Contract structure:

1st year: $1

Defferrals: $49,999,999, starting in the year 10,000

BREAKING: Jason has agreed to pay Evan $50,000,000 in a 1 year contract, pending physical. Deferrals are believed to be included.

Asking about the Superbowl halftime show *is* political in today's climate. It has been political ever since Republicans started objecting to the performer on grounds of not being "American" enough.

Is that not effectively what this is? You think it's a coincidence they're asking about a hot button political topic related to the sport of football?

I think we could get more value from eg a position by position breakdown (I have my expectations based on data I've seen in the past), but it's still good to learn these things.

From this article, I learned 41% of NFL players think Bad Bunny was a bad choice of performer. That tells me a very sizable portion (obviously not that whole 41%) agrees with xenophobic right wing ideas about an "American" half time performer.

I think it is a fundamentally good thing when we as fans are reminded where sports players lie politically, almost as a sort of warning to not idolize them. Without anonymous surveys like this, we would not hear about how many NFL players think these things.

If a poll was entirely sports related (eg the MLB players poll) do you think the poll should not be anonymous? Or is the objection just to an anonymous poll on a semi-political topic within the league

The value is that you don't get responses to a survey if there isn't anonymity. The Athletic does a ton of surveys, and they want to get a representative sample of the league. If they don't make them anonymous, some players might be afraid to respond with their actual opinions.

Ok, so if I substitute that sqrt expression for v, then substitute vx - vwindx, vy - vwindy, etc, that should work?

Also is omega spin rate (rpm) or angular velocity (radians per second)? I sort of assume the latter, but I figure it could be either

@pobguy.bsky.social When using your baseball equations of motion, to account for wind, can I simply substitute (v - v_wind) for v, v_z - v_(wind in z direction) for v_z, and so on?

Pitchers get more strikeouts, prevent more runs, etc as a direct result of their catcher's framing skills (or a wide zone. either way, exploit in the rules) why do they get credit (through allowing fewer runs) in WAR but catchers can't? Either way, you're giving someone credit for exploiting rules

What's that hanging off your lanyard?

@dkappelman.fangraphs.com Why does the formula for LOB% subtract 1.4*HR in the denominator? I would get subtracting just 1*HR (the batter in a HR isn't a baserunner, so exclude them from the denominator), but why subtract the average run value of a HR?

I understand that the difference would likely be minimal, but I'm just curious as to why you chose when creating FIP to have it be constant. Is it a matter of simplicity?

That term doesn't necessarily have to be constant though. I don't see why the PA term has to be the league average PA/IP instead of the pitcher's individual PA/IP. Wouldn't that fix the bias from better pitchers having fewer PAs?

@tangotiger.com How did you decide to make the FIP constant something that's the same leaguewide? From your article deconstructing FIP (www.insidethebook.com/ee/index.php...) it appears that, instead of a constant, you could instead have a weight (around 0.8) for PAs in the numerator of FIP.

Sorry I'm struggling to connect the dots here. Are you saying that because teams all get the same number of outs, that's why the number of plate appearances doesn't affect R - wRAA for teams?

And I'm now seeing more stuff that implies this is wrong (the gradient between wRC specifically and runs = 1). Really not sure what's going on. wRC's formula (rearranged) is wRC - wRAA = k*PA, but R - wRAA ≠ k*PA, so why does the wRC formula work?

tldr it appears that the number of PAs a team has does not have any effect on what the "average" level is in wRAA. No idea why this is. That means that wRC gives too much credit to teams that have more PAs and penalizes teams with fewer PAs too much, because somehow wRAA has already normalized this.

So if this observation is correct (and I have no clue why it would—it seems VERY wrong) it would appear that the correct formula for wRC would be something like wRAA + lgR/G * TG. Trying this out, we can see the relationship is significantly closer to expected (maybe it should be lgR/out * outs?)

...it appears that they are expected to score the same number of runs assuming they've both played a whole season, because there is no relationship between the number of runs that is average (R - wRAA) and PA (excluding the 2020 season).

...as the same regardless of the number of PAs they have. Then, wRC is calculating by adding R/PA * PA, which then inflates the runs produced of teams with more PAs.

To illustrate it with an example. If one team has 100 wRAA in 100 PAs and another team has 100 wRAA in 50 PAs...

of weighted runs is also higher in a higher number of PAs) but when comparing wRAA and runs, the expected relationship occurs.

I think this might be why the issue with wRC occurs. wRAA somehow (still not clear on why this is the case, but it appears to be) sets the average value for every team...

Ok I think I figured out the issue with wRAA vs RAA. The issue is that teams who score more runs have a higher "average" by my formula due to having more PAs, which suppresses their RAA slightly. I'm not quite sure why the same thing doesn't happen to wRAA (surely the average number...

Obviously an approximation but 27 outs per game should be close enough, still getting the same result. Outs/G is slightly lower than 27, but not by a ton.

Also: wRAA and RAA aren't per PA, so if the issue was using the wrong denominator, the wRAA vs RAA regression wouldn't have the same issue

Where can I find runs per out? The number of outs will be roughly 27*G, but not quite because of extra innings (and in 2020, the 7 inning double headers).

I also see a very similar result when comparing wRAA and RAA (runs above average, comparing the number of runs a team scored to lgR/PA * the team's number of PAs) where wRAA assumes the team will have a higher magnitude of RAA than they actually do (farther from the mean of 0)

CC @tangotiger.com to see if he can explain why this is or if I've gone wrong somewhere (I could be incorrect that one point of wRC+ is supposed to be one percentage point above average in run scoring). I recommend skipping to the end because the rest is not strictly necessary for what I've found