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You do not understand what the pythag formula is measuring or you would not have been talking about things which took place outside of the 16 game streak.
The very scoring of runs is heavily luck-laden, but the pythag refuses to even acknowledge that. It assumes that the number of runs and opponents runs is perfectly merit-driven, and therefore, the pythag, casts a faulty context for the exposure to luck.
The luck involved in the scoring of runs is disregarded in a formula that purports to quantify luck.
Conversely, one could look at the WL record of a team and compute with a formula that they should have scored x runs and allowed y. What is gained by that? You simply have a proving b and b proving a, which is not proof of anything.
The fact that you advocate a certain hypothesis does not, by itself, constitute proof that persons who do not endorse it do not understand it. That is a very risky logical position.
Whitesox play to their competition thats for sure. Can't beat crappy teams and play well against solid teams. I'm not really sure what that says about them
It is simply a mathematical model that shows a high correlation to the observed data.
And that is all it does: show correlation. But the thing it shows correlation to cannot be selected for, so it is valueless to know about the correlation. Team with the best ratio of runs scored/opponents runs also has the best ratio of wins/losses. What surprises has that uncovered?
I shouldn't have allowed myself to be distracted by the silly discussion of whether the pythag has any analytical utility.
My quarrel was with the use of the term "genuine badness" to characterize a team that had just gone 39-32 in the period immediately preceding, all the while being the same players playing together as the same team against the same opponents under the same conditions, but suddenly genuine badness afflicts them. I will be extremely surprised if, in the remainder of the season, this team of "genuine badness" does not put together a stretch of 16 games in which they win more than they lose. Nor will I be surprised if they outscore their opponents in those 16 games, nor herald an amazing formula that predicts that they will.
It also does not require any mathematical formulas to reveal that, during a 16-game losing streak, they were outscored by their opponents. By at least a 16-run delta.
Whitesox play to their competition thats for sure. Can't beat crappy teams and play well against solid teams. I'm not really sure what that says about them
The very scoring of runs is heavily luck-laden, but the pythag refuses to even acknowledge that. .
Well, looks like I was right, the problem is that you do not understand what the formula is measuring.
It is nothing but a math formula, it has no agenda of any kind, it is incapable of acknowledging or failing to acknowledge things.
Bill James is not, and never has been, any sort of math theoretician, he is instead a math tinkerer. He comes up with an orginal question and it isn't a matter of "Okay, I'll plug the data into the formula and see if it is validated." What he does is sit down and try out numerous potential formulas until by trial and error, he finds one which works. The Pythag formula he employs, he employs because it works. Better than anything else he tried, it successfully predicted the won lost records of teams based on their runs scored and runs allowed.
The idea behind the formula was examining data to determine how much of a team's won loss record is due to luck. If team A has scored 400 runs and given up 350 runs, and Team B has an identical runs scored and surrendered record, but Team A has won five more games than Team B, then we must suspect that team A has been more fortunate in the manner in which those runs were distributed. The Pythag formula brings precision to that question.
The utility of having such measuring tool is that we may look at the standings, compare won loss records to expected won loss records, and get a sense for which teams are getting by with luck, which teams are better than their actual records but have had foul luck. Since luck tends to even out the larger the sampling data is, we may predict that the team that has been overachieving, is likely to regress to their actual level of ability. The underachieving teams have a higher probability of improving.
Now...I applied the formula to just the 16 game losing streak, my question being, have the Mariners been bad during this stretch, or have they just been plagued by uncommon misfortune? And that is it, that was my only point..the data suggests that they have earned their losing streak.
So...when you start talking about games outside the streak, right away I knew that you didn't understand what was being discussed. Games outside the streak would be irelevancies. That you wrote something about "advocating the hypothesis," shows that you don't understand what the formula measures or how it came into being. There is no advocacy, any more than my saying "I counted ten bluebirds on that telephone wire this morning" is advocacy of counting, bluebirds or telephone wires.
Now do you understand?
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