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Transaction Oracle — A Timely Look at Transactions as They Happen Thursday, May 26, 2005ZiPS InSeason ProjectionsI’ve added a simple spreadsheet I use to calculate ZiPS projections inseason. You enter the projection and the seasontodate stats and the spreadsheet automatically calculates the weights and makes a new baseline projection. The spreadsheet then calculates the rest of the season and spits out the totals. Anyone who downloaded my toosoon posting last night should download it again. I had more time this morning and ironed out what I hope are the last of the kinks (I did a projection for Todd Walker and had a nasty surprise). 
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1. Joey B. has reignited his October #Natitude Posted: May 26, 2005 at 05:58 PM (#1363379)Whoopsydaisy. Better revise that sucker downwards. Way downwards.
As a side note, I actually uploaded the update file now. This has not been a good couple of days for me!
Now if we could get the YTD stats in a sheet and get a similar lookup working, that'd be awesome. Dan, a request for stuff like this going forward: could you include a standard player ID for each player (retrosheet, Lahman, STATS, DMB, whatever); that would make it really easy for others to add more data, crossreference, etc.
Brian Giles is up when I open the file, but if I type over his name with another, nothing happens but a bunch of errors.
How did you do that so easily? That's something I've never played with in Excel  if it's that simple, I can really streamline my projections this year.
Dan, Excel's lookup functions are really cool, and once you get the hang of them, they're really easy to use. Just look at the formulas in cells G4:R4 (it's really the same formula, just copied into all the cells).
I'm a bit surprised his awfulness hasn't impacted his projection more.
The only way Renteria is worth his deal is if he matches his ZiPS. Matching his PECOTA won't suffice.
ZiPS gives me hope!
I noticed that Mike Cameron's updated projection is for .259/.372/.483. This seems like a pretty big jump up from his original .244/.338/.449 projection, and it's only based on 65 AB, which sort of strikes me as odd. Am I doing something wrong?
Also, it would be really nice to have inseason stats in the sheet so that everything updates automagically on the projection sheet. That way one could quickly look at updated projections for any player without having to manually update each of the fields.
Those are 65 unbelievable ABs, though. He can go 034 and *still* be beating his projection.
But hey, sounds good to me.
How much are you weighting this years results versus the last three years?
Jeter is projected to hit 297/374/446 over the rest of the season to end up at 301/380/438 and 625 atbats.
From his great .292/.349/.528 projected line, he drops to a less than great .277/.328/.485...
Those first four are pretty nasty.
Silva 8 6 3.66 37 24 187.0 211 76 16 20 70
Radke 12 10 3.94 35 35 231.0 254 101 32 19 136
Santana 14 6 3.26 36 32 210.1 174 76 22 40 256
Mays 7 6 4.77 29 24 151.1 172 80 24 38 55
Lohse 9 10 4.76 31 29 172.0 190 91 24 48 96
165 total walks out of those five.
One problem with the hitter projections  the formula for projected HBP is referencing the cell for SB. So in the spreadsheet I downloaded, D'Angelo Jimenez is projected to get hit 7 times the rest of the season.
Specifically, cell P6 looks wrong. There's no column to the right for HBP, and it looks like there should be one, between AB and AC.
803 OPS+ and that has to be mashing from here on out.
Specifically, cell P6 looks wrong. There's no column to the right for HBP, and it looks like there should be one, between AB and AC.
Squashed that bug now. I had fixed the SB and CS bugs earlier, but forgot to do the HBP one. Essentially, that blue area is park neutral information and since there's no HBP park effects, I didn't make a HBP column over that, which made the columns not line up perfectly.
Part of the problems is that I didn't create an entirely new spreadsheet for this but modified the simple ZiPS spreadsheet (that doesn't incorporate multiple teams in one season). This saved me time on the one hand, but also served to cause some adaptability issues.
Get me near him and we'll talk.
The example that is in the spreadsheet I downloaded is Eric Milton. He's 35, which prorates to 1118 for the year. His original projection was 812. So we have 29 prorated decisions, and 20 decisions from the original projection. I would expect his new projection to be somewhere between those two. But his new projection is 20 decisions, because his 8 yeartodate decisions (not prorated) are heavily weighted in the new projection.
Maybe that's not the best example; it becomes more apparent with, say, Randy Johnson. His new projection is for less decisions than either his prorated YTD or his original projection. This seems wrong, but feel free to tell me that I just don't understand how this is working if that's the case.
Hope you don't mind me finding these errors  I really am using this tool! :)
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