I'm interested. I'm also skeptical.
You speak with the self-assuredness of the so-called "smartest guy in the room," and you frequently state your opinions as though they are facts chiseled in bedrock. You (obviously) defend your opinions, but defending something doesn't make it accurate, so frankly I'm looking for more than just a defense. I'm looking for an analytical justification. An awful lot of very smart people who do this for a living disagree with you. I'd like to see the analysis that makes you so sure that you're right and they're wrong.
Hey, maybe you have it. That's why I'm asking.
If it helps, let me try a short version.
Every one of these articles has a series of assumptions and the like that they admit are part of their process. If I point out the short-comings of what they're doing they'd likely say "Sure, accounted for that in there"...and they did. Over and over, so there's nothing wrong with that specifically.
I have issues with every part of what they do (beyond just the caveats), but let's completely ignore that discussion for now. Let's pretend and accept that the above, with all of the caveats, is fair enough. It's a generic approximation for some portion of the information based on a bunch of assumptions that may (or may not) be true.
Then they put a number in a chart and tell you THAT is the answer. People are lazy. They aren't going to do any work and they just look at the number, assume it's correct and the apply it across every situation. Teams are developing teams of people to do this internally. People write for Fangraphs (and other places) hoping to get noticed and get hooked up into a baseball operation. Me too, I get it.
...but the number in the chart is devoid of application. It fails at both ends because that's not how teams operate. They ARE doing application. They not only have their own approach (and I'd argue some of the ways they are intentionally skewing data now) but there's a bunch of other things that will matter at the end of the day. It will feel right in some portions of some range because there's elements of truth [if you will] that everyone is looking at. So where it matches up, cool, and if it doesn't match up, well, I'm only offering you what I'm offering you.
Fangraphs is the most guilty of just putting that number into a chart and doing multiplication and then putting a label at the top of the column that leads the masses to conclusions that aren't going to necessarily be consistent with the future because they lack application. That leads us to ridiculous things like "surplus value". Dave Stewart thought he was doing it correct in AZ and it got him fired. MacPhail and the Phillies were all that too for the last 5 years and look where it got them.
You want to regress the data and say it's linear and draw a line, cool, but the actual data isn't sitting on that line and it's wrong everywhere on the line especially at the ends.
....to hallas's point, the contract numbers are already accounting for the perceived discounts he's describing from the higher "worth 60-80M" numbers. That's already in the $$/win numbers. He's re-discounting the data to try and force it to match up because it doesn't.
For me, it's largely the presentation of the data. $$/win isn't a generic number for application because supply/demand (and there's a number of pieces in there, teams, positions, etc) is actually going to wind up driving the contracts for specific players. If you started parsing that out and try to develop more accuracy for the projections on specifics you'd have all kinds of issues....so we just roll them all up into a ball and let the masses run with them however they want.
But people like generic because they don't really want to do the rest of the work. They just want to multiply WAR by $$/WAR and pretend they know something about the contract projection.
