if you want to forecast this years team ERA with all the additions, then one can forecast win totals.
Examples if all the additions result in a decline from 4.59 to 4.54, the model predicts one more win.
If predicted ERA drops to 4.39, four more wins.
ERA of 4.19, eight more wins or roughly 92 wins.
By the way, the above are approximations. If your a math nerd, I'd be happy to provide math details.
 nicksaviking, Craig Arko, Oldgoat_MN and 1 other like this
#2
Posted 19 March 2018  01:17 PM
Note that the Twins overperformed Pythag by 2 wins next year, so you wouldn't necessarily add these wins to 85, you should add them to 83.
 Thrylos and Dantes929 like this
#3
Posted 19 March 2018  01:43 PM
You also have one more unstated assumption here  that our number of unearned runs stays the same too.
I notice Toronto is projected very close to the numbers you reference  5.01 runs per game, and a 4.24 ERA  but they are only projected for 86 wins. The unearned run difference works out to 34 wins from your Twins model.
 caninatl04 likes this
#4
Posted 19 March 2018  01:44 PM
You also are implicitly assuming that defense is constant year over year (i.e., the same number of unearned runs as last year.)
Cool.Thanks for sharing.
 caninatl04 likes this
#5
Posted 19 March 2018  01:46 PM
You also are implicitly assuming that defense is constant year over year (i.e., the same number of unearned runs as last year.)
Great minds think alike!
 jkcarew likes this
#6
Posted 19 March 2018  02:01 PM
Great minds think alike!
Yeah...but I notice that some think faster.Oh, Well!
 ashburyjohn likes this
#7
Posted 20 March 2018  06:19 AM
Also, I doubt that increases/decreases in ERA are linear with wins. At some point, you're going to see diminishing returns.
#8
Posted 20 March 2018  06:41 AM
To be fair, this is a pretty decent start. The other side is the runs scored side of it too, increasing them should also add wins. I think the offense should be better as well, namely b/c I don't think Buxton will be an abomination at the plate to start the year, and many of the kids should take steps forward (even if they all make incremental improvements, that's going to add wins). You may see a guy like Dozier taking a step back (hope not), but there's not a lot of regression candidates in the offense. The team is young, there's really not much in terms of regression candidates at all. Santana is probably the biggest. I'm hoping the extra month off actually does him a bit of good in this front.
#9
Posted 20 March 2018  06:57 AM
To be fair, this is a pretty decent start. The other side is the runs scored side of it too, increasing them should also add wins. I think the offense should be better as well, namely b/c I don't think Buxton will be an abomination at the plate to start the year, and many of the kids should take steps forward (even if they all make incremental improvements, that's going to add wins). You may see a guy like Dozier taking a step back (hope not), but there's not a lot of regression candidates in the offense. The team is young, there's really not much in terms of regression candidates at all. Santana is probably the biggest. I'm hoping the extra month off actually does him a bit of good in this front.
I think the offense holds steady somewhere between the first and second half of last season. They'll be very good but not elite, I think. Losing Polanco hurts for sure.
There are some regression candidates but none appear particularly noteworthy IMO. Dozier might fade a bit but he has pretty firmly established a baseline. I think Mauer is for real and will continue being a productive player. Escobar might get exposed as a fulltime player but hopefully, he won't be out there every day for long. Rosario *might* regress but I don't think he will, at least not much.
On the other hand, Buxton has room to grow. As does Sano. Kepler has tons of headroom.
In the end, I think it all balances out.
 Platoon likes this
#10
Posted 21 March 2018  01:17 PM
Note that the Twins overperformed Pythag by 2 wins next year, so you wouldn't necessarily add these wins to 85, you should add them to 83.
Actually, that’s exactly what I did
#11
Posted 21 March 2018  01:19 PM
Also, I doubt that increases/decreases in ERA are linear with wins. At some point, you're going to see diminishing returns.
IF you believe the pythag model, it actually works the other way since there are a bunch of “squared” terms.
 ToddlerHarmon likes this
#12
Posted 21 March 2018  01:38 PM
Actually, that’s exactly what I did
Yup. Sorry, that was more directed to readers who might try this experiment at home.
#13
Posted 21 March 2018  02:37 PM
IF you believe the pythag model, it actually works the other way since there are a bunch of “squared” terms.
Right, I said that backwards.
#14
Posted 21 March 2018  03:26 PM
Also, I doubt that increases/decreases in ERA are linear with wins. At some point, you're going to see diminishing returns.
What if the ERA is 0.00?
#15
Posted 21 March 2018  03:58 PM
Right, I said that backwards.
 Brock Beauchamp, Sconnie and Platoon like this
A slim chance equals a fat chance, yet a wise man and a wise guy are opposites.
#16
Posted 21 March 2018  06:58 PM
This is exactly right, and I don't think Pythag could possibly compensate for that completely.Also, I doubt that increases/decreases in ERA are linear with wins. At some point, you're going to see diminishing returns.
The number of wins each unit of ERA is worth would look like a bell curve (more likely a triangle with a sharp peak). If you're up at a 5.5 ERA, and you drop to a 5.0, or conversely are at a 2.5 ERA and drop to 2.0, you aren't going get a large number of wins added in return. You're likely going to find the large fluctuations in wins (without doing any math) between 3.5 and 4.5.
A drop from 4.5 to 4.0 would likely be worth a significant amount more than those mentioned in the previous paragraph. I think that is clear, and don't think anybody would doubt that. Pythag has some correction in sure, but it wouldn't eliminate this.
This isn't even considering the unlimited variables that can be introduced (weather, injuries to position players, inevitable statistical fluctuation of position players offensive and defensively, the strength of schedule, how well the pitching staff is managed, the stadium you're playing in, the proportions of LH/RH pitcher and hitter combos). It's endless, and basically futile to attempt a calculation of such magnitude short of having access to a supercomputer.....Unless your comfortable with a margin for error that could possibly put you in the neighborhood of unrealistic ERAs.
You could just stop at the assumption that all thing are constant except for ERA. The statistical chance of that happening is microscopic, destroying the integrity of any output. Could possibly be a useful guide...but you'd need a lot of testing to show its reliable.
Edited by Darius, 21 March 2018  07:08 PM.
#17
Posted 21 March 2018  09:39 PM
uhh, Baseball Prospectus, Fangraphs, they have great big models to run those kinds of things. They are great, but take way more resources than I have.This is exactly right, and I don't think Pythag could possibly compensate for that completely.
The number of wins each unit of ERA is worth would look like a bell curve (more likely a triangle with a sharp peak). If you're up at a 5.5 ERA, and you drop to a 5.0, or conversely are at a 2.5 ERA and drop to 2.0, you aren't going get a large number of wins added in return. You're likely going to find the large fluctuations in wins (without doing any math) between 3.5 and 4.5.
A drop from 4.5 to 4.0 would likely be worth a significant amount more than those mentioned in the previous paragraph. I think that is clear, and don't think anybody would doubt that. Pythag has some correction in sure, but it wouldn't eliminate this.
This isn't even considering the unlimited variables that can be introduced (weather, injuries to position players, inevitable statistical fluctuation of position players offensive and defensively, the strength of schedule, how well the pitching staff is managed, the stadium you're playing in, the proportions of LH/RH pitcher and hitter combos). It's endless, and basically futile to attempt a calculation of such magnitude short of having access to a supercomputer.....Unless your comfortable with a margin for error that could possibly put you in the neighborhood of unrealistic ERAs.
You could just stop at the assumption that all thing are constant except for ERA. The statistical chance of that happening is microscopic, destroying the integrity of any output. Could possibly be a useful guide...but you'd need a lot of testing to show its reliable.
The swag is a lot of fun for me
#18
Posted 22 March 2018  05:59 AM
If I wanted balls and strikes called by a robot, I would get an Xbox!
#19
Posted 22 March 2018  10:52 AM
What if the ERA is 0.00?
Roughly speaking, runs for squared divided by (runs for squared plus zero squared) = 100%.
#20
Posted 22 March 2018  10:59 AM
I guess is was hoping readers would guess what all the FA additions would do to team ERA. And then use the approximation to again guess the value of these additions to wins.
My guess is a reduction by .25, so maybe 5 wins?
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