November 06, 2008
Probabilistic Model of Range, 2008, Second Basemen
The following table shows how team second basemen ranked according to the Probabilistic Model of Range:
Team Second Basemen PMR, 2008, Visit Smooth Distance Model, 2008 data only
Team | In Play | Actual Outs | Predicted Outs | DER | Predicted DER | Ratio |
Marlins | 4338 | 527 | 500.98 | 0.121 | 0.115 | 105.19 |
Phillies | 4396 | 528 | 504.35 | 0.120 | 0.115 | 104.69 |
Reds | 4299 | 498 | 478.19 | 0.116 | 0.111 | 104.14 |
Diamondbacks | 4224 | 561 | 539.98 | 0.133 | 0.128 | 103.89 |
Cubs | 4156 | 500 | 487.52 | 0.120 | 0.117 | 102.56 |
Rockies | 4535 | 564 | 552.06 | 0.124 | 0.122 | 102.16 |
Tigers | 4536 | 505 | 495.02 | 0.111 | 0.109 | 102.02 |
Angels | 4374 | 545 | 535.72 | 0.125 | 0.122 | 101.73 |
Indians | 4513 | 554 | 545.22 | 0.123 | 0.121 | 101.61 |
Twins | 4607 | 513 | 505.30 | 0.111 | 0.110 | 101.52 |
Athletics | 4285 | 518 | 510.99 | 0.121 | 0.119 | 101.37 |
Blue Jays | 4215 | 532 | 525.31 | 0.126 | 0.125 | 101.27 |
Brewers | 4354 | 508 | 503.13 | 0.117 | 0.116 | 100.97 |
White Sox | 4409 | 535 | 533.38 | 0.121 | 0.121 | 100.30 |
Orioles | 4540 | 498 | 498.38 | 0.110 | 0.110 | 99.92 |
Cardinals | 4597 | 517 | 517.91 | 0.112 | 0.113 | 99.82 |
Yankees | 4349 | 556 | 557.46 | 0.128 | 0.128 | 99.74 |
Red Sox | 4232 | 505 | 508.07 | 0.119 | 0.120 | 99.40 |
Astros | 4292 | 464 | 467.09 | 0.108 | 0.109 | 99.34 |
Mariners | 4512 | 602 | 608.69 | 0.133 | 0.135 | 98.90 |
Rangers | 4667 | 539 | 546.88 | 0.115 | 0.117 | 98.56 |
Royals | 4413 | 547 | 555.11 | 0.124 | 0.126 | 98.54 |
Nationals | 4417 | 464 | 471.01 | 0.105 | 0.107 | 98.51 |
Braves | 4383 | 526 | 534.13 | 0.120 | 0.122 | 98.48 |
Pirates | 4683 | 466 | 478.32 | 0.100 | 0.102 | 97.43 |
Mets | 4335 | 476 | 492.58 | 0.110 | 0.114 | 96.63 |
Giants | 4232 | 417 | 432.81 | 0.099 | 0.102 | 96.35 |
Rays | 4264 | 472 | 490.56 | 0.111 | 0.115 | 96.22 |
Padres | 4419 | 475 | 499.74 | 0.107 | 0.113 | 95.05 |
Dodgers | 4265 | 484 | 514.65 | 0.113 | 0.121 | 94.04 |
The Marlins number one at second base? That certainly flies in the face of Dan Uggla's performance in the All-Star Game. It's not that surprising, however, to see the Dodgers with the aging Jeff Kent coming in last. On to the individual players:
Individual Second Baseman PMR, 2008, Visit Smooth Distance Model, 2008 data only (1000 balls in play)
Player | In Play | Actual Outs | Predicted Outs | DER | Predicted DER | Ratio |
Adam Kennedy | 2036 | 247 | 226.55 | 0.121 | 0.111 | 109.03 |
Mike Fontenot | 1448 | 175 | 160.82 | 0.121 | 0.111 | 108.82 |
Emilio Bonifacio | 1008 | 100 | 93.17 | 0.099 | 0.092 | 107.33 |
Chase Utley | 4231 | 513 | 485.09 | 0.121 | 0.115 | 105.75 |
Marco Scutaro | 1077 | 144 | 136.95 | 0.134 | 0.127 | 105.15 |
Placido Polanco | 3806 | 424 | 405.94 | 0.111 | 0.107 | 104.45 |
Dan Uggla | 3841 | 465 | 445.31 | 0.121 | 0.116 | 104.42 |
Howie Kendrick | 2341 | 308 | 295.94 | 0.132 | 0.126 | 104.07 |
Joe Inglett | 1554 | 205 | 197.44 | 0.132 | 0.127 | 103.83 |
Asdrubal Cabrera | 2446 | 316 | 304.98 | 0.129 | 0.125 | 103.61 |
Juan Uribe | 1112 | 138 | 133.57 | 0.124 | 0.120 | 103.32 |
Brandon Phillips | 3704 | 429 | 416.27 | 0.116 | 0.112 | 103.06 |
Clint Barmes | 1519 | 183 | 177.61 | 0.120 | 0.117 | 103.03 |
Mark Ellis | 3006 | 373 | 365.23 | 0.124 | 0.122 | 102.13 |
Alexi Casilla | 2611 | 288 | 282.01 | 0.110 | 0.108 | 102.12 |
Orlando Hudson | 2668 | 346 | 339.70 | 0.130 | 0.127 | 101.86 |
Kaz Matsui | 2485 | 267 | 265.25 | 0.107 | 0.107 | 100.66 |
Rickie Weeks | 3150 | 355 | 353.07 | 0.113 | 0.112 | 100.55 |
Dustin Pedroia | 4003 | 479 | 477.12 | 0.120 | 0.119 | 100.39 |
Brian Roberts | 4195 | 471 | 469.83 | 0.112 | 0.112 | 100.25 |
Robinson Cano | 4152 | 531 | 530.64 | 0.128 | 0.128 | 100.07 |
Sean Rodriguez | 1229 | 149 | 148.91 | 0.121 | 0.121 | 100.06 |
Mark Loretta | 1110 | 129 | 128.96 | 0.116 | 0.116 | 100.03 |
Jose Lopez | 3861 | 531 | 533.54 | 0.138 | 0.138 | 99.52 |
Alexei Ramirez | 3081 | 371 | 373.04 | 0.120 | 0.121 | 99.45 |
Luis Castillo | 2054 | 219 | 220.31 | 0.107 | 0.107 | 99.41 |
Mark Grudzielanek | 2175 | 280 | 282.08 | 0.129 | 0.130 | 99.26 |
Tadahito Iguchi | 1962 | 217 | 218.94 | 0.111 | 0.112 | 99.12 |
Jamey Carroll | 1800 | 206 | 207.94 | 0.114 | 0.116 | 99.07 |
Ian Kinsler | 3462 | 413 | 417.34 | 0.119 | 0.121 | 98.96 |
Kelly Johnson | 3631 | 441 | 448.84 | 0.121 | 0.124 | 98.25 |
Mark DeRosa | 1930 | 232 | 236.45 | 0.120 | 0.123 | 98.12 |
Freddy Sanchez | 3688 | 368 | 378.01 | 0.100 | 0.102 | 97.35 |
Eugenio Velez | 1355 | 128 | 133.20 | 0.094 | 0.098 | 96.09 |
Jeff Baker | 1174 | 139 | 144.85 | 0.118 | 0.123 | 95.96 |
Felipe Lopez | 2435 | 266 | 279.15 | 0.109 | 0.115 | 95.29 |
Aaron Hill | 1375 | 164 | 172.51 | 0.119 | 0.125 | 95.07 |
Akinori Iwamura | 3916 | 435 | 457.88 | 0.111 | 0.117 | 95.00 |
Aaron Miles | 1551 | 171 | 182.78 | 0.110 | 0.118 | 93.55 |
Alberto Callaspo | 1128 | 128 | 137.62 | 0.113 | 0.122 | 93.01 |
Ray Durham | 2160 | 212 | 228.31 | 0.098 | 0.106 | 92.86 |
Edgar Gonzalez | 1701 | 191 | 205.90 | 0.112 | 0.121 | 92.76 |
Brendan Harris | 1016 | 101 | 109.08 | 0.099 | 0.107 | 92.59 |
Damion Easley | 1607 | 170 | 186.57 | 0.106 | 0.116 | 91.12 |
Jeff Kent | 2630 | 290 | 318.37 | 0.110 | 0.121 | 91.09 |
One thing I need to look at more closely is why Dan Uggla does so well. In the previous post on shortstops, a couple of commenters wanted more proof that this system actually works. I was a bit suprised by Akinori Iwamura rating so low, so I thought I would look at his poorest plays to see if they made sense. Of his four worst plays, all with a probablility of .889 or higher of being turned, two were errors hit right at him. One was a grounder to his right when he was playing too far left (poor positioning) and one was just bad judgement on a double play ball.
To compare, I looked at Utley's best play, since he was the best regular at the position. All three of his best plays were balls to the right of first base that got by Howard off the bats of left handers. In each case, Utley ranged into the outfield to field the ball and throw out the batter at first, twice I believe to the pitcher covering. He made those plays because Howard couldn't, but he was positioned so well he was in the right place to cover for Ryan.
The other thing I noticed is that toughest plays Utley made were much tougher than the best plays Iwamura executed. At the other end, easiest balls in play that Iwamura failed to turn into outs were much easier than Utley's worse plays.
If anyone would like to review video on MLB.com for a particular player, I'll be happy to send you the dates and innings of their best and worst plays.
In case you want to check my work, Iwamura's worst plays were on 9/7, 3rd inning, 8/20, 9th inning, 4/25, 9th inning, 7/30, 5th inning. Utley's best plays were on 7/23, 1st inning, 7/1, 1st inning and 8/3, 3rd inning.
I am curious to know whether you or others have done an analysis to determine the variability of a player's defensive performance in general from year to year. In other words, other than the very good and the very poor fielders (performance of both are assumed to be fairly consistent), how much does a player's range vary from year to year as determined by PMR?
It appears that there aren't the extremes this year for the middle infielders that there have been in years past. The best, and worst, fielders are 20 plays above or below average...in past years, players were as much as 40-50 plays above or below average.
I was planning looking into the variation later in the off-season.
Marco Scutaro is the best SS and 5th best 2B - who knew - and what's with the Rickie Weeks detractors?
David:
If you want to send me Uggla's data, I'll be happy to take a look at his best/worst plays.
I'm surprised there aren't more Red Sox fans here commenting about Pedroia's 2-plays-above-average rating :)
Anyone know if it's possible/legal to post clips of individual fielding plays on the web? I'd love to put together something similar to the famous Jeter/Everett fielding video.
Sky,
My guess is that you could do it, but eventually MLB will make you take it down. I suppose, however, it could be circulated privately by email as long as no one charges for it and doesn't post it on the web.
You've improved this considerably since the year Orlando Hudson broke the model (ball-hog effect). Good work.
You might want to take a look at Rickie Weeks as a data set to show it is or isn't working. Most people seem to think he is so bad defensively that he needs to be moved to another position but PMR has him above average with range.
To be honest most defensive metrics show him as average this year, I think he just improved and people just key in on the mistakes still.