Posted by barracuda3 on 1/19/2023 9:41:00 AM (view original):
Posted by schwarze on 1/19/2023 8:37:00 AM (view original):
Posted by barracuda3 on 1/19/2023 7:09:00 AM (view original):
Pick #15: League 2: 1901-1902 Philadelphia Athletics/Baltimore Orioles (A.L. West)
.334/.401/.499 (1), 2.62 (28)
Here’s where it starts to get interesting. The obvious draw here is the $23.7M 1901 Lajoie. .417/.461/.649, A+ at 2B and SS goes a long way. However, even if you remove him from the roster this team’s OPS# is still .872, which would rank second in this league. So yeah, my lineup is far and away the league’s best when everyone plays. But that won’t be all the time, as the ’02 Lajoie (.370/.418/.552) only has 459 PA and ’01 McGraw (.506 OBP) only has 376. And my pitching staff ranks only 16th among teams that were drafted. On the plus side, my defense is pretty good. All of this to say, I’m not completely sold on this team. On paper, in theory, they’re pretty good. But I don’t know how it will play out. This was likely a reach. I wanted them so I could avoid having to be involved in the League 2 draft, but that was a high price to pay if I don’t make the postseason.
I think deadball teams are especially difficult to compare using overall stats. Clearly, I have the best offense and worst pitching in my division. I’m showing my primary contender as chisock’s ’07-’08 Pirates/Senators, who I have at .804/2.37 compared to my .900/2.62. But what does that mean? Is a point of OPS as valuable as a point of ERC? Probably not. But what’s the ratio? My gut feeling is that a point of ERC is worth twice as much as a point of OPS, which would suggest that all else being equal my team should still be better. But that’s a complete guess. If it’s worth 4 times as much then my team is worse. Anyway, I won’t be shocked if this team fails to make the playoffs.
I just thought of a way to attempt to quantify the value of a point of OPS vs. ERC. I wish I had thought of this before the draft. Now I’m afraid to do it because it probably turns out that most of my teams suck.
This is why I use standard deviations. By calculating the league average and standard deviation for ERC# and OPS#, you can see exactly how an unbalanced team fares. Also, each league is different. In a tightly packed league, the standard deviation is smaller, so an outlier offensive or pitching unit will be more valuable.
One of the things I noticed is that most of *my* high-ranking teams that dropped to me in the second half of the draft were unbalanced teams. One extreme example was the 1975-76 Dodgers/Padres (I took at pick #20). Based on the rosters I built, this team was a whopping +2.4 standard deviations better than league average in pitching (ERC#) but a horrific -1.9 standard deviations in offense (OPS#). Just summing up those two standard deviations rates this team as above average, and then after factoring in that they are +1.9 standard deviations better in fielding, this team jumped up pretty high in my rankings.
That's interesting. I never thought about using standard deviations, but they are yet another thing that Excel is good at calculating.
Out of curiosity, do you factor speed and/or stolen bases into your calculations?
No, I do not factor in speed or stolen bases. Unless you're a Raines type base-stealer, I usually don't even bother with stealing bases. I will miss out of some teams b/c of this, like that mid 80's Raines x2 team that pedrocerrano selected.
And I know I need to improve how I factor in defense. Even in real life analytics, the proper evaluation of defense's affect on pitching has always been difficult to quantify. In theory, I should be applying the defensive grade to the pitching score (good defense improves my pitching score, bad defense makes it worse), but I've not figured out how to accurately do that, so I basically keep track of defensive score separately. So I add the pitching and hitting standard deviations together (i.e., equal weight), then add in a fraction of the defensive standard deviation to get my final roster score.
I really need to take some data from completed sim leagues and figure it out. This wouldn't be that hard to do, but the problem is that extreme ballparks complicates things. So, if a certain team's pitching is better or worse than expected (based on my formula), how much it due to defense vs playing in Petco or Wrigley? And of course, salary cap matters too. Even in $100M leagues, players will mostly underperform their real life stats... so how much weight should defense have on pitching in a $100M league a $160M league? A league with no cap?
Thinking about this some more, maybe I don't really want to solve how to accurately measure defense . The mystery is what keeps me coming back. Back in the early days of WIS, I remember when pitchers' salaries were 100% based on a player's real life ERA. Find pitchers who's ERA was way higher than their ERC, and you could crush the game. It was too easy back then, and I almost quit playing b/c of it. Luckily, admin recognized the flaw and recalibrated the salaries (this was well before the dynamic salaries).
1/19/2023 11:02 AM (edited)