I sent the latest update in this afternoon. The most significant change from the programming side is a bugfix that was giving pitchers too many innings, by about 3%. So pitchers who did have 200 innings got moved down to about 194, without any of their hit/run/walk/strikeout numbers changing (those numbers had already been set by the program; literally the last step is take all the batters faced that are left over, and convert those to outs, and that’s where the bug was.) That had the side-effect of requiring me to pump about 30 innings back from the starters to the bullpens, with some slight rearrangement for teams who were stronger in one than the other.

There were also quite a few changes to the hitters, but not from the program. As I was preparing for my first draft (tomorrow!) I came to the realization that I was just being too conservative with the PA I was giving to the top, no doubt they’re starting as long as they’re healthy, types of players. Those players got their PA set by my eyeball rather than the computer-derived number, with a strong favoritism towards the median value for the past five years.

I also blew the dust off the playoff odds routine and ran the current projections though it, producing the results you’ll find here. That chart uses the basic projections to set the performance for each team, and then plays the season a million different times using the actual schedule. A key feature of this model is that it does not treat the Red Sox, for example, as a definite .577 team, even though that’s what their latest projection says. That .577 rating is an estimate of the Red Sox value; it may be higher (key players may do better than expected), although there’s a lot more ways it could end up worse (injuries, in addition to just randomly worse performances). This model creates a spread of values used for each “year” run in the model – perhaps .578 in year 1, then .534 in year 2, .601 in years 3, etc etc up to a million. The spread is a curve that has a median value of .577 (meaning that there are just as many scores below .577 as above it) –  but it has a longer tail to the low side, so the mean value will be a little below .577.

Unfortunately, the American League looks rather dull – my models clearly and unambiguously favor the Red Sox, Yankees, Tigers, and Rangers to make the playoffs, with only weak challenges led by the Angels and Rays. Fortunately, the National League looks to be almost totally up for grabs. The Phillies and Marlins provide a strong East race (the Nationals break .500, but there’s too much power in the division for them to contend). The Cardinals, Red, and Brewers have been repeatedly swapping positions through my various updates, so it is no surprise that they all have solid chances to win. And the West is even tighter, between the Giants, Diamondbacks, and Rockies – I would say that is officially too close to call.

And I have to note, with some sadness, the passing of Gary Carter. For ten consecutive years, from 1977-86, I have Carter rated (by WARP) as the #1 catcher in the National League; seven of those he was the #1 catcher in both leagues, and in 1982 he was the #1 player in the NL (losing the major league title to Robin Yount’s spectacular season).  That creates a strongly affirmative answer the question, “Was he the best player at his position?”, the number 3 item on Bill Jmaes’ Keltner List.  By one way I ran for comparing players all-time, I rated Carter as the #2 catcher – only behind Bench. It is ridiculous, beyond ridiculous, that he was not elected on the first ballot.

But Carter’s death holds a special poignancy for me, because, just a few months prior to his initial diagnosis, I had a similar run-in with the medical establishment – a shadow on a CT and overhearing a long and largely unintelligible word that ended with the suffix “-oma”. Mine, fortunately for me, turned out to be of a type that is as passive and benign as Carter’s was aggressive and malignant – but it took a couple of weeks to get the tests done to verify that, and I certainly have not forgotten the fear that came in the meantime. There, but for the grace of God, go I.




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