2010 PrOPS Over- and Under-Performers (Through 6/15)
I have updated PrOPS through June 15 (minimum 200 PA). I report the top-30 over- and under-performers. Here is my previous post on 2010 PrOPS.
Top-30 Over-Performers Rk Player Team OPS PrOPS Diff PA 1 Andres Torres SFG 0.885 0.721 0.164 220 2 Justin Morneau MIN 1.079 0.925 0.154 266 3 Kevin Youkilis BOS 1.043 0.889 0.154 273 4 Ichiro Suzuki SEA 0.830 0.698 0.132 293 5 Jayson Werth PHI 0.904 0.776 0.128 243 6 Nick Markakis BAL 0.818 0.695 0.123 282 7 Andrew McCutchen PIT 0.861 0.741 0.120 271 8 David DeJesus KCR 0.873 0.761 0.112 276 9 Colby Rasmus STL 0.997 0.888 0.109 223 10 Daric Barton OAK 0.818 0.712 0.106 293 11 Evan Longoria TBR 0.964 0.861 0.103 279 12 Carl Crawford TBR 0.831 0.731 0.100 274 13 Adam Dunn WSN 0.951 0.852 0.099 265 14 Johnny Damon DET 0.808 0.711 0.097 262 15 Ben Zobrist TBR 0.824 0.728 0.096 275 16 Billy Butler KCR 0.890 0.798 0.092 278 17 Fred Lewis TOR 0.780 0.689 0.091 218 18 Franklin Gutierrez SEA 0.755 0.666 0.089 273 19 Robinson Cano NYY 1.022 0.936 0.086 278 20 Brett Gardner NYY 0.842 0.763 0.079 236 21 Elvis Andrus TEX 0.722 0.647 0.075 279 22 Aubrey Huff SFG 0.909 0.835 0.074 256 23 David Freese STL 0.809 0.735 0.074 234 24 Jason Bay NYM 0.790 0.719 0.071 272 25 Brandon Phillips CIN 0.849 0.780 0.069 287 26 Andre Ethier LAD 1.021 0.959 0.062 203 27 Josh Hamilton TEX 0.941 0.880 0.061 268 28 Drew Stubbs CIN 0.738 0.678 0.060 242 29 Erick Aybar LAA 0.688 0.629 0.059 292 30 Troy Tulowitzki COL 0.869 0.810 0.059 257
Top-30 Under-Performers Rk Player Team OPS PrOPS Diff PA 1 Casey Kotchman SEA 0.551 0.749 -0.198 200 2 Carlos Lee HOU 0.658 0.823 -0.165 259 3 Hunter Pence HOU 0.751 0.906 -0.155 251 4 Jose Lopez SEA 0.571 0.717 -0.146 271 5 Kendry Morales LAA 0.833 0.970 -0.137 211 6 Skip Schumaker STL 0.613 0.748 -0.135 247 7 Ian Stewart COL 0.758 0.877 -0.119 224 8 Derek Jeter NYY 0.780 0.896 -0.116 301 9 Mike Napoli LAA 0.798 0.912 -0.114 211 10 Juan Rivera LAA 0.746 0.853 -0.107 223 11 Adam Lind TOR 0.636 0.737 -0.101 268 12 Carlos Gonzalez COL 0.824 0.919 -0.095 250 13 Cameron Maybin FLA 0.631 0.726 -0.095 201 14 Clint Barmes COL 0.671 0.761 -0.090 202 15 Carlos Pena TBR 0.736 0.823 -0.087 261 16 Aaron Hill TOR 0.666 0.752 -0.086 230 17 A.J. Pierzynski CHW 0.649 0.734 -0.085 204 18 Pedro Feliz HOU 0.567 0.651 -0.084 224 19 Carlos Quentin CHW 0.681 0.764 -0.083 224 20 Melky Cabrera ATL 0.646 0.724 -0.078 212 21 Nate McLouth ATL 0.577 0.653 -0.076 205 22 Yadier Molina STL 0.666 0.739 -0.073 227 23 Matt Wieters BAL 0.629 0.697 -0.068 231 24 Howie Kendrick LAA 0.712 0.777 -0.065 276 25 Miguel Tejada BAL 0.676 0.741 -0.065 265 26 Alcides Escobar MIL 0.657 0.722 -0.065 233 27 Jerry Hairston SDP 0.618 0.682 -0.064 229 28 Derrek Lee CHC 0.688 0.750 -0.062 270 29 Juan Pierre CHW 0.584 0.645 -0.061 277 30 Brandon Inge DET 0.715 0.774 -0.059 248
Looking at the numbers for Nick Markakis (since his underlying statistics suggest he is having a sustainably good season), I think you might be overweighting HR% in your model. His numbers:
Line Drive %: 20%
GB/FB: 0.82
BB%: 13.5%
K%: 14.2%
HBP%: 0.0%
HR%: 1.1%
Park: Baltimore (neutral park)
Other than his home run number, he is clearly and above average hitter (and certainly a better talent than a .695 OPS hitter). However, is extra base hit percentage (8.9%) is also above average. How would running the regression for XBH% instead of HR% change your results?
The estimates are based on past performance. The numbers are what the are. Alternate specifications are welcome.