Tuesday, March 31, 2009
On Browning.
$100k sounds like a lot of money to owe in child support. But we're dealing with someone who should be worth multiple millions. Of course, I have no idea what he's currently worth...but according to BRef, Browning made $16,713,333 in his 12-year big league career.
So, his back child support amounts to 0.5% of his total earnings. That's before the considerable money he should have made with via investments over the years.
For comparison, let's say I make a $40k salary and work for 12 years. I'd make $480,000 total. 0.5% of that is $2,400.
I hesitate to get too judgemental without hearing Browning's side... but still, pay up, Tom.
Monday, March 30, 2009
Jose Tabata's story
There are so many bizarre things wrapped up in this story that I'm not really sure where to start. Just off the top:
-Jose Tabata's wife is 43?
-Jose Tabata's wife has multiple aliases?
-Jose Tabata gave the Pirates wrong information about his wife's name?
-And, oh yeah, Jose Tabata's wife may have kidnapped a two-month old baby.
Thanks to Thunder for the link.
UPDATE: More details. Tabata's wife has a rap sheet that includes theft and fraud. The U.S Immigration and Customs Enforcement has begun an investigation. It sounds like she's in very serious trouble. Hopefully, Jose is as surprised by some of these details as I am, because it would be terrible if he were connected to all this--not, obviously, just for baseball reasons but because he's a young kid with a long life ahead of him.
UPDATE II: Tabata says he's "shocked" by what his wife did.
A few days later, Tabata released a statement:
The truth is that my wife told me many lies that, until this whole situation began, I did not know. One that hurt me a lot was her history as a criminal- that she had spent years in prison, that she had robbed and committed fraud. But the worst lie was that she completely falsified her pregnancy and the eventual birth of a baby girl, which would have made me a father for the first time. Imagine how that made me feel.
Hard to know exactly what's going on in this situation. But signs are that this woman has been badly manipulating the much younger Tabata for quite some time. Hopefully he'll be able to put all of this stuff behind him. I'm going to try to make it to quite a few Curve games this season, so I'll be chearing for the kid.
Friday, March 27, 2009
5 Questions - Cincinnati Reds
What I tried to do in this piece is to do a comprehensive projection of the Reds ballclub and use that as a basis of looking forward at this coming season. This is kind of an extension to my recent pieces on 2009 catchers and 2009 opening day outfielders, but extended to the entire team. It addresses many of the very reasonable and problematic concerns that folks had about the outfield study in a manner that I think is pretty reasonable.
The results were surprising, to say the least, especially on offense:
Overall, after working through the projections and forcing the plate appearances to match last years' Reds, my estimate for 2009 Reds offense was.... 25 runs above average. If the NL average is 734 runs scored per team, as it was last year, that would put the Reds at 759 runs scored. That would have ranked sixth in the league in 2008. And this is from a team that scored just 704 runs last year with a partial season of Adam Dunn. Granted, if you adjust for park effects, you should cull 15 or so runs off of this total. But even so, most of us think of the Reds as a below-average hitting team these days. These data indicate that this isn't the case.All rate stats are built upon CHONE, but I assigned playing time via a process that is part objective and part intuition. The article has a description of these methods at its end. The total projected plate appearances are matched to last year's team PA's, while the innings pitched are matched to last year's IP.
In the interest of showing my work, here are projected statistics for all players on this imaginary Reds team of mine:
Hitters | PT-Coef | PA | AB | H | 2B | 3B | HR | BB | SO | HBP | SB | CS | AVG | OBP | SLG | wOBA | lwts | RAR | FLD | PosAdj | WAR |
Brandon Phillips | 100% | 594 | 550 | 149 | 27 | 4 | 22 | 38 | 95 | 6 | 20 | 6 | 0.271 | 0.325 | 0.455 | 0.338 | 7.5 | 25.5 | 6.4 | 2.0 | 3.6 |
Joey Votto | 100% | 576 | 512 | 146 | 31 | 2 | 24 | 62 | 115 | 2 | 11 | 5 | 0.285 | 0.365 | 0.494 | 0.373 | 21.8 | 39.3 | 2.7 | -9.7 | 3.4 |
Jay Bruce | 100% | 536 | 493 | 136 | 26 | 4 | 27 | 40 | 139 | 3 | 10 | 5 | 0.276 | 0.334 | 0.509 | 0.361 | 15.5 | 31.8 | 1.7 | -5.4 | 3.0 |
Edwin Encarnacion | 100% | 561 | 499 | 140 | 31 | 1 | 23 | 54 | 94 | 8 | 5 | 1 | 0.281 | 0.360 | 0.485 | 0.368 | 19.6 | 36.7 | -12.1 | 1.9 | 2.8 |
Ramon Hernandez | 100% | 467 | 425 | 113 | 22 | 1 | 16 | 37 | 63 | 5 | 1 | 0 | 0.266 | 0.332 | 0.435 | 0.336 | 4.1 | 18.3 | -3.7 | 7.8 | 2.4 |
Alex Gonzalez | 100% | 432 | 400 | 103 | 23 | 1 | 12 | 28 | 74 | 4 | 2 | 1 | 0.258 | 0.313 | 0.410 | 0.317 | -3.3 | 9.8 | 0.0 | 4.4 | 1.5 |
Willy Taveras | 100% | 543 | 502 | 137 | 22 | 3 | 2 | 35 | 82 | 6 | 39 | 9 | 0.273 | 0.328 | 0.341 | 0.303 | -7.9 | 8.6 | 2.5 | 1.8 | 1.4 |
Jonny Gomes | 74% | 327 | 282 | 72 | 15 | 1 | 18 | 40 | 86 | 5 | 7 | 3 | 0.255 | 0.357 | 0.507 | 0.373 | 12.7 | 22.6 | -7.1 | -3.3 | 1.3 |
Chris Dickerson | 75% | 375 | 329 | 78 | 15 | 4 | 12 | 43 | 120 | 2 | 13 | 4 | 0.238 | 0.330 | 0.419 | 0.330 | 1.5 | 12.9 | 1.7 | -3.8 | 1.2 |
Jeff Keppinger | 57% | 294 | 271 | 80 | 16 | 1 | 4 | 22 | 18 | 1 | 2 | 1 | 0.297 | 0.353 | 0.408 | 0.339 | 2.7 | 11.6 | -2.3 | 1.0 | 1.1 |
Ryan Hanigan | 43% | 163 | 145 | 38 | 7 | 0 | 2 | 17 | 23 | 2 | 0 | 0 | 0.262 | 0.345 | 0.362 | 0.321 | -1.0 | 4.0 | 0.0 | 2.7 | 0.7 |
Jerry Hairston Jr. | 74% | 248 | 226 | 60 | 13 | 1 | 4 | 19 | 34 | 3 | 7 | 2 | 0.265 | 0.328 | 0.395 | 0.321 | -0.9 | 6.6 | 1.5 | -2.5 | 0.6 |
Danny Richar | 29% | 153 | 140 | 37 | 8 | 1 | 4 | 12 | 26 | 1 | 3 | 1 | 0.261 | 0.321 | 0.418 | 0.324 | -0.2 | 4.4 | 0.0 | 0.5 | 0.5 |
Norris Hopper | 37% | 140 | 130 | 38 | 6 | 1 | 1 | 9 | 14 | 1 | 4 | 1 | 0.290 | 0.339 | 0.364 | 0.316 | -1.2 | 3.0 | 1.9 | -1.4 | 0.4 |
Adam Rosales | 29% | 143 | 131 | 33 | 8 | 1 | 4 | 10 | 31 | 2 | 2 | 1 | 0.254 | 0.313 | 0.426 | 0.322 | -0.3 | 4.0 | -1.5 | 0.5 | 0.3 |
Paul Janish | 29% | 140 | 127 | 30 | 7 | 1 | 2 | 12 | 26 | 1 | 1 | 0 | 0.233 | 0.305 | 0.350 | 0.294 | -3.7 | 0.5 | 0.2 | 1.4 | 0.2 |
Wilkin Castillo | 21% | 93 | 89 | 22 | 5 | 0 | 1 | 4 | 14 | 1 | 2 | 1 | 0.249 | 0.288 | 0.354 | 0.284 | -3.3 | -0.4 | 0.0 | 1.6 | 0.1 |
Pitchers | 6% | 326 | 313 | 39 | 7 | 0 | 1 | 12 | 108 | 0 | 1 | 1 | 0.124 | 0.159 | 0.157 | 0.146 | -39.0 | -29.1 | 0.0 | 0.0 | -3.1 |
Totals | 6110 | 5564 | 1450 | 288 | 30 | 179 | 493 | 1163 | 53 | 131 | 42 | 0.261 | 0.327 | 0.420 | 0.328 | 25 | 210 | -8 | 0 | 21 |
PT-Coef is a playing time coefficient that I used to adjust time for each player. lwts is relative to average, and RAR is a conversion of that number to replacement level (using 2.0 wins/season as replacement in the NL). FLD is Rally's fielding projection, PosAdj are Tom Tango's position adjustment numbers based the designated CHONE position (I did change Hairston to an OF). WAR is the sum of RAR, FLD, and PosAdj.
None of the offensive numbers are park adjusted (i.e. they are given as expected to be seen playing half of one's games in GABP)--this is because I wanted to directly compare them to 2008 raw numbers. But that means that the WAR values, in particular, are overestimates of value if you wanted to take them and convert them to
You'll note that the smallest number of PA's went to Castillo with 93. Most "real" teams have a lot of players in the 10-30 range by the end of the season, and they don't tend to be good performances. I sort of think of Castillo's and maybe Janish's line as essentially taking all of those performances and lumping them together. So I don't think that's a huge problem here, though I could be wrong..
Now the pitchers:
Pitchers | G | GS | IP | ERA | ER | R | H | HR | BB | SO | HB | RAR |
Edinson Volquez | 30 | 30 | 166 | 3.58 | 66 | 71 | 138 | 16 | 78 | 170 | 9 | 34 |
Aaron Harang | 29 | 29 | 193 | 4.01 | 86 | 93 | 192 | 26 | 50 | 162 | 5 | 31 |
Bronson Arroyo | 30 | 30 | 188 | 4.40 | 92 | 99 | 196 | 24 | 62 | 143 | 7 | 21 |
Johnny Cueto | 27 | 27 | 146 | 4.19 | 68 | 74 | 138 | 21 | 54 | 130 | 9 | 19 |
Micah Owings | 20 | 20 | 111 | 4.29 | 53 | 57 | 109 | 14 | 39 | 86 | 10 | 13 |
Homer Bailey | 20 | 20 | 103 | 4.61 | 53 | 57 | 104 | 13 | 48 | 77 | 3 | 9 |
Francisco Cordero | 65 | 0 | 64 | 3.38 | 24 | 26 | 54 | 5 | 28 | 69 | 2 | 7 |
Bill Bray | 62 | 0 | 62 | 3.48 | 24 | 26 | 54 | 6 | 25 | 65 | 2 | 5 |
Jared Burton | 60 | 0 | 68 | 3.97 | 30 | 32 | 63 | 7 | 30 | 60 | 3 | 2 |
Mike Lincoln | 42 | 0 | 45 | 4.00 | 20 | 22 | 44 | 5 | 16 | 36 | 2 | 2 |
Nick Masset | 49 | 0 | 57 | 3.95 | 25 | 27 | 56 | 5 | 22 | 47 | 2 | 2 |
Matthew Maloney | 2 | 2 | 12 | 4.34 | 6 | 6 | 11 | 2 | 4 | 10 | 1 | 2 |
Ramon A Ramirez | 2 | 2 | 10 | 4.38 | 5 | 5 | 9 | 1 | 5 | 8 | 0 | 1 |
Arthur Rhodes | 44 | 0 | 31 | 3.77 | 13 | 14 | 28 | 2 | 15 | 31 | 1 | 1 |
Daniel Herrera | 42 | 0 | 49 | 4.41 | 24 | 26 | 50 | 7 | 17 | 37 | 2 | 1 |
Daryl Thompson | 2 | 2 | 10 | 4.73 | 5 | 6 | 11 | 2 | 4 | 7 | 0 | 1 |
Pedro Viola | 13 | 0 | 15 | 4.91 | 8 | 9 | 15 | 2 | 8 | 13 | 1 | -1 |
Dave Weathers | 60 | 0 | 62 | 4.35 | 30 | 32 | 63 | 6 | 26 | 40 | 3 | -1 |
Josh Roenicke | 51 | 0 | 50 | 4.50 | 25 | 27 | 49 | 7 | 24 | 47 | 2 | -1 |
RAR in this case is straight from Rally's tables (prorated for innings), and so it should be park-neutral. He also (somehow) adjusts for fielding, and given how close the Reds' forecasted team is to average in the field (it should be just a bit below average), I see no real payoff to trying to do any further adjustments. This rotation, if it lives up to these numbers, would be freaking fantastic. Let's hope it at least comes close!
Anyway, that at least should help you see where these data are coming from.s.
You'll note that the smallest number of PA's went to Castillo with 93. Most "real" teams have a lot of players in the 10-30 range by the end of the season, and they don't tend to be good performances. I sort of think of Castillo's and maybe Janish's line as essentially taking all of those performances and lumping them together. So I don't think that's a huge problem here, though I could be wrong..
Now the pitchers:
Pitchers | G | GS | IP | ERA | ER | R | H | HR | BB | SO | HB | RAR |
Edinson Volquez | 30 | 30 | 166 | 3.58 | 66 | 71 | 138 | 16 | 78 | 170 | 9 | 34 |
Aaron Harang | 29 | 29 | 193 | 4.01 | 86 | 93 | 192 | 26 | 50 | 162 | 5 | 31 |
Bronson Arroyo | 30 | 30 | 188 | 4.40 | 92 | 99 | 196 | 24 | 62 | 143 | 7 | 21 |
Johnny Cueto | 27 | 27 | 146 | 4.19 | 68 | 74 | 138 | 21 | 54 | 130 | 9 | 19 |
Micah Owings | 20 | 20 | 111 | 4.29 | 53 | 57 | 109 | 14 | 39 | 86 | 10 | 13 |
Homer Bailey | 20 | 20 | 103 | 4.61 | 53 | 57 | 104 | 13 | 48 | 77 | 3 | 9 |
Francisco Cordero | 65 | 0 | 64 | 3.38 | 24 | 26 | 54 | 5 | 28 | 69 | 2 | 7 |
Bill Bray | 62 | 0 | 62 | 3.48 | 24 | 26 | 54 | 6 | 25 | 65 | 2 | 5 |
Jared Burton | 60 | 0 | 68 | 3.97 | 30 | 32 | 63 | 7 | 30 | 60 | 3 | 2 |
Mike Lincoln | 42 | 0 | 45 | 4.00 | 20 | 22 | 44 | 5 | 16 | 36 | 2 | 2 |
Nick Masset | 49 | 0 | 57 | 3.95 | 25 | 27 | 56 | 5 | 22 | 47 | 2 | 2 |
Matthew Maloney | 2 | 2 | 12 | 4.34 | 6 | 6 | 11 | 2 | 4 | 10 | 1 | 2 |
Ramon A Ramirez | 2 | 2 | 10 | 4.38 | 5 | 5 | 9 | 1 | 5 | 8 | 0 | 1 |
Arthur Rhodes | 44 | 0 | 31 | 3.77 | 13 | 14 | 28 | 2 | 15 | 31 | 1 | 1 |
Daniel Herrera | 42 | 0 | 49 | 4.41 | 24 | 26 | 50 | 7 | 17 | 37 | 2 | 1 |
Daryl Thompson | 2 | 2 | 10 | 4.73 | 5 | 6 | 11 | 2 | 4 | 7 | 0 | 1 |
Pedro Viola | 13 | 0 | 15 | 4.91 | 8 | 9 | 15 | 2 | 8 | 13 | 1 | -1 |
Dave Weathers | 60 | 0 | 62 | 4.35 | 30 | 32 | 63 | 6 | 26 | 40 | 3 | -1 |
Josh Roenicke | 51 | 0 | 50 | 4.50 | 25 | 27 | 49 | 7 | 24 | 47 | 2 | -1 |
RAR in this case is straight from Rally's tables (prorated for innings), and so it should be park-neutral. He also (somehow) adjusts for fielding, and given how close the Reds' forecasted team is to average in the field (it should be just a bit below average), I see no real payoff to trying to do any further adjustments. This rotation, if it lives up to these numbers, would be freaking fantastic. Let's hope it at least comes close!
Anyway, that at least should help you see where these data are coming from.
Update: More discussion at RedsZone, RedReporter, and RedLegNation.