Razzball Hittertron – Next 7 Day (Weekly) Hitter Projections

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# Name Team ESPN Y! $ $U G PA AB H R HR RBI SB BB SO AVG OBP SLG OPS OWN%
Kendrys Morales SEA 1B 1B 38.8 45.6 1.0 4.1 3.7 1.1 0.9 0.3 0.9 0.0 0.3 1.0 0.308 0.378 0.523 0.901 54
Carl Crawford LAN OF OF 37.8 39.7 0.9 4.0 3.9 1.2 0.6 0.2 0.7 0.2 0.1 0.5 0.318 0.347 0.497 0.844 96
Adrian Gonzalez LAN 1B 1B 37.7 44.3 1.0 4.3 4.1 1.3 0.7 0.3 0.9 0.0 0.2 0.7 0.326 0.376 0.571 0.947 100
Carlos Gomez MIL OF OF 36.2 39.6 1.0 4.4 4.1 1.2 0.6 0.2 0.6 0.4 0.3 1.0 0.302 0.367 0.503 0.870 100
Robinson Cano SEA 2B 2B 33.7 30.5 1.0 4.2 3.8 1.3 0.7 0.2 0.7 0.0 0.4 0.6 0.350 0.440 0.584 1.024 100
Scooter Gennett MIL 2B 2B 29.2 26.3 1.0 4.0 3.8 1.2 0.5 0.2 0.6 0.2 0.1 0.6 0.325 0.366 0.476 0.842 54
Aramis Ramirez MIL 3B 3B 29.0 31.1 1.0 4.2 3.9 1.2 0.7 0.2 0.7 0.0 0.2 0.6 0.317 0.382 0.512 0.894 98
Hanley Ramirez LAN SS SS 28.1 24.9 0.9 3.8 3.6 1.0 0.5 0.2 0.6 0.1 0.2 0.6 0.289 0.358 0.493 0.851 100
Ryan Braun MIL OF OF 25.8 27.2 0.8 3.7 3.4 1.1 0.6 0.1 0.6 0.2 0.2 0.7 0.333 0.397 0.561 0.958 100
David Wright NYN 3B 3B 25.3 22.4 1.0 4.5 4.2 1.2 0.5 0.2 0.5 0.2 0.3 1.0 0.295 0.368 0.465 0.833 67
Dee Gordon LAN 2B, SS 2B, SS 24.7 31.0 0.9 4.7 4.5 1.3 0.7 0.0 0.4 0.5 0.2 0.8 0.292 0.326 0.389 0.715 100
Jonathan Lucroy MIL C,1B C, 1B 24.7 21.6 1.0 4.4 4.1 1.3 0.6 0.2 0.6 0.0 0.3 0.6 0.326 0.394 0.491 0.885 100
Jose Bautista TOR 1B, OF 1B, OF 23.7 24.1 1.0 3.9 3.5 0.9 0.6 0.3 0.7 0.0 0.4 0.6 0.243 0.362 0.527 0.889 100
Matt Kemp LAN OF OF 23.6 23.8 0.9 3.9 3.7 1.1 0.6 0.2 0.7 0.0 0.2 1.0 0.286 0.346 0.507 0.853 100
Matt Holliday STL OF OF 22.0 22.3 1.0 3.9 3.7 1.0 0.6 0.2 0.7 0.0 0.3 0.7 0.282 0.364 0.508 0.872 99
Andre Ethier LAN OF OF 21.7 21.9 0.8 3.5 3.2 1.0 0.6 0.2 0.6 0.0 0.2 0.6 0.302 0.370 0.500 0.870 11
Yasiel Puig LAN OF OF 20.3 21.6 0.8 3.8 3.6 1.2 0.5 0.2 0.5 0.1 0.2 0.7 0.326 0.374 0.521 0.895 100
Anthony Rendon WAS 2B, 3B 2B, 3B 20.3 18.3 0.9 4.0 3.8 1.2 0.5 0.1 0.4 0.2 0.2 0.6 0.318 0.361 0.461 0.822 100
Logan Morrison SEA 1B, OF 1B, OF 19.9 20.2 0.9 3.7 3.3 1.0 0.5 0.3 0.5 0.0 0.4 0.5 0.297 0.398 0.522 0.920 23
Coco Crisp OAK OF OF 19.5 20.7 0.7 3.2 3.0 0.8 0.6 0.2 0.4 0.1 0.2 0.3 0.262 0.349 0.446 0.795 93
Daniel Murphy NYN 2B, 3B 1B, 2B, 3B 19.5 17.0 1.0 4.4 4.2 1.2 0.5 0.1 0.4 0.1 0.2 0.6 0.295 0.349 0.444 0.793 88
Jed Lowrie OAK 2B, SS 2B, SS 19.4 14.0 0.8 3.2 3.0 0.8 0.5 0.2 0.6 0.0 0.2 0.4 0.278 0.339 0.442 0.781 58
David Ortiz BOS DH 1B 19.4 20.6 0.9 3.4 3.1 0.9 0.5 0.2 0.6 0.0 0.3 0.5 0.297 0.368 0.570 0.938 100
Bryce Harper WAS OF OF 18.7 20.2 0.9 3.9 3.6 1.1 0.5 0.1 0.5 0.2 0.3 0.8 0.300 0.382 0.519 0.901 100
Miguel Cabrera DET 1B, 3B 1B, 3B 17.3 19.2 1.0 3.8 3.6 1.1 0.6 0.2 0.7 0.0 0.2 0.6 0.316 0.373 0.522 0.895 100
Ian Desmond WAS SS SS 17.2 15.6 0.9 3.9 3.7 1.0 0.4 0.1 0.6 0.2 0.2 0.9 0.279 0.327 0.439 0.766 100
Jhonny Peralta STL SS SS 17.2 11.6 1.0 3.9 3.7 1.0 0.5 0.2 0.6 0.0 0.2 0.7 0.282 0.317 0.440 0.757 100
Edwin Encarnacion TOR 1B 1B, 3B 16.5 21.8 1.0 3.7 3.4 0.9 0.5 0.3 0.8 0.0 0.3 0.6 0.250 0.337 0.526 0.863 100
Jacoby Ellsbury NYA OF OF 16.4 19.1 1.0 4.0 3.7 1.0 0.5 0.1 0.4 0.3 0.2 0.6 0.282 0.334 0.410 0.744 90
Dustin Pedroia BOS 2B 2B 16.3 13.7 1.0 3.6 3.4 1.0 0.5 0.1 0.4 0.1 0.2 0.5 0.278 0.332 0.439 0.771 63
Kyle Seager SEA 3B 3B 15.4 17.3 1.0 4.1 3.7 1.1 0.5 0.2 0.6 0.0 0.4 0.9 0.308 0.403 0.537 0.940 100
Brandon Moss OAK 1B, OF 1B, OF 15.2 15.4 1.0 3.3 3.0 0.8 0.5 0.2 0.7 0.0 0.3 0.7 0.250 0.344 0.533 0.877 86
Josh Donaldson OAK 3B 3B 14.9 17.1 1.0 4.1 3.8 1.0 0.6 0.2 0.6 0.0 0.3 0.6 0.250 0.332 0.467 0.799 100
Ben Revere PHI OF OF 14.4 17.8 0.9 4.3 4.2 1.3 0.5 0.0 0.3 0.4 0.1 0.4 0.304 0.326 0.374 0.700 100
Jose Altuve HOU 2B 2B 14.4 13.4 1.0 4.3 4.2 1.3 0.5 0.0 0.4 0.3 0.1 0.4 0.318 0.326 0.426 0.752 100
Lucas Duda NYN 1B, OF 1B, OF 14.3 14.5 1.0 4.3 3.8 1.0 0.6 0.2 0.7 0.0 0.5 1.0 0.275 0.373 0.487 0.860 95
Dustin Ackley SEA 2B, OF 1B, 2B, OF 14.0 12.1 0.8 3.5 3.2 0.9 0.5 0.1 0.5 0.0 0.3 0.7 0.293 0.386 0.483 0.869 57
Josh Reddick OAK OF OF 13.6 13.9 0.9 3.4 3.2 0.8 0.5 0.2 0.6 0.0 0.2 0.5 0.250 0.329 0.508 0.837 43
Jayson Werth WAS OF OF 13.5 13.6 0.8 3.6 3.3 1.1 0.5 0.1 0.5 0.0 0.2 0.6 0.317 0.390 0.476 0.866 100
Arismendy Alcantara CHN 2B, OF 2B, OF 13.5 10.7 0.8 3.2 3.1 0.7 0.4 0.2 0.4 0.1 0.2 1.2 0.216 0.261 0.379 0.640 61
Chris Carter HOU 1B, OF 1B, OF 13.5 13.8 0.9 3.9 3.6 0.8 0.4 0.3 0.7 0.0 0.3 1.3 0.225 0.298 0.475 0.773 95
Todd Frazier CIN 1B, 3B 1B, 3B 13.3 11.3 0.9 3.8 3.5 0.9 0.5 0.1 0.5 0.1 0.3 0.9 0.263 0.326 0.438 0.764 100
Michael Brantley CLE OF OF 12.9 14.6 1.0 4.2 4.0 1.2 0.4 0.1 0.4 0.2 0.2 0.6 0.310 0.358 0.436 0.794 100
Brad Miller SEA 2B, SS 2B, SS 12.8 9.3 0.7 2.8 2.5 0.7 0.4 0.2 0.4 0.0 0.2 0.6 0.286 0.376 0.484 0.860 31
Salvador Perez KC C C 12.3 9.4 1.0 3.8 3.5 0.9 0.4 0.2 0.6 0.0 0.2 0.4 0.243 0.301 0.384 0.685 94
Mookie Betts BOS 2B, OF 2B, OF 11.8 10.9 0.9 3.8 3.6 1.0 0.5 0.0 0.4 0.3 0.2 0.5 0.275 0.334 0.442 0.776 94
Matt Adams STL 1B 1B 11.2 14.2 0.8 3.1 3.0 0.8 0.5 0.2 0.6 0.0 0.1 0.6 0.275 0.306 0.502 0.808 90
Billy Hamilton CIN OF OF 11.1 14.5 0.8 3.3 3.1 0.8 0.5 0.0 0.3 0.4 0.2 0.8 0.256 0.304 0.348 0.652 98
Khris Davis MIL OF OF 11.0 11.1 0.9 3.6 3.3 0.9 0.4 0.1 0.6 0.0 0.3 0.9 0.282 0.358 0.503 0.861 79
Dilson Herrera NYN 2B 2B 10.8 8.6 0.9 3.5 3.3 0.9 0.3 0.1 0.5 0.1 0.2 0.8 0.256 0.305 0.384 0.689 0
Yoenis Cespedes BOS OF OF 10.8 10.9 0.9 3.7 3.6 1.0 0.5 0.1 0.6 0.0 0.1 0.8 0.275 0.309 0.510 0.819 99
Mike Zunino SEA C C 10.5 7.8 0.9 3.5 3.2 0.7 0.5 0.2 0.5 0.0 0.3 1.2 0.222 0.311 0.451 0.762 29
Nelson Cruz BAL OF OF 10.2 10.4 1.0 4.0 3.8 1.0 0.5 0.2 0.6 0.0 0.2 0.9 0.250 0.304 0.473 0.777 100
Adam Jones BAL OF OF 9.6 9.8 0.8 3.4 3.3 0.9 0.4 0.2 0.5 0.0 0.1 0.6 0.268 0.301 0.461 0.762 100
Corey Hart SEA 1B OF 9.3 12.7 0.9 3.3 3.0 0.9 0.4 0.2 0.6 0.0 0.3 0.9 0.286 0.360 0.499 0.859 24
Jose Ramirez CLE 2B, SS 2B, SS 9.2 12.6 0.9 4.1 3.9 1.0 0.7 0.0 0.2 0.3 0.2 0.7 0.256 0.308 0.362 0.670 37
Ian Kinsler DET 2B 2B 9.1 7.0 1.0 4.1 3.9 1.0 0.5 0.1 0.4 0.1 0.2 0.4 0.244 0.302 0.383 0.685 100
Denard Span WAS OF OF 8.8 10.1 0.9 4.0 3.9 1.2 0.5 0.0 0.3 0.2 0.2 0.4 0.311 0.360 0.422 0.782 99
Allen Craig BOS 1B, OF 1B, OF 8.4 8.6 0.9 3.4 3.3 0.9 0.5 0.1 0.5 0.0 0.2 0.7 0.270 0.326 0.477 0.803 46
Asdrubal Cabrera WAS 2B, SS 2B, SS 8.3 4.6 1.0 4.1 3.9 1.1 0.4 0.1 0.4 0.0 0.2 0.7 0.293 0.343 0.444 0.787 98
Ryan Zimmerman WAS 3B, OF 1B, 3B, OF 8.2 9.7 1.0 3.9 3.7 1.1 0.5 0.1 0.5 0.0 0.2 0.7 0.308 0.357 0.474 0.831 77
Travis d’Arnaud NYN C C 8.1 6.5 0.7 3.0 2.8 0.8 0.3 0.2 0.4 0.0 0.2 0.5 0.275 0.329 0.454 0.783 38
Brian McCann NYA C,1B C, 1B 8.0 5.3 0.9 3.5 3.3 0.9 0.5 0.1 0.5 0.0 0.2 0.4 0.270 0.328 0.443 0.771 99
Wilson Ramos WAS C C 7.9 6.4 0.7 2.9 2.8 0.9 0.3 0.1 0.4 0.0 0.1 0.4 0.308 0.328 0.452 0.780 75
Devin Mesoraco CIN C C 7.9 5.8 0.8 3.0 2.8 0.7 0.4 0.1 0.5 0.0 0.2 0.8 0.243 0.319 0.434 0.753 92
Javier Baez CHN 2B, SS 2B, SS 7.7 4.9 1.0 4.0 3.8 0.8 0.4 0.2 0.5 0.1 0.2 1.5 0.200 0.253 0.382 0.635 89
J.J. Hardy BAL SS SS 7.6 2.7 1.0 3.7 3.6 0.9 0.4 0.2 0.5 0.0 0.1 0.6 0.237 0.283 0.383 0.666 81
Jason Kipnis CLE 2B 2B 7.4 5.7 0.8 3.4 3.2 0.8 0.3 0.1 0.4 0.1 0.2 0.7 0.263 0.342 0.398 0.740 92
Juan Uribe LAN 3B 3B 7.3 8.5 0.7 2.9 2.8 0.8 0.3 0.2 0.4 0.0 0.1 0.5 0.282 0.309 0.432 0.741 58
Seth Smith SD OF OF 7.3 7.5 0.9 4.0 3.7 1.0 0.5 0.1 0.6 0.0 0.3 0.8 0.282 0.351 0.391 0.742 33
Adam Lind TOR 1B 1B 7.1 10.8 1.0 3.3 3.1 0.9 0.5 0.2 0.6 0.0 0.2 0.5 0.273 0.330 0.500 0.830 67
J.D. Martinez DET OF OF 6.8 6.9 1.0 3.8 3.7 1.0 0.5 0.1 0.5 0.0 0.1 0.8 0.256 0.303 0.421 0.724 100
Xander Bogaerts BOS SS, 3B SS, 3B 6.8 2.7 0.9 3.6 3.4 0.9 0.4 0.1 0.5 0.0 0.2 0.9 0.263 0.294 0.411 0.705 98
Adam LaRoche WAS 1B 1B 6.8 9.4 0.9 3.8 3.4 1.0 0.5 0.1 0.5 0.0 0.3 0.7 0.289 0.380 0.495 0.875 96
Buster Posey SF C,1B C, 1B 6.8 4.4 0.9 3.8 3.5 1.1 0.5 0.0 0.5 0.0 0.2 0.4 0.308 0.370 0.506 0.876 100
Andrew McCutchen PIT OF OF 6.6 7.6 1.0 3.8 3.5 0.9 0.5 0.1 0.5 0.1 0.3 0.9 0.243 0.324 0.426 0.750 100
Carlos Beltran NYA OF OF 6.5 6.6 0.9 3.6 3.3 0.9 0.5 0.1 0.5 0.0 0.2 0.6 0.270 0.338 0.449 0.787 55
Jose Abreu CHA 1B 1B 6.4 10.9 1.0 3.7 3.4 0.9 0.4 0.3 0.6 0.0 0.3 0.8 0.250 0.323 0.456 0.779 100
Adrian Beltre TEX 3B 3B 6.3 7.9 1.0 3.7 3.5 1.0 0.5 0.2 0.4 0.0 0.2 0.5 0.297 0.345 0.448 0.793 100
Miguel Montero ARI C C 6.3 4.1 0.8 3.0 2.9 0.7 0.4 0.1 0.5 0.0 0.2 0.6 0.257 0.316 0.390 0.706 76
Austin Jackson SEA OF OF 6.1 7.9 1.0 4.5 4.1 1.2 0.5 0.0 0.4 0.2 0.4 1.2 0.302 0.380 0.455 0.835 94
Colby Rasmus TOR OF OF 6.1 6.2 0.8 2.6 2.5 0.6 0.4 0.2 0.4 0.0 0.2 0.7 0.242 0.292 0.464 0.756 51
Alejandro De Aza BAL OF OF 6.1 7.0 0.7 2.9 2.8 0.7 0.4 0.1 0.3 0.1 0.1 0.6 0.250 0.311 0.395 0.706 87
Lonnie Chisenhall CLE 1B, 3B 1B, 3B 5.9 7.5 0.9 3.8 3.6 0.9 0.5 0.1 0.5 0.0 0.2 0.8 0.263 0.326 0.433 0.759 75
Starling Marte PIT OF OF 5.9 8.0 1.0 3.5 3.4 0.8 0.4 0.1 0.4 0.2 0.2 1.0 0.222 0.276 0.365 0.641 100
Jorge Soler CHN OF OF 5.8 5.9 0.8 2.9 2.7 0.7 0.3 0.2 0.5 0.0 0.2 0.8 0.250 0.299 0.433 0.732 100
Carlos Santana CLE C, 1B, 3B C, 1B, 3B 5.7 2.9 1.0 4.2 3.6 1.0 0.5 0.1 0.5 0.0 0.5 1.0 0.263 0.373 0.450 0.823 100
Jason Castro HOU C C 5.4 3.6 0.8 3.2 3.0 0.7 0.3 0.2 0.4 0.0 0.2 0.9 0.237 0.298 0.403 0.701 37
Jose Reyes TOR SS SS 5.4 6.9 1.0 4.0 3.8 1.0 0.5 0.0 0.4 0.2 0.2 0.4 0.275 0.317 0.420 0.737 100
Anthony Rizzo CHN 1B 1B 5.4 8.9 0.9 3.7 3.4 0.8 0.5 0.2 0.5 0.0 0.3 0.8 0.237 0.325 0.497 0.822 100
Gerardo Parra MIL OF OF 5.2 5.4 0.8 3.6 3.4 1.1 0.5 0.0 0.4 0.0 0.2 0.7 0.317 0.376 0.471 0.847 32
Curtis Granderson NYN OF OF 5.2 5.5 0.9 3.9 3.5 0.8 0.5 0.2 0.5 0.0 0.4 0.9 0.231 0.352 0.460 0.812 87
Mike Moustakas KC 3B 3B 5.2 7.0 1.0 3.6 3.3 0.8 0.5 0.2 0.6 0.0 0.3 0.4 0.229 0.300 0.397 0.697 25
Adam Dunn OAK 1B 1B, OF 5.1 7.8 0.8 2.9 2.6 0.6 0.4 0.2 0.6 0.0 0.3 0.7 0.235 0.333 0.463 0.796 52
Jean Segura MIL SS SS 4.8 6.0 0.8 3.0 3.0 0.9 0.4 0.0 0.4 0.2 0.1 0.4 0.306 0.349 0.428 0.777 75
Chris Owings ARI 2B, SS 2B, SS 4.6 3.3 0.9 3.4 3.4 0.9 0.4 0.1 0.4 0.1 0.1 0.8 0.250 0.258 0.354 0.612 43
Victor Martinez DET 1B 1B 4.5 7.0 1.0 3.8 3.6 1.1 0.5 0.1 0.5 0.0 0.2 0.3 0.316 0.367 0.445 0.812 100
Alex Gordon KC OF OF 4.4 4.7 1.0 3.9 3.5 0.9 0.5 0.2 0.4 0.0 0.4 0.6 0.243 0.344 0.419 0.763 100
Brett Gardner NYA OF OF 4.3 5.1 0.7 3.0 2.8 0.7 0.4 0.1 0.3 0.1 0.2 0.6 0.256 0.333 0.382 0.715 95
Nick Markakis BAL OF OF 4.3 4.5 0.8 3.6 3.4 0.9 0.4 0.1 0.4 0.0 0.2 0.4 0.262 0.322 0.381 0.703 85
Torii Hunter DET OF OF 4.1 4.3 0.9 3.7 3.6 1.0 0.5 0.1 0.5 0.0 0.1 0.5 0.268 0.313 0.411 0.724 100
Eric Hosmer KC 1B 1B 4.1 7.4 0.9 3.6 3.3 0.8 0.5 0.2 0.5 0.0 0.3 0.5 0.250 0.333 0.418 0.751 93
Starlin Castro CHN SS SS 4.0 -0.5 1.0 3.3 3.2 0.9 0.3 0.1 0.4 0.0 0.1 0.8 0.265 0.295 0.387 0.682 74
Yadier Molina STL C C, 1B 4.0 1.3 1.0 3.8 3.7 1.1 0.5 0.0 0.5 0.0 0.1 0.4 0.308 0.331 0.454 0.785 94
Kolten Wong STL 2B 2B 3.7 2.9 0.9 3.4 3.3 0.9 0.5 0.0 0.4 0.1 0.1 0.5 0.270 0.297 0.421 0.718 81
Alexei Ramirez CHA SS SS 3.5 1.7 1.0 3.7 3.6 0.9 0.4 0.1 0.4 0.1 0.2 0.5 0.237 0.275 0.325 0.600 99
Mike Napoli BOS 1B 1B 3.4 6.1 0.9 3.2 3.0 0.8 0.5 0.1 0.5 0.0 0.3 1.0 0.257 0.334 0.480 0.814 87
Josh Willingham KC OF OF 3.4 3.6 1.0 4.0 3.4 0.7 0.5 0.2 0.6 0.0 0.5 0.9 0.194 0.330 0.380 0.710 25
Juan Lagares NYN OF OF 3.1 4.3 0.7 3.2 3.0 0.8 0.4 0.0 0.3 0.2 0.1 0.6 0.279 0.314 0.389 0.703 23
Ben Zobrist TB 2B, SS, OF 2B, SS, OF 2.9 0.7 1.0 4.6 4.2 1.1 0.6 0.0 0.4 0.0 0.4 0.8 0.273 0.366 0.400 0.766 99
Billy Butler KC 1B 1B 2.4 5.4 0.9 3.5 3.2 0.8 0.4 0.1 0.5 0.0 0.3 0.5 0.257 0.343 0.400 0.743 68
Kelly Johnson BAL 1B, 2B, 3B, OF 1B, 2B, 3B, OF 2.1 1.2 0.5 2.1 1.9 0.4 0.2 0.1 0.2 0.0 0.2 0.5 0.211 0.300 0.386 0.686 10
Welington Castillo CHN C C 2.1 0.7 0.8 2.6 2.5 0.6 0.3 0.2 0.3 0.0 0.2 0.8 0.242 0.286 0.373 0.659 1
Alex Rios TEX OF OF 2.0 3.8 0.9 3.5 3.3 0.9 0.4 0.0 0.4 0.2 0.1 0.6 0.270 0.302 0.377 0.679 70
Rajai Davis DET OF OF 1.9 3.2 0.8 2.8 2.6 0.7 0.4 0.0 0.3 0.2 0.1 0.4 0.257 0.296 0.355 0.651 96
Jay Bruce CIN OF OF 1.6 1.8 0.9 3.3 3.0 0.8 0.4 0.1 0.4 0.0 0.3 1.0 0.265 0.336 0.469 0.805 83
Michael Saunders SEA OF OF 1.5 1.5 0.5 2.1 1.8 0.5 0.4 0.0 0.3 0.0 0.2 0.5 0.278 0.392 0.506 0.898 7
Will Venable SD OF OF 1.4 2.2 0.7 3.0 2.8 0.7 0.3 0.1 0.3 0.1 0.1 0.8 0.256 0.314 0.372 0.686 44
Josh Harrison PIT 2B, 3B, OF 2B, SS, 3B, OF 1.3 0.5 0.9 3.8 3.7 0.9 0.5 0.0 0.3 0.2 0.1 0.6 0.244 0.265 0.357 0.622 100
Brandon Guyer TB OF OF 1.3 1.4 0.9 4.1 3.9 1.1 0.5 0.0 0.5 0.0 0.2 0.8 0.279 0.333 0.390 0.723 0
Jimmy Paredes BAL 3B, OF 3B, OF 1.3 0.3 0.4 1.5 1.5 0.4 0.2 0.0 0.2 0.1 0.0 0.3 0.250 0.269 0.364 0.633 12
Christian Yelich MIA OF OF 1.1 2.3 1.0 3.8 3.6 0.9 0.4 0.1 0.4 0.1 0.2 0.8 0.237 0.282 0.364 0.646 100
Brandon Phillips CIN 2B 2B 1.1 -0.8 0.9 3.5 3.3 0.9 0.4 0.1 0.4 0.0 0.2 0.6 0.278 0.318 0.392 0.710 76
Alex Avila DET C C 1.0 -0.6 0.8 2.9 2.6 0.6 0.4 0.1 0.3 0.0 0.2 0.7 0.235 0.330 0.369 0.699 1
Chris Taylor SEA SS SS 0.7 1.0 0.3 1.1 1.0 0.3 0.1 0.0 0.1 0.1 0.1 0.3 0.286 0.371 0.417 0.788 1
Mark Reynolds MIL 1B, 3B 1B, 3B 0.6 0.7 0.2 0.9 0.8 0.2 0.1 0.1 0.2 0.0 0.1 0.3 0.265 0.356 0.492 0.848 27
Justin Turner LAN 2B, SS, 3B 1B, 2B, SS, 3B 0.5 0.2 0.4 1.6 1.6 0.5 0.2 0.0 0.2 0.0 0.1 0.2 0.300 0.335 0.412 0.747 35
Chris Young NYA OF OF 0.5 0.6 0.7 2.9 2.7 0.6 0.5 0.0 0.5 0.0 0.2 0.6 0.237 0.307 0.405 0.712 65
Robbie Grossman HOU OF OF 0.5 1.9 0.8 3.6 3.4 0.9 0.4 0.0 0.4 0.2 0.2 0.9 0.256 0.317 0.358 0.675 5
Jarrod Dyson KC OF OF 0.5 0.8 0.3 1.1 1.0 0.2 0.1 0.0 0.1 0.1 0.1 0.2 0.222 0.310 0.327 0.637 37
Delmon Young BAL OF OF 0.5 0.5 0.3 1.0 0.9 0.2 0.1 0.0 0.2 0.0 0.0 0.2 0.250 0.291 0.410 0.701 0
Chris Heisey CIN OF OF 0.4 0.4 0.3 1.1 1.1 0.3 0.2 0.0 0.2 0.0 0.1 0.3 0.237 0.295 0.400 0.695 2
Endy Chavez SEA OF OF 0.4 0.5 0.6 2.0 1.8 0.6 0.4 0.0 0.3 0.0 0.1 0.3 0.303 0.359 0.422 0.781 0
Brock Holt BOS 2B, SS, 3B, OF 1B,3B,OF 0.3 0.1 0.3 1.3 1.2 0.3 0.1 0.0 0.2 0.0 0.0 0.1 0.286 0.319 0.400 0.719 49
Will Middlebrooks BOS 3B 3B 0.2 0.8 0.6 2.3 2.2 0.6 0.4 0.0 0.4 0.0 0.1 0.7 0.250 0.276 0.442 0.718 24
Eric Young NYN OF OF 0.1 0.3 0.3 1.1 1.0 0.3 0.1 0.0 0.1 0.1 0.1 0.3 0.250 0.327 0.347 0.674 33
Ezequiel Carrera DET OF OF 0.1 0.2 0.2 0.6 0.6 0.2 0.1 0.0 0.1 0.1 0.0 0.1 0.270 0.317 0.345 0.662 0
Rafael Lopez CHN C C 0.0 0.0 0.1 0.2 0.2 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.222 0.288 0.348 0.636 0
Scott Van Slyke LAN 1B, OF 1B, OF 0.0 0.0 0.1 0.2 0.2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.267 0.325 0.446 0.771 1
Jeff Kobernus WAS OF OF 0.0 0.0 0.1 0.2 0.2 0.1 0.0 0.0 0.0 0.0 0.0 0.0 0.286 0.322 0.355 0.677 0
Dan Johnson TOR 1B 1B 0.0 0.0 0.1 0.2 0.2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.229 0.319 0.421 0.740 0
Daniel Butler BOS C C 0.0 0.0 0.1 0.2 0.2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.250 0.286 0.391 0.677 0
Jesus Guzman HOU 1B, OF 1B, OF 0.0 0.0 0.1 0.2 0.2 0.1 0.0 0.0 0.0 0.0 0.0 0.1 0.238 0.293 0.386 0.679 0
Brent Morel PIT 3B 3B 0.0 0.0 0.1 0.2 0.2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.189 0.241 0.285 0.526 0
Tony Campana LAA OF OF 0.0 0.0 0.1 0.2 0.2 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.205 0.232 0.240 0.472 0
Andy Parrino OAK SS 2B, SS 0.0 0.0 0.1 0.2 0.2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.250 0.309 0.369 0.678 0
Jordan Pacheco ARI C,1B C, 1B 0.0 0.0 0.1 0.2 0.2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.250 0.261 0.314 0.575 0
Ryan Raburn CLE OF OF 0.0 0.0 0.1 0.2 0.2 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.242 0.282 0.342 0.624 0
Elian Herrera MIL SS, 3B, OF 2B, SS, 3B, OF 0.0 0.0 0.1 0.3 0.3 0.1 0.0 0.0 0.0 0.0 0.0 0.1 0.286 0.341 0.376 0.717 0
Eric Campbell NYN 1B, 3B, OF 1B, 3B, OF 0.0 0.0 0.1 0.2 0.2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.250 0.335 0.371 0.706 0
Jesus Aguilar CLE 1B 1B 0.0 0.0 0.1 0.2 0.2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.242 0.297 0.336 0.633 0
Michael Taylor WAS OF OF 0.0 0.0 0.1 0.2 0.2 0.1 0.0 0.0 0.0 0.0 0.0 0.1 0.250 0.297 0.364 0.661 1
Juan Centeno NYN C C 0.0 0.0 0.1 0.2 0.2 0.1 0.0 0.0 0.0 0.0 0.0 0.0 0.250 0.312 0.340 0.652 0
Jayson Nix KC 2B, SS, 3B 2B, SS, 3B 0.0 0.0 0.1 0.2 0.2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.188 0.276 0.307 0.583 0
Scott Hairston WAS OF OF 0.0 0.0 0.1 0.2 0.2 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.265 0.289 0.406 0.695 0
Steven Souza WAS OF OF 0.0 0.0 0.1 0.2 0.2 0.1 0.0 0.0 0.0 0.0 0.0 0.1 0.282 0.340 0.439 0.779 0
George Kottaras TOR C C 0.0 0.0 0.1 0.2 0.2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.200 0.296 0.404 0.700 0
Nate Freiman OAK 1B 1B 0.0 0.0 0.1 0.2 0.1 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.241 0.299 0.423 0.722 0
Stefen Romero SEA OF OF 0.0 0.0 0.1 0.2 0.2 0.1 0.0 0.0 0.0 0.0 0.0 0.0 0.278 0.335 0.461 0.796 0
Nick Franklin TB 2B 2B, SS 0.0 0.0 0.1 0.2 0.2 0.1 0.0 0.0 0.0 0.0 0.0 0.0 0.250 0.316 0.338 0.654 5
Chris Denorfia SEA OF OF 0.0 0.0 0.1 0.2 0.2 0.1 0.0 0.0 0.0 0.0 0.0 0.0 0.294 0.362 0.438 0.800 1
Hector Gomez MIL SS SS, 3B 0.0 0.0 0.1 0.3 0.3 0.1 0.1 0.0 0.0 0.0 0.0 0.1 0.250 0.294 0.389 0.683 0
A.J. Pierzynski STL C C 0.0 0.0 0.1 0.2 0.2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.265 0.280 0.418 0.698 14
Jason Rogers MIL 3B 3B 0.0 0.0 0.1 0.2 0.2 0.1 0.0 0.0 0.0 0.0 0.0 0.0 0.286 0.344 0.435 0.779 0
Nick Ahmed ARI SS SS 0.0 0.0 0.1 0.2 0.2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.231 0.255 0.308 0.563 0
Raul Ibanez KC OF 1B, OF 0.0 0.0 0.1 0.3 0.3 0.1 0.0 0.0 0.0 0.0 0.0 0.0 0.226 0.304 0.387 0.691 2
Bobby Wilson ARI C C 0.0 0.0 0.1 0.2 0.2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.226 0.251 0.305 0.556 0
Grant Green LAA 2B, OF 2B, 3B, OF 0.0 0.0 0.1 0.2 0.2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.226 0.238 0.287 0.525 1
Tyler Collins DET OF OF 0.0 0.0 0.1 0.2 0.2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.250 0.299 0.371 0.670 0
Hernan Perez DET 2B 2B 0.0 0.0 0.1 0.2 0.2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.242 0.278 0.326 0.604 0
Adam Moore SD C C 0.0 0.0 0.1 0.2 0.2 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.205 0.264 0.317 0.581 0
Carlos Rivero BOS SS SS 0.0 0.0 0.1 0.2 0.2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.243 0.281 0.386 0.667 0
Sandy Leon WAS C C 0.0 0.0 0.1 0.2 0.2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.235 0.303 0.333 0.636 0
Ryan Lavarnway BOS C C, 1B 0.0 0.0 0.1 0.2 0.2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.250 0.308 0.424 0.732 0
James McCann DET C C 0.0 0.0 0.1 0.2 0.2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.243 0.274 0.325 0.599 0
Nick Punto OAK 2B, SS, 3B 2B, SS, 3B 0.0 0.0 0.1 0.2 0.2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.226 0.318 0.339 0.657 0
Darwin Barney LAN 2B 2B 0.0 0.0 0.1 0.2 0.2 0.1 0.0 0.0 0.0 0.0 0.0 0.0 0.250 0.291 0.345 0.636 0
Logan Schafer MIL OF OF 0.0 0.0 0.1 0.4 0.4 0.1 0.0 0.0 0.1 0.0 0.0 0.1 0.275 0.350 0.420 0.770 0
Erik Kratz KC C C 0.0 0.0 0.1 0.2 0.2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.219 0.290 0.372 0.662 0
Tim Federowicz LAN C C 0.0 0.0 0.1 0.2 0.2 0.1 0.0 0.0 0.0 0.0 0.0 0.0 0.265 0.286 0.384 0.670 0
David Murphy CLE OF OF 0.0 0.1 0.8 2.7 2.5 0.7 0.3 0.1 0.3 0.0 0.2 0.4 0.281 0.334 0.405 0.739 20
Martin Maldonado MIL C C, 1B 0.0 0.0 0.1 0.3 0.3 0.1 0.1 0.0 0.0 0.0 0.0 0.1 0.257 0.325 0.399 0.724 0
Rickie Weeks MIL 2B 2B 0.0 0.0 0.1 0.2 0.2 0.1 0.0 0.0 0.0 0.0 0.0 0.1 0.289 0.366 0.452 0.818 4
Justin Smoak SEA 1B 1B 0.0 0.0 0.1 0.2 0.2 0.1 0.0 0.0 0.0 0.0 0.0 0.1 0.265 0.383 0.480 0.863 18
Jose Tabata PIT OF OF 0.0 0.0 0.1 0.2 0.2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.233 0.275 0.318 0.593 0
Austin Romine NYA C C 0.0 -0.1 0.1 0.3 0.3 0.1 0.0 0.0 0.0 0.0 0.0 0.0 0.242 0.285 0.347 0.632 0
Jonny Gomes OAK OF OF -0.1 0.0 0.1 0.1 0.1 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.200 0.308 0.396 0.704 2
Adam Duvall SF 1B 1B -0.1 -0.1 0.1 0.4 0.3 0.1 0.0 0.0 0.0 0.0 0.0 0.1 0.242 0.279 0.411 0.690 0
Steve Tolleson TOR 2B, 3B 2B, 3B, OF -0.1 -0.1 0.1 0.2 0.2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.219 0.286 0.354 0.640 0
Matt McBride COL OF 1B -0.1 -0.1 0.1 0.2 0.2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.194 0.230 0.303 0.533 1
Xavier Scruggs STL 1B 1B -0.1 -0.1 0.1 0.4 0.3 0.1 0.1 0.0 0.0 0.0 0.0 0.1 0.235 0.295 0.406 0.701 0
Tony Gwynn PHI OF OF -0.1 -0.1 0.1 0.3 0.3 0.1 0.0 0.0 0.0 0.0 0.0 0.0 0.242 0.287 0.306 0.593 0
Cesar Hernandez PHI 2B, 3B, OF 2B, 3B, OF -0.1 -0.1 0.1 0.3 0.3 0.1 0.0 0.0 0.0 0.0 0.0 0.1 0.265 0.309 0.366 0.675 0
Ed Lucas MIA 1B, 2B, SS, 3B 1B, 2B, SS, 3B, OF -0.1 -0.1 0.1 0.2 0.2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.200 0.231 0.282 0.513 0
Max Stassi HOU C C -0.1 -0.2 0.1 0.5 0.4 0.1 0.1 0.0 0.0 0.0 0.0 0.1 0.225 0.253 0.355 0.608 0
Ramiro Pena ATL 2B, SS, 3B 2B, SS, 3B -0.1 -0.1 0.1 0.2 0.2 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.206 0.231 0.272 0.503 0
Danny Espinosa WAS 2B, SS 2B, SS -0.1 -0.2 0.2 0.8 0.7 0.2 0.1 0.0 0.1 0.0 0.0 0.3 0.237 0.296 0.376 0.672 6
Cameron Rupp PHI C C -0.1 -0.1 0.1 0.2 0.2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.235 0.281 0.382 0.663 0
JR Murphy NYA C C -0.1 -0.1 0.1 0.5 0.5 0.1 0.1 0.0 0.1 0.0 0.0 0.1 0.237 0.284 0.363 0.647 0
Craig Gentry OAK OF OF -0.1 -0.1 0.1 0.2 0.2 0.1 0.0 0.0 0.0 0.0 0.0 0.0 0.243 0.310 0.347 0.657 0
John Mayberry TOR 1B, OF 1B, OF -0.1 -0.1 0.1 0.2 0.2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.222 0.280 0.394 0.674 0
Leury Garcia CHA 2B, 3B, OF 2B, SS, 3B, OF -0.1 -0.1 0.1 0.2 0.2 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.194 0.237 0.251 0.488 0
Luis Jimenez LAA 3B 3B -0.1 -0.1 0.1 0.2 0.2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.194 0.216 0.281 0.497 0
Guilder Rodriguez TEX SS SS -0.1 -0.1 0.1 0.2 0.2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.235 0.302 0.267 0.569 0
Mark Ellis STL 2B 2B -0.1 0.0 0.1 0.2 0.2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.242 0.293 0.351 0.644 0
Chris Gimenez CLE C,1B C, 1B -0.1 -0.1 0.1 0.2 0.2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.219 0.298 0.298 0.596 0
Carlos Corporan HOU C C -0.1 -0.1 0.1 0.5 0.4 0.1 0.1 0.0 0.0 0.0 0.0 0.1 0.231 0.281 0.384 0.665 0
Tyler Holt CLE OF OF -0.1 -0.1 0.1 0.4 0.3 0.1 0.0 0.0 0.0 0.0 0.0 0.1 0.226 0.295 0.272 0.567 0
Jeff Baker MIA 1B, 2B, OF 1B, 2B, 3B, OF -0.1 -0.1 0.1 0.2 0.2 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.200 0.232 0.318 0.550 0
Alexi Casilla BAL 2B 2B -0.1 0.0 0.1 0.2 0.2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.216 0.274 0.313 0.587 0
Junior Lake CHN OF OF -0.1 -0.1 0.1 0.2 0.2 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.219 0.263 0.358 0.621 17
Brett Jackson ARI OF OF -0.1 -0.1 0.1 0.2 0.2 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.226 0.267 0.356 0.623 0
Moises Sierra CHA OF OF -0.1 0.0 0.1 0.2 0.2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.194 0.265 0.314 0.579 0
Tyler Moore WAS 1B, OF 1B, OF -0.1 -0.1 0.1 0.4 0.4 0.1 0.0 0.0 0.0 0.0 0.0 0.1 0.282 0.318 0.442 0.760 0
Jake Elmore CIN SS 2B, SS, OF -0.1 -0.1 0.1 0.3 0.3 0.1 0.0 0.0 0.0 0.0 0.0 0.0 0.242 0.324 0.323 0.647 0
Travis Ishikawa SF 1B 1B, OF -0.1 0.0 0.1 0.2 0.2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.216 0.274 0.318 0.592 0
Eury Perez NYA OF OF -0.1 -0.1 0.1 0.3 0.3 0.1 0.0 0.0 0.0 0.0 0.0 0.0 0.282 0.301 0.351 0.652 0
Eric Fryer MIN C C -0.1 -0.2 0.1 0.3 0.3 0.1 0.0 0.0 0.0 0.0 0.0 0.1 0.200 0.244 0.294 0.538 0
Kevin Frandsen WAS 1B, 2B, 3B, OF 1B, 2B, 3B, OF -0.1 -0.2 0.2 0.8 0.7 0.2 0.1 0.0 0.1 0.0 0.0 0.1 0.308 0.327 0.376 0.703 0
Steve Clevenger BAL C C -0.1 -0.2 0.1 0.4 0.4 0.1 0.0 0.0 0.0 0.0 0.0 0.0 0.250 0.302 0.358 0.660 0
J.T. Realmuto MIA C C -0.1 -0.1 0.1 0.2 0.2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.205 0.233 0.295 0.528 0
Miguel Rojas LAN SS, 3B SS, 3B -0.1 -0.1 0.1 0.2 0.2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.225 0.272 0.309 0.581 0
Kyle Parker COL OF OF -0.1 -0.1 0.1 0.2 0.2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.205 0.227 0.278 0.505 0
Tony Cruz STL C C -0.1 -0.1 0.1 0.2 0.2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.237 0.271 0.351 0.622 0
Nolan Reimold ARI OF OF -0.2 -0.2 0.1 0.3 0.3 0.1 0.0 0.0 0.0 0.0 0.0 0.1 0.206 0.263 0.353 0.616 0
Donald Lutz CIN OF 1B, OF -0.2 -0.2 0.1 0.4 0.4 0.1 0.0 0.0 0.1 0.0 0.0 0.2 0.229 0.287 0.388 0.675 0
Cristhian Adames COL SS SS -0.2 -0.2 0.1 0.4 0.4 0.1 0.0 0.0 0.0 0.0 0.0 0.1 0.205 0.238 0.259 0.497 0
Tommy Medica SD 1B, OF 1B, OF -0.2 -0.2 0.1 0.4 0.3 0.1 0.0 0.0 0.0 0.0 0.0 0.1 0.226 0.276 0.362 0.638 6
Jordany Valdespin MIA 2B, OF 2B, OF -0.2 -0.2 0.1 0.3 0.3 0.1 0.0 0.0 0.0 0.0 0.0 0.0 0.233 0.259 0.362 0.621 0
Jesus Sucre SEA C C -0.2 -0.2 0.1 0.4 0.3 0.1 0.1 0.0 0.0 0.0 0.0 0.1 0.258 0.310 0.368 0.678 0
Doug Bernier MIN SS SS, 3B -0.2 -0.2 0.1 0.3 0.3 0.1 0.0 0.0 0.0 0.0 0.0 0.1 0.233 0.254 0.301 0.555 0
Michael Taylor CHA OF OF -0.2 -0.2 0.1 0.4 0.3 0.1 0.0 0.0 0.0 0.0 0.0 0.1 0.212 0.294 0.325 0.619 1
Matt Dominguez HOU 3B 3B -0.2 1.3 0.9 3.5 3.4 0.8 0.4 0.2 0.4 0.0 0.1 0.7 0.237 0.267 0.393 0.660 14
Evan Longoria TB 3B 3B -0.2 1.0 1.0 4.2 3.8 1.0 0.5 0.0 0.4 0.0 0.3 0.9 0.275 0.374 0.487 0.861 100
Jim Adduci TEX OF OF -0.2 -0.2 0.1 0.4 0.4 0.1 0.0 0.0 0.1 0.0 0.0 0.1 0.250 0.318 0.338 0.656 1
Cory Spangenberg SD 2B 3B -0.2 -0.5 0.6 2.6 2.4 0.7 0.2 0.0 0.1 0.2 0.1 0.5 0.275 0.305 0.328 0.633 1
Andres Blanco PHI 3B 2B, SS, 3B -0.2 -0.1 0.1 0.3 0.3 0.1 0.0 0.0 0.0 0.0 0.0 0.0 0.235 0.289 0.364 0.653 0
Joc Pederson LAN OF OF -0.2 -0.2 0.2 0.7 0.7 0.2 0.1 0.0 0.1 0.0 0.1 0.2 0.268 0.341 0.448 0.789 14
Gary Brown SF OF OF -0.2 -0.2 0.1 0.4 0.4 0.1 0.1 0.0 0.0 0.0 0.0 0.1 0.237 0.279 0.352 0.631 0
James Jones SEA OF OF -0.2 -0.2 0.2 0.7 0.6 0.2 0.1 0.0 0.1 0.0 0.0 0.2 0.278 0.345 0.412 0.757 11
Carlos Peguero KC OF OF -0.2 -0.1 0.1 0.3 0.3 0.1 0.0 0.0 0.0 0.0 0.0 0.1 0.219 0.301 0.408 0.709 0
Paul Konerko CHA 1B 1B -0.3 -0.2 0.1 0.4 0.3 0.1 0.0 0.0 0.0 0.0 0.0 0.1 0.206 0.288 0.334 0.622 1
Christian Walker BAL 1B 1B -0.3 -0.2 0.2 0.5 0.5 0.1 0.1 0.0 0.1 0.0 0.0 0.1 0.242 0.286 0.388 0.674 0
Zelous Wheeler NYA 3B 3B, OF -0.3 -0.3 0.1 0.5 0.4 0.1 0.0 0.0 0.0 0.0 0.0 0.1 0.242 0.305 0.378 0.683 0
Jose Lobaton WAS C C -0.3 -0.6 0.3 1.2 1.1 0.3 0.1 0.0 0.1 0.0 0.1 0.3 0.256 0.322 0.368 0.690 0
Mike Trout LAA OF OF -0.3 0.7 1.0 3.6 3.3 0.8 0.4 0.1 0.4 0.1 0.2 1.1 0.229 0.297 0.395 0.692 100
Nate Schierholtz WAS OF OF -0.3 -0.3 0.2 0.9 0.9 0.2 0.1 0.0 0.1 0.0 0.0 0.2 0.270 0.316 0.443 0.759 8
Matthew Clark MIL 1B 1B -0.3 -0.1 0.3 1.1 1.1 0.3 0.1 0.0 0.2 0.0 0.1 0.3 0.303 0.369 0.553 0.922 0
Tucker Barnhart CIN C C -0.3 -0.4 0.2 0.6 0.6 0.1 0.1 0.0 0.1 0.0 0.0 0.1 0.222 0.297 0.318 0.615 0
Randal Grichuk STL OF OF -0.3 -0.3 0.2 0.6 0.6 0.2 0.1 0.0 0.1 0.0 0.0 0.1 0.256 0.267 0.411 0.678 0
Jose Molina TB C C -0.3 -0.3 0.1 0.5 0.5 0.1 0.1 0.0 0.0 0.0 0.0 0.1 0.229 0.294 0.301 0.595 0
Sam Fuld OAK OF OF -0.3 1.6 0.8 3.4 3.2 0.7 0.4 0.0 0.2 0.2 0.2 0.3 0.237 0.325 0.384 0.709 10
Skip Schumaker CIN 2B, OF 2B, OF -0.3 -0.3 0.2 0.8 0.7 0.2 0.1 0.0 0.1 0.0 0.0 0.2 0.278 0.329 0.349 0.678 0
Shawn O’Malley LAA SS OF -0.3 -0.3 0.1 0.4 0.4 0.1 0.0 0.0 0.0 0.0 0.0 0.1 0.200 0.244 0.254 0.498 0
Alberto Callaspo OAK 1B, 2B, 3B 1B, 2B, 3B -0.4 -0.4 0.2 0.7 0.7 0.2 0.1 0.0 0.1 0.0 0.0 0.0 0.258 0.339 0.395 0.734 1
Yorman Rodriguez CIN OF OF -0.4 -0.4 0.2 0.8 0.7 0.2 0.1 0.0 0.1 0.0 0.0 0.3 0.216 0.273 0.324 0.597 0
Alfredo Marte ARI OF OF -0.4 -0.4 0.2 0.6 0.6 0.1 0.1 0.0 0.1 0.0 0.0 0.2 0.235 0.259 0.339 0.598 0
Jack Hannahan CIN 1B, 3B 1B, 3B -0.4 -0.4 0.2 0.6 0.6 0.1 0.1 0.0 0.1 0.0 0.0 0.1 0.229 0.309 0.344 0.653 0
Tuffy Gosewisch ARI C C -0.4 -0.5 0.2 0.7 0.6 0.1 0.1 0.0 0.1 0.0 0.0 0.1 0.222 0.234 0.305 0.539 0
Pete Kozma STL SS 2B, SS -0.4 -0.4 0.1 0.4 0.3 0.1 0.0 0.0 0.0 0.0 0.0 0.1 0.235 0.279 0.346 0.625 0
J.B. Shuck CLE OF OF -0.5 -0.4 0.2 0.8 0.7 0.2 0.1 0.0 0.1 0.0 0.0 0.1 0.273 0.326 0.344 0.670 0
Daniel Robertson TEX OF OF -0.5 -0.5 0.2 0.7 0.6 0.2 0.1 0.0 0.1 0.0 0.0 0.1 0.250 0.308 0.306 0.614 0
Adrian Nieto CHA C C -0.5 -0.6 0.2 0.5 0.5 0.1 0.0 0.0 0.0 0.0 0.0 0.2 0.200 0.256 0.274 0.530 0
Chris Stewart PIT C C -0.5 -0.6 0.1 0.5 0.4 0.1 0.1 0.0 0.0 0.0 0.0 0.1 0.194 0.251 0.263 0.514 0
Jason Bourgeois CIN OF OF -0.5 -0.5 0.2 0.8 0.7 0.2 0.1 0.0 0.1 0.0 0.0 0.1 0.270 0.307 0.339 0.646 0
Gaby Sanchez PIT 1B 1B -0.5 -0.5 0.1 0.4 0.4 0.1 0.0 0.0 0.0 0.0 0.0 0.1 0.214 0.265 0.320 0.585 0
Ryan Doumit ATL C, OF C, OF -0.5 -0.6 0.1 0.5 0.5 0.1 0.0 0.0 0.0 0.0 0.0 0.2 0.200 0.236 0.314 0.550 0
Tommy La Stella ATL 2B 2B -0.5 -0.5 0.1 0.5 0.5 0.1 0.0 0.0 0.0 0.0 0.0 0.0 0.212 0.262 0.283 0.545 19
Gregory Polanco PIT OF OF -0.5 0.4 0.9 3.3 3.1 0.7 0.4 0.1 0.3 0.1 0.2 0.6 0.216 0.266 0.330 0.596 38
Stephen Drew NYA 2B, SS 2B, SS -0.5 -2.7 0.8 2.6 2.4 0.5 0.4 0.1 0.3 0.0 0.2 0.6 0.219 0.309 0.362 0.671 4
Clint Barmes PIT 2B, SS 2B, SS -0.6 -0.6 0.1 0.5 0.4 0.1 0.0 0.0 0.0 0.0 0.0 0.1 0.188 0.230 0.273 0.503 0
Travis Snider PIT OF OF -0.6 -0.5 0.6 2.2 2.1 0.4 0.2 0.1 0.3 0.0 0.1 0.5 0.212 0.277 0.366 0.643 21
David Ross BOS C C -0.6 -0.6 0.2 0.7 0.6 0.2 0.1 0.0 0.1 0.0 0.0 0.2 0.235 0.273 0.404 0.677 0
Peter Bourjos STL OF OF -0.6 0.5 0.8 2.9 2.8 0.7 0.4 0.0 0.4 0.1 0.1 0.6 0.257 0.291 0.398 0.689 5
Yan Gomes CLE C C -0.6 -2.3 0.8 3.4 3.2 0.8 0.3 0.1 0.3 0.0 0.2 1.0 0.256 0.297 0.390 0.687 94
Russell Martin PIT C C -0.6 -2.5 0.9 3.1 2.9 0.6 0.3 0.2 0.4 0.0 0.3 0.7 0.206 0.282 0.321 0.603 79
Mark Teixeira NYA 1B 1B -0.6 1.4 0.8 3.2 2.8 0.6 0.4 0.1 0.4 0.0 0.2 0.7 0.222 0.324 0.424 0.748 71
David Lough BAL OF OF -0.6 -0.2 0.5 2.0 1.9 0.5 0.3 0.0 0.2 0.1 0.1 0.3 0.263 0.292 0.377 0.669 1
Derek Jeter NYA SS SS -0.6 -1.8 0.9 3.6 3.4 1.0 0.5 0.0 0.4 0.0 0.2 0.5 0.282 0.320 0.351 0.671 21
Daniel Nava BOS 1B, OF 1B, OF -0.6 -0.4 0.9 3.4 3.2 0.9 0.6 0.0 0.4 0.0 0.2 0.7 0.278 0.343 0.432 0.775 7
Marc Krauss HOU 1B, OF 1B, OF -0.7 -0.7 0.2 0.8 0.7 0.2 0.1 0.0 0.1 0.0 0.0 0.2 0.235 0.303 0.406 0.709 0
Brandon Barnes COL OF OF -0.7 -0.7 0.2 0.5 0.5 0.1 0.0 0.0 0.0 0.0 0.0 0.2 0.171 0.213 0.261 0.474 2
Matt Duffy SF 2B 2B, SS -0.7 -0.7 0.2 0.8 0.8 0.2 0.1 0.0 0.0 0.0 0.0 0.2 0.263 0.304 0.352 0.656 0
Francisco Cervelli NYA C C, 1B -0.8 -1.0 0.3 1.1 1.0 0.2 0.1 0.0 0.1 0.0 0.1 0.3 0.235 0.312 0.339 0.651 1
Don Kelly DET 1B, 3B, OF 1B, 3B, OF -0.8 -0.8 0.3 0.9 0.8 0.2 0.1 0.0 0.1 0.0 0.1 0.1 0.242 0.313 0.336 0.649 0
Jemile Weeks BOS 2B 2B -0.8 -0.8 0.2 0.9 0.8 0.2 0.1 0.0 0.1 0.0 0.0 0.1 0.265 0.324 0.395 0.719 0
Chase Headley NYA 3B 1B, 3B -0.9 0.1 0.8 2.9 2.7 0.7 0.4 0.1 0.4 0.0 0.2 0.7 0.265 0.346 0.402 0.748 77
Matt Szczur CHN OF OF -0.9 -0.9 0.2 0.7 0.7 0.2 0.1 0.0 0.1 0.0 0.0 0.1 0.242 0.278 0.322 0.600 0
Daniel Descalso STL 2B, SS, 3B 2B, SS, 3B -0.9 -1.0 0.3 1.1 1.0 0.2 0.1 0.0 0.1 0.0 0.1 0.2 0.235 0.298 0.377 0.675 0
Jedd Gyorko SD 2B 2B, 3B -0.9 -2.3 0.8 3.7 3.4 0.8 0.3 0.1 0.4 0.0 0.2 0.9 0.244 0.292 0.383 0.675 77
Juan Perez SF OF OF -0.9 -0.9 0.3 1.0 1.0 0.2 0.1 0.0 0.1 0.0 0.0 0.3 0.242 0.282 0.378 0.660 0
Ichiro Suzuki NYA OF OF -0.9 0.1 0.7 2.6 2.5 0.7 0.2 0.0 0.2 0.1 0.1 0.3 0.286 0.314 0.345 0.659 0
Jason Giambi CLE DH DH -1.0 -0.9 0.2 0.8 0.7 0.2 0.1 0.0 0.1 0.0 0.1 0.2 0.219 0.314 0.363 0.677 0
Grady Sizemore PHI OF OF -1.0 -1.0 0.3 1.1 1.1 0.2 0.1 0.0 0.1 0.0 0.1 0.1 0.231 0.290 0.367 0.657 6
Ben Paulsen COL 1B 1B -1.1 -1.1 0.2 0.6 0.6 0.1 0.0 0.0 0.1 0.0 0.0 0.2 0.200 0.242 0.326 0.568 1
Abraham Almonte SD OF OF -1.1 -1.1 0.3 1.1 1.0 0.3 0.1 0.0 0.1 0.0 0.1 0.3 0.243 0.298 0.324 0.622 2
Curt Casali TB C C -1.1 -1.2 0.3 0.9 0.9 0.2 0.1 0.0 0.0 0.0 0.1 0.2 0.235 0.320 0.330 0.650 0
Drew Butera LAN C C -1.1 -1.1 0.2 0.6 0.6 0.1 0.0 0.0 0.0 0.0 0.0 0.1 0.206 0.254 0.313 0.567 0
J.P. Arencibia TEX C,1B C, 1B -1.2 -1.3 0.2 0.9 0.9 0.2 0.1 0.0 0.1 0.0 0.0 0.2 0.222 0.257 0.366 0.623 7
Reed Johnson MIA OF OF -1.2 -1.2 0.2 0.7 0.7 0.2 0.1 0.0 0.1 0.0 0.0 0.2 0.219 0.234 0.306 0.540 0
Robinson Chirinos TEX C C -1.2 -1.5 0.4 1.3 1.2 0.3 0.2 0.0 0.1 0.0 0.1 0.2 0.229 0.290 0.346 0.636 2
Neil Walker PIT 2B 2B -1.3 -3.3 1.0 3.7 3.5 0.8 0.4 0.1 0.5 0.0 0.2 0.8 0.216 0.290 0.385 0.675 100
Drew Stubbs COL OF OF -1.3 -1.1 0.4 1.4 1.3 0.2 0.2 0.0 0.1 0.1 0.1 0.5 0.189 0.232 0.272 0.504 71
Josh Thole TOR C C -1.3 -1.4 0.3 0.9 0.8 0.2 0.1 0.0 0.1 0.0 0.1 0.1 0.258 0.307 0.369 0.676 0
Charlie Culberson COL 2B, SS, 3B, OF 2B, SS, 3B, OF -1.3 -1.3 0.2 0.6 0.6 0.1 0.0 0.0 0.0 0.0 0.0 0.2 0.194 0.213 0.259 0.472 1
Stephen Vogt OAK C, 1B, OF C, 1B, OF -1.4 -2.2 0.6 1.9 1.8 0.5 0.2 0.0 0.2 0.0 0.1 0.2 0.273 0.331 0.481 0.812 35
Kevin Kiermaier TB OF OF -1.4 -1.4 0.4 1.6 1.5 0.4 0.2 0.0 0.2 0.0 0.1 0.4 0.256 0.314 0.371 0.685 14
Andrew Lambo PIT OF OF -1.4 -1.4 0.3 0.9 0.9 0.2 0.1 0.0 0.1 0.0 0.0 0.2 0.212 0.260 0.368 0.628 0
Mike Olt CHN 1B, 3B 1B, 3B -1.5 -1.5 0.3 0.9 0.9 0.2 0.1 0.0 0.1 0.0 0.1 0.5 0.200 0.262 0.352 0.614 11
Dalton Pompey TOR OF OF -1.5 -1.5 0.3 1.0 0.9 0.2 0.1 0.0 0.0 0.0 0.1 0.2 0.222 0.282 0.370 0.652 0
Dioner Navarro TOR C C -1.5 -3.0 0.7 2.7 2.5 0.6 0.4 0.0 0.4 0.0 0.1 0.4 0.250 0.297 0.399 0.696 33
Lyle Overbay MIL 1B 1B -1.5 -1.1 0.5 1.8 1.7 0.5 0.2 0.0 0.2 0.0 0.2 0.4 0.273 0.366 0.457 0.823 0
Elvis Andrus TEX SS SS -1.6 0.0 0.9 3.7 3.4 0.9 0.4 0.0 0.3 0.2 0.2 0.5 0.256 0.319 0.318 0.637 93
Zach Walters CLE 3B OF -1.6 -1.6 0.3 1.0 1.0 0.2 0.1 0.0 0.1 0.0 0.0 0.3 0.235 0.279 0.428 0.707 4
Chris Parmelee MIN 1B, OF 1B, OF -1.6 -1.6 0.3 0.9 0.9 0.2 0.1 0.0 0.1 0.0 0.0 0.0 0.206 0.241 0.287 0.528 1
Garin Cecchini BOS 3B 3B -1.7 -1.4 0.5 1.9 1.8 0.5 0.2 0.0 0.3 0.0 0.1 0.5 0.278 0.322 0.411 0.733 0
Jake Goebbert SD 1B 1B, OF -1.7 -1.5 0.3 1.2 1.1 0.3 0.1 0.0 0.1 0.0 0.1 0.3 0.242 0.321 0.347 0.668 0
John Baker CHN C C -1.7 -1.9 0.3 1.1 1.0 0.2 0.1 0.0 0.1 0.0 0.1 0.3 0.200 0.265 0.296 0.561 0
Matt Carpenter STL 2B, 3B 2B, 3B -1.7 -2.2 0.9 3.8 3.6 1.0 0.5 0.0 0.3 0.0 0.3 0.6 0.286 0.355 0.445 0.800 99
Wil Nieves PHI C C -1.7 -1.9 0.4 1.2 1.1 0.3 0.1 0.0 0.1 0.0 0.0 0.2 0.258 0.285 0.373 0.658 0
Mark Trumbo ARI 1B, OF 1B, OF -1.8 -1.7 1.0 3.6 3.5 0.9 0.4 0.1 0.5 0.0 0.1 1.0 0.243 0.273 0.430 0.703 99
Jon Singleton HOU 1B 1B -1.8 1.1 0.9 3.1 2.9 0.7 0.3 0.2 0.4 0.0 0.3 0.9 0.235 0.308 0.397 0.705 38
Ramon Santiago CIN 2B, SS, 3B 2B, SS, 3B -1.8 -1.8 0.3 1.0 1.0 0.2 0.1 0.0 0.1 0.0 0.1 0.3 0.235 0.318 0.321 0.639 0
Wilmer Flores NYN 2B, SS, 3B 2B, SS, 3B -1.9 -3.2 0.9 3.9 3.7 1.0 0.5 0.0 0.5 0.0 0.2 0.6 0.268 0.308 0.418 0.726 73
Yasmani Grandal SD C,1B C, 1B -1.9 -4.1 0.9 4.1 3.8 0.9 0.4 0.1 0.4 0.0 0.4 1.0 0.250 0.340 0.372 0.712 12
Anthony Recker NYN C C -1.9 -2.7 0.5 2.1 1.9 0.5 0.3 0.0 0.2 0.0 0.2 0.8 0.237 0.295 0.393 0.688 0
Leonys Martin TEX OF OF -1.9 -0.3 1.0 4.1 3.8 1.0 0.4 0.0 0.3 0.2 0.2 0.7 0.275 0.321 0.374 0.695 100
Ryan Kalish CHN OF OF -1.9 -1.9 0.3 0.8 0.7 0.2 0.1 0.0 0.1 0.0 0.0 0.3 0.240 0.277 0.394 0.671 0
Rymer Liriano SD OF OF -1.9 -1.9 0.3 1.2 1.2 0.3 0.1 0.0 0.1 0.0 0.1 0.4 0.229 0.276 0.324 0.600 10
Josh Phegley CHA C C -2.0 -2.2 0.3 1.1 1.0 0.2 0.1 0.0 0.1 0.0 0.1 0.2 0.206 0.259 0.342 0.601 0
Steve Pearce BAL 1B, OF 1B, OF -2.0 -1.9 0.5 2.1 1.9 0.5 0.3 0.0 0.2 0.0 0.2 0.5 0.270 0.328 0.448 0.776 86
Carlos Ruiz PHI C C -2.1 -3.4 0.7 2.9 2.7 0.8 0.3 0.0 0.3 0.0 0.2 0.4 0.289 0.357 0.448 0.805 11
Corey Dickerson COL OF OF -2.2 -1.0 0.9 3.4 3.3 0.7 0.3 0.1 0.4 0.1 0.1 0.7 0.216 0.264 0.388 0.652 100
Roberto Perez CLE C C -2.3 -2.5 0.3 1.0 1.0 0.2 0.1 0.0 0.0 0.0 0.1 0.4 0.206 0.277 0.267 0.544 0
Enrique Hernandez MIA OF SS, OF -2.3 -2.3 0.3 1.0 0.9 0.2 0.1 0.0 0.1 0.0 0.0 0.2 0.226 0.237 0.312 0.549 0
Ruben Tejada NYN SS SS -2.3 -2.5 0.4 1.5 1.4 0.4 0.2 0.0 0.1 0.0 0.1 0.2 0.250 0.333 0.344 0.677 0
Jose Pirela NYA SS SS -2.4 -2.7 0.5 2.0 1.9 0.5 0.2 0.0 0.2 0.0 0.1 0.3 0.263 0.308 0.381 0.689 0
Nick Hundley BAL C C -2.5 -2.7 0.4 1.3 1.3 0.3 0.1 0.0 0.1 0.0 0.0 0.3 0.229 0.277 0.377 0.654 0
Kirk Nieuwenhuis NYN OF OF -2.5 -2.5 0.5 2.2 2.0 0.5 0.2 0.0 0.2 0.0 0.2 0.5 0.250 0.322 0.428 0.750 0
Luis Sardinas TEX 2B, SS 2B, SS, 3B -2.6 -2.9 0.5 1.9 1.9 0.5 0.2 0.0 0.2 0.0 0.1 0.4 0.257 0.291 0.309 0.600 0
Ryan Hanigan TB C C -2.6 -3.7 0.6 2.4 2.2 0.6 0.3 0.0 0.3 0.0 0.3 0.4 0.257 0.357 0.334 0.691 0
Christian Bethancourt ATL C C -2.6 -3.1 0.4 1.5 1.5 0.3 0.2 0.0 0.2 0.0 0.0 0.3 0.200 0.234 0.319 0.553 0
Bryan Holaday DET C C -2.7 -2.8 0.3 1.1 1.0 0.2 0.1 0.0 0.1 0.0 0.0 0.2 0.226 0.272 0.308 0.580 1
Lorenzo Cain KC OF OF -2.7 -1.3 0.9 3.5 3.3 0.8 0.4 0.0 0.4 0.2 0.3 0.7 0.237 0.310 0.351 0.661 93
Andy Wilkins CHA 1B 1B -2.7 -1.1 0.7 2.5 2.2 0.5 0.3 0.1 0.3 0.0 0.1 0.6 0.219 0.276 0.366 0.642 0
Eugenio Suarez DET SS SS -2.8 -3.0 0.4 1.3 1.2 0.3 0.1 0.0 0.1 0.0 0.1 0.2 0.219 0.281 0.319 0.600 2
Collin Cowgill LAA OF OF -3.0 -3.0 0.4 1.2 1.2 0.2 0.1 0.0 0.1 0.0 0.0 0.3 0.182 0.229 0.257 0.486 1
Alex Presley HOU OF OF -3.0 -2.9 0.5 2.0 1.9 0.5 0.2 0.0 0.2 0.0 0.1 0.4 0.278 0.308 0.426 0.734 0
David DeJesus TB OF OF -3.1 -3.0 0.8 3.1 2.9 0.8 0.4 0.0 0.3 0.0 0.2 0.5 0.263 0.326 0.351 0.677 0
Mike Aviles CLE 2B, SS, 3B, OF 2B, SS, 3B, OF -3.1 -3.3 0.4 1.5 1.5 0.4 0.2 0.0 0.1 0.0 0.0 0.3 0.242 0.273 0.322 0.595 8
Cliff Pennington ARI 2B, SS 2B, SS, 3B -3.1 -3.2 0.4 1.3 1.3 0.3 0.1 0.0 0.1 0.0 0.1 0.3 0.229 0.285 0.330 0.615 1
Marcus Semien CHA 2B, 3B 2B, 3B -3.1 -3.2 0.5 1.7 1.5 0.3 0.2 0.0 0.2 0.0 0.1 0.4 0.206 0.281 0.325 0.606 7
Jeff Mathis MIA C C -3.2 -3.3 0.3 0.9 0.8 0.2 0.0 0.0 0.1 0.0 0.0 0.3 0.179 0.197 0.252 0.449 0
Tomas Telis TEX C C -3.2 -4.5 0.7 2.8 2.7 0.7 0.3 0.0 0.3 0.0 0.1 0.3 0.263 0.289 0.331 0.620 0
Chris Dominguez SF 3B OF -3.2 -3.0 0.5 1.8 1.7 0.4 0.2 0.0 0.2 0.0 0.1 0.5 0.235 0.269 0.382 0.651 0
Michael McKenry COL C C -3.3 -3.6 0.4 1.5 1.4 0.3 0.1 0.0 0.1 0.0 0.1 0.4 0.194 0.241 0.291 0.532 2
Jake Smolinski TEX OF OF -3.4 -3.4 0.5 1.8 1.7 0.4 0.2 0.0 0.2 0.0 0.1 0.3 0.250 0.307 0.344 0.651 20
Aaron Hill ARI 2B 2B, 3B -3.4 -5.2 1.0 3.5 3.4 0.9 0.4 0.1 0.4 0.0 0.1 0.7 0.250 0.280 0.383 0.663 65
Nori Aoki KC OF OF -3.5 -2.2 0.9 3.7 3.4 0.9 0.5 0.0 0.3 0.1 0.3 0.2 0.270 0.346 0.370 0.716 83
Bryce Brentz BOS OF OF -3.6 -3.6 0.5 1.9 1.9 0.5 0.2 0.0 0.2 0.0 0.1 0.6 0.243 0.287 0.452 0.739 1
Cody Ross ARI OF OF -3.8 -3.7 0.8 2.6 2.5 0.6 0.2 0.1 0.3 0.0 0.1 0.6 0.242 0.280 0.372 0.652 4
Oscar Taveras STL OF OF -3.8 -3.8 0.6 2.0 1.9 0.5 0.2 0.0 0.2 0.0 0.1 0.2 0.290 0.306 0.448 0.754 61
Matt Joyce TB OF OF -3.9 -3.8 0.8 3.1 2.8 0.7 0.3 0.0 0.3 0.0 0.2 0.9 0.243 0.326 0.377 0.703 35
Andrew Susac SF C C -3.9 -4.8 0.6 2.5 2.3 0.5 0.2 0.0 0.3 0.0 0.2 0.4 0.231 0.309 0.375 0.684 0
Brayan Pena CIN C,1B C, 1B -4.0 -4.5 0.5 2.0 2.0 0.5 0.1 0.0 0.2 0.0 0.1 0.3 0.263 0.305 0.376 0.681 1
Kurt Suzuki MIN C C -4.0 -4.4 0.5 1.7 1.6 0.4 0.1 0.0 0.1 0.0 0.0 0.3 0.222 0.253 0.320 0.573 15
Michael Choice TEX OF OF -4.0 -4.0 0.5 1.6 1.5 0.4 0.1 0.0 0.2 0.0 0.1 0.4 0.250 0.306 0.351 0.657 0
Michael Bourn CLE OF OF -4.0 -2.5 1.0 4.3 4.0 1.0 0.4 0.0 0.3 0.2 0.3 1.1 0.262 0.325 0.360 0.685 56
Garrett Jones MIA 1B, OF 1B, OF -4.0 -3.8 0.8 2.7 2.5 0.5 0.2 0.1 0.4 0.0 0.1 0.6 0.219 0.260 0.392 0.652 32
Andrew Romine DET 2B, SS, 3B 2B, SS, 3B -4.1 -3.2 0.6 1.8 1.7 0.4 0.2 0.0 0.1 0.1 0.1 0.3 0.241 0.285 0.278 0.563 2
Jacob Lamb ARI 3B 3B -4.1 -3.2 0.7 2.6 2.6 0.7 0.2 0.1 0.4 0.0 0.1 0.7 0.257 0.282 0.385 0.667 0
Gregorio Petit HOU SS, 3B SS, 3B -4.1 -4.4 0.5 1.9 1.9 0.5 0.2 0.0 0.2 0.0 0.1 0.3 0.257 0.274 0.366 0.640 2
Kevin Pillar TOR OF OF -4.1 -4.1 0.6 2.1 2.0 0.5 0.2 0.0 0.2 0.0 0.1 0.2 0.257 0.289 0.411 0.700 0
David Peralta ARI OF OF -4.2 -4.1 0.6 2.0 2.0 0.6 0.2 0.0 0.2 0.0 0.1 0.3 0.278 0.290 0.418 0.708 23
James Loney TB 1B 1B -4.2 -3.4 0.8 3.2 3.1 0.9 0.3 0.0 0.3 0.0 0.2 0.5 0.293 0.334 0.387 0.721 83
Marwin Gonzalez HOU 2B, SS, 3B 2B, SS, 3B -4.4 -4.7 0.5 2.2 2.1 0.5 0.2 0.0 0.1 0.0 0.1 0.3 0.250 0.277 0.361 0.638 1
Jarrod Saltalamacchia MIA C C -4.4 -5.7 0.8 2.5 2.3 0.5 0.2 0.1 0.3 0.0 0.2 0.8 0.194 0.249 0.336 0.585 6
A.J. Pollock ARI OF OF -4.7 -3.8 0.8 3.3 3.2 0.8 0.3 0.0 0.3 0.1 0.1 0.6 0.256 0.281 0.369 0.650 81
Brendan Ryan NYA 2B, SS 1B, 2B, SS -4.7 -4.8 0.4 1.5 1.4 0.3 0.1 0.0 0.1 0.0 0.1 0.3 0.212 0.275 0.286 0.561 0
Justin Bour MIA 1B 1B -4.8 -4.5 0.5 1.7 1.7 0.4 0.2 0.0 0.2 0.0 0.1 0.3 0.212 0.254 0.353 0.607 0
Ryan Ludwick CIN OF OF -4.8 -4.8 0.8 3.0 2.9 0.7 0.4 0.0 0.3 0.0 0.2 1.0 0.237 0.310 0.393 0.703 1
Chris Valaika CHN 1B, 2B 1B, 2B, SS, 3B -5.0 -5.1 0.6 2.1 2.0 0.5 0.2 0.0 0.2 0.0 0.1 0.6 0.229 0.267 0.333 0.600 1
Desmond Jennings TB OF OF -5.0 -4.8 1.0 4.1 3.7 1.0 0.5 0.0 0.3 0.0 0.3 0.9 0.256 0.348 0.394 0.742 61
Alcides Escobar KC SS SS -5.1 -4.2 1.0 4.0 3.7 0.9 0.4 0.0 0.4 0.1 0.2 0.5 0.231 0.291 0.325 0.616 100
Jordan Danks CHA OF OF -5.1 -5.1 0.5 1.7 1.6 0.3 0.2 0.0 0.2 0.0 0.2 0.4 0.194 0.295 0.327 0.622 0
Brennan Boesch LAA OF OF -5.2 -5.1 0.6 1.9 1.8 0.4 0.1 0.1 0.1 0.0 0.1 0.4 0.212 0.239 0.327 0.566 2
Eduardo Escobar MIN SS, 3B 2B, SS, 3B -5.4 -5.7 0.6 1.8 1.8 0.4 0.2 0.0 0.2 0.0 0.1 0.4 0.219 0.236 0.309 0.545 6
Hank Conger LAA C C -5.4 -5.9 0.5 1.6 1.5 0.3 0.2 0.0 0.1 0.0 0.1 0.5 0.207 0.239 0.279 0.518 0
Cameron Maybin SD OF OF -5.5 -4.6 0.8 2.9 2.7 0.7 0.2 0.0 0.3 0.1 0.2 0.5 0.250 0.295 0.347 0.642 0
A.J. Ellis LAN C C -5.5 -6.9 0.8 3.0 2.7 0.7 0.3 0.0 0.3 0.0 0.2 0.5 0.257 0.336 0.366 0.702 1
Derek Norris OAK C C -5.6 -7.2 0.8 2.8 2.6 0.6 0.4 0.0 0.3 0.0 0.2 0.5 0.242 0.319 0.415 0.734 40
Chris Herrmann MIN C, OF C, OF -5.7 -6.1 0.5 1.8 1.7 0.3 0.1 0.0 0.2 0.0 0.1 0.1 0.182 0.224 0.252 0.476 0
Wil Myers TB OF OF -5.8 -5.7 1.0 4.3 3.9 1.0 0.4 0.0 0.4 0.0 0.3 0.9 0.268 0.350 0.422 0.772 73
Sean Rodriguez TB 1B, 2B, OF 1B, 2B, SS, 3B, OF -5.8 -6.4 0.9 3.1 2.9 0.7 0.5 0.0 0.4 0.0 0.2 1.0 0.242 0.315 0.393 0.708 1
Conor Gillaspie CHA 3B 1B, 3B -5.8 -4.3 1.0 3.5 3.3 0.8 0.4 0.1 0.4 0.0 0.2 0.5 0.229 0.293 0.340 0.633 27
Logan Watkins CHN 2B 2B -5.8 -6.0 0.5 1.7 1.6 0.3 0.1 0.0 0.1 0.1 0.1 0.4 0.207 0.277 0.346 0.623 1
Efren Navarro LAA 1B, OF 1B, OF -5.8 -5.7 0.5 1.3 1.3 0.3 0.1 0.0 0.1 0.0 0.1 0.2 0.200 0.259 0.277 0.536 0
Eric Sogard OAK 2B, SS 2B, SS -5.9 -3.8 0.9 2.8 2.6 0.7 0.4 0.0 0.2 0.2 0.2 0.3 0.276 0.333 0.401 0.734 0
Eduardo Nunez MIN SS, 3B, OF SS, 3B, OF -5.9 -6.7 0.7 2.6 2.6 0.6 0.3 0.0 0.3 0.0 0.1 0.7 0.222 0.247 0.330 0.577 0
Dayan Viciedo CHA OF OF -5.9 -5.8 0.9 3.1 3.0 0.7 0.3 0.1 0.4 0.0 0.2 0.7 0.229 0.271 0.356 0.627 39
Matt den Dekker NYN OF OF -6.0 -5.9 0.8 3.3 3.0 0.8 0.4 0.0 0.3 0.0 0.2 0.9 0.256 0.333 0.408 0.741 0
Kristopher Negron CIN 2B, 3B 2B, 3B -6.0 -6.1 0.5 1.9 1.8 0.4 0.1 0.0 0.1 0.0 0.1 0.6 0.216 0.278 0.330 0.608 0
Ike Davis PIT 1B 1B -6.1 -4.1 0.8 2.3 2.1 0.5 0.3 0.1 0.3 0.0 0.2 0.5 0.231 0.306 0.384 0.690 13
Munenori Kawasaki TOR 2B, SS, 3B 2B, SS, 3B -6.1 -6.4 0.6 1.8 1.7 0.4 0.2 0.0 0.1 0.0 0.1 0.2 0.241 0.300 0.339 0.639 0
Nick Castellanos DET 3B 3B, OF -6.1 -5.1 0.9 3.6 3.5 0.9 0.4 0.0 0.5 0.0 0.1 0.6 0.263 0.294 0.368 0.662 71
Yunel Escobar TB SS SS -6.1 -7.3 1.0 3.9 3.6 1.0 0.4 0.0 0.4 0.0 0.3 0.4 0.263 0.349 0.359 0.708 15
Marcell Ozuna MIA OF OF -6.1 -6.0 0.8 2.8 2.8 0.6 0.2 0.1 0.4 0.0 0.1 0.8 0.222 0.237 0.355 0.592 100
Ryan Flaherty BAL 2B, SS, 3B 2B, SS, 3B -6.2 -6.9 0.7 2.6 2.5 0.5 0.3 0.0 0.3 0.0 0.1 0.5 0.216 0.272 0.361 0.633 6
Ender Inciarte ARI OF OF -6.2 -4.5 0.9 3.7 3.6 0.9 0.4 0.0 0.2 0.2 0.1 0.5 0.250 0.276 0.339 0.615 65
Hunter Pence SF OF OF -6.4 -6.2 0.9 3.8 3.5 1.0 0.4 0.0 0.3 0.0 0.2 0.7 0.282 0.331 0.465 0.796 100
Maikel Franco PHI 3B 1B, 3B -6.5 -5.6 0.9 3.8 3.6 1.0 0.5 0.0 0.4 0.0 0.1 0.5 0.275 0.296 0.454 0.750 5
Tyler Flowers CHA C C -6.5 -7.7 0.8 2.6 2.3 0.5 0.2 0.1 0.3 0.0 0.2 0.8 0.194 0.251 0.306 0.557 5
Zack Cozart CIN SS SS -6.6 -7.5 0.8 2.7 2.6 0.6 0.3 0.0 0.3 0.0 0.1 0.6 0.242 0.288 0.359 0.647 10
Dexter Fowler HOU OF OF -6.6 -5.3 0.9 3.9 3.6 0.9 0.3 0.0 0.3 0.1 0.3 1.1 0.244 0.333 0.391 0.724 64
Christian Vazquez BOS C C -6.8 -8.3 0.8 3.0 2.9 0.7 0.3 0.0 0.3 0.0 0.1 0.6 0.250 0.293 0.374 0.667 1
Jackie Bradley Jr. BOS OF OF -6.8 -6.7 0.8 2.6 2.6 0.6 0.3 0.0 0.3 0.0 0.2 0.7 0.235 0.297 0.385 0.682 2
Jonathan Villar HOU SS SS -7.2 -6.0 0.9 3.0 2.8 0.7 0.3 0.0 0.3 0.1 0.1 0.9 0.242 0.274 0.354 0.628 13
Rougned Odor TEX 2B 2B -7.2 -7.9 1.0 3.7 3.5 1.0 0.4 0.0 0.4 0.0 0.1 0.7 0.270 0.296 0.372 0.668 43
Yangervis Solarte SD 2B, 3B SS -7.3 -7.5 0.7 3.2 3.0 0.8 0.3 0.0 0.1 0.0 0.1 0.5 0.268 0.321 0.346 0.667 63
Ryan Goins TOR 2B, SS 2B, SS -7.4 -8.0 0.7 2.2 2.1 0.5 0.2 0.0 0.3 0.0 0.1 0.3 0.233 0.269 0.351 0.620 0
Josmil Pinto MIN C C -7.5 -7.9 0.6 1.8 1.7 0.4 0.1 0.0 0.1 0.0 0.1 0.4 0.233 0.263 0.351 0.614 2
Rene Rivera SD C C -7.5 -9.1 0.8 3.1 3.0 0.7 0.3 0.0 0.3 0.0 0.2 0.7 0.237 0.280 0.349 0.629 2
Rafael Ynoa COL 3B 3B -7.5 -7.4 0.5 2.1 2.0 0.4 0.1 0.0 0.1 0.0 0.1 0.3 0.205 0.244 0.273 0.517 4
Gerald Laird ATL C C -7.5 -7.6 0.4 1.4 1.3 0.3 0.0 0.0 0.0 0.0 0.1 0.4 0.200 0.249 0.284 0.533 0
Anthony Gose TOR OF OF -7.5 -5.9 0.8 2.7 2.5 0.6 0.3 0.0 0.1 0.2 0.2 0.5 0.233 0.284 0.362 0.646 5
Adam Eaton CHA OF OF -7.9 -6.7 1.0 3.8 3.5 0.9 0.5 0.0 0.3 0.1 0.3 0.6 0.243 0.312 0.331 0.643 89
Chase Utley PHI 2B 2B -7.9 -8.8 1.0 4.1 3.8 1.0 0.4 0.0 0.3 0.0 0.3 0.6 0.250 0.332 0.423 0.755 100
Marlon Byrd PHI OF OF -7.9 -7.8 1.0 4.0 3.8 1.0 0.4 0.0 0.3 0.0 0.2 0.9 0.275 0.318 0.482 0.800 85
Caleb Joseph BAL C C -7.9 -8.7 0.6 2.1 2.1 0.4 0.2 0.0 0.2 0.0 0.1 0.6 0.212 0.266 0.350 0.616 0
Pablo Sandoval SF 3B 3B -8.0 -7.1 0.9 3.8 3.6 1.0 0.3 0.0 0.4 0.0 0.2 0.6 0.275 0.314 0.417 0.731 96
Charlie Blackmon COL OF OF -8.0 -6.9 1.0 4.0 3.9 0.9 0.4 0.1 0.3 0.1 0.1 0.8 0.220 0.252 0.324 0.576 100
Wilin Rosario COL C C -8.2 -9.3 0.8 2.8 2.7 0.5 0.2 0.1 0.2 0.0 0.1 0.7 0.194 0.227 0.317 0.544 93
Jon Jay STL OF OF -8.3 -8.1 0.9 3.7 3.5 1.0 0.5 0.0 0.2 0.0 0.2 0.7 0.282 0.330 0.417 0.747 33
Joaquin Arias SF 1B, 2B, SS, 3B 1B, 2B, SS, 3B -8.7 -9.6 0.9 3.4 3.3 0.9 0.4 0.0 0.3 0.0 0.1 0.5 0.270 0.284 0.349 0.633 0
Jake Marisnick HOU OF OF -8.8 -8.7 0.8 3.2 3.1 0.8 0.3 0.0 0.3 0.0 0.1 0.9 0.256 0.271 0.377 0.648 43
Angel Pagan SF OF OF -8.8 -8.7 0.9 4.0 3.8 1.1 0.4 0.0 0.3 0.0 0.1 0.7 0.286 0.313 0.391 0.704 76
Cody Asche PHI 3B 3B -8.9 -8.3 0.8 3.0 2.9 0.8 0.2 0.0 0.2 0.0 0.2 0.8 0.263 0.298 0.401 0.699 10
Josh Hamilton LAA OF OF -9.0 -8.8 0.9 3.0 2.8 0.6 0.3 0.1 0.3 0.0 0.2 0.9 0.212 0.263 0.350 0.613 64
Logan Forsythe TB 2B 2B, SS, 3B, OF -9.1 -9.6 0.9 3.8 3.4 0.9 0.4 0.0 0.4 0.0 0.3 0.6 0.263 0.336 0.367 0.703 4
Danny Santana MIN SS, OF SS, OF -9.3 -10.0 0.7 3.0 2.9 0.7 0.3 0.0 0.3 0.0 0.1 0.8 0.225 0.229 0.300 0.529 100
Kole Calhoun LAA OF OF -9.5 -9.3 1.0 3.8 3.6 0.8 0.4 0.1 0.3 0.0 0.1 0.8 0.211 0.263 0.350 0.613 100
Justin Morneau COL 1B 1B -9.6 -7.8 0.9 3.5 3.3 0.8 0.3 0.1 0.3 0.0 0.2 0.5 0.243 0.283 0.392 0.675 100
Omar Infante KC 2B 2B -9.6 -10.2 1.0 3.9 3.6 1.0 0.4 0.0 0.4 0.0 0.2 0.5 0.263 0.311 0.359 0.670 37
Joe Panik SF 2B 2B -9.8 -10.1 0.8 3.7 3.5 0.9 0.3 0.0 0.2 0.0 0.1 0.2 0.250 0.294 0.320 0.614 23
Carlos Sanchez CHA 2B 2B -9.9 -10.1 0.6 2.1 2.0 0.4 0.1 0.0 0.1 0.0 0.1 0.4 0.212 0.274 0.281 0.555 0
Albert Pujols LAA 1B 1B -9.9 -7.9 1.0 3.5 3.3 0.8 0.4 0.1 0.5 0.0 0.2 0.6 0.229 0.267 0.374 0.641 100
Jordan Schafer MIN OF OF -9.9 -9.9 0.6 1.9 1.8 0.3 0.1 0.0 0.1 0.0 0.1 0.7 0.182 0.221 0.226 0.447 55
C.J. Cron LAA 1B 1B -10.0 -8.7 0.8 2.4 2.3 0.5 0.2 0.1 0.3 0.0 0.1 0.6 0.194 0.229 0.305 0.534 17
Chris Iannetta LAA C C -10.5 -11.6 0.8 2.4 2.3 0.4 0.2 0.1 0.2 0.0 0.2 0.9 0.167 0.260 0.266 0.526 0
Avisail Garcia CHA OF OF -10.9 -10.8 0.9 3.4 3.2 0.7 0.3 0.0 0.5 0.0 0.2 0.7 0.222 0.278 0.340 0.618 65
Domonic Brown PHI OF OF -11.1 -10.9 0.9 3.4 3.2 0.9 0.3 0.0 0.2 0.0 0.2 0.6 0.263 0.303 0.409 0.712 48
Danny Valencia TOR 1B, 3B 1B, 2B, 3B -11.1 -10.6 0.8 3.0 2.9 0.7 0.3 0.0 0.3 0.0 0.1 0.6 0.243 0.269 0.403 0.672 2
Ryan Rua TEX OF 1B, OF -11.1 -11.0 0.9 3.3 3.2 0.8 0.3 0.0 0.3 0.0 0.2 0.9 0.250 0.296 0.355 0.651 6
Phil Gosselin ATL 2B 2B, SS, 3B -11.1 -11.3 0.7 2.7 2.6 0.6 0.3 0.0 0.1 0.0 0.1 0.5 0.216 0.248 0.310 0.558 0
Jonathan Schoop BAL 2B, 3B 2B, 3B -11.2 -11.5 0.7 2.5 2.4 0.5 0.2 0.0 0.2 0.0 0.1 0.7 0.212 0.260 0.352 0.612 17
Jimmy Rollins PHI SS SS -11.4 -13.0 0.9 4.1 3.8 0.9 0.3 0.0 0.2 0.0 0.3 0.6 0.238 0.306 0.384 0.690 77
Darin Ruf PHI 1B, OF 1B, OF -11.6 -11.5 0.9 3.3 3.1 0.8 0.3 0.0 0.3 0.0 0.2 0.9 0.265 0.332 0.464 0.796 0
Josh Rutledge COL 2B, SS 2B, SS, 3B -11.7 -12.3 0.8 2.7 2.6 0.5 0.3 0.0 0.2 0.0 0.1 0.7 0.200 0.237 0.282 0.519 55
Evan Gattis ATL C, OF C, OF -11.8 -12.8 0.8 2.7 2.6 0.5 0.2 0.0 0.2 0.0 0.1 0.8 0.206 0.253 0.416 0.669 75
Michael Morse SF 1B, OF 1B, OF -11.8 -11.7 0.9 3.3 3.2 0.8 0.3 0.0 0.3 0.0 0.1 0.8 0.257 0.308 0.451 0.759 57
Brandon Belt SF 1B 1B -12.0 -11.1 0.9 3.4 3.1 0.9 0.2 0.0 0.3 0.0 0.2 0.9 0.270 0.309 0.394 0.703 62
Didi Gregorius ARI 2B, SS 2B, SS -12.2 -13.0 0.9 3.1 3.0 0.7 0.3 0.0 0.3 0.0 0.1 0.5 0.242 0.282 0.361 0.643 4
Brandon Crawford SF SS SS -12.4 -13.3 0.9 3.4 3.2 0.8 0.3 0.0 0.3 0.0 0.2 0.9 0.237 0.285 0.321 0.606 33
Jason Heyward ATL OF OF -12.5 -12.5 0.7 2.6 2.5 0.5 0.2 0.0 0.1 0.0 0.1 0.5 0.200 0.263 0.325 0.588 92
Howie Kendrick LAA 2B 2B -12.8 -13.3 0.9 3.2 3.2 0.7 0.2 0.0 0.3 0.1 0.1 0.7 0.229 0.256 0.307 0.563 99
Jordy Mercer PIT 2B, SS 2B, SS -13.0 -14.2 0.9 3.2 3.2 0.6 0.4 0.0 0.4 0.0 0.1 0.5 0.200 0.256 0.325 0.581 69
Joe Mauer MIN C,1B C, 1B -13.3 -14.3 0.8 3.0 2.9 0.7 0.2 0.0 0.2 0.0 0.2 0.7 0.229 0.284 0.307 0.591 100
Kennys Vargas MIN 1B 1B -13.5 -12.2 0.9 3.5 3.4 0.7 0.5 0.0 0.3 0.0 0.1 0.6 0.211 0.236 0.328 0.564 90
Freddy Galvis PHI 2B, SS, 3B 2B, SS, 3B, OF -13.6 -14.7 0.9 3.2 3.1 0.7 0.2 0.0 0.4 0.0 0.1 0.5 0.235 0.277 0.389 0.666 2
Erick Aybar LAA SS SS -13.8 -13.4 1.0 3.2 3.1 0.8 0.3 0.0 0.3 0.1 0.1 0.5 0.242 0.255 0.300 0.555 96
Ryan Howard PHI 1B 1B -14.4 -12.8 1.0 4.1 3.8 0.9 0.4 0.0 0.4 0.0 0.3 1.5 0.225 0.291 0.396 0.687 81
Gordon Beckham LAA 2B, 3B 2B, SS, 3B -14.5 -15.3 0.9 2.8 2.7 0.5 0.2 0.1 0.2 0.0 0.1 0.6 0.188 0.230 0.275 0.505 12
Alexi Amarista SD 2B, SS, 3B, OF 2B, SS, 3B, OF -14.7 -15.6 0.9 3.5 3.3 0.9 0.2 0.0 0.3 0.0 0.1 0.5 0.270 0.296 0.318 0.614 60
Luis Valbuena CHN 2B, 3B 2B, 3B -14.8 -15.3 0.9 3.6 3.3 0.7 0.3 0.0 0.3 0.0 0.3 0.8 0.216 0.307 0.412 0.719 58
Justin Upton ATL OF OF -15.6 -15.5 1.0 3.4 3.1 0.8 0.4 0.0 0.3 0.0 0.2 0.9 0.242 0.303 0.425 0.728 100
Michael Cuddyer COL 1B, OF 1B, OF -16.0 -15.9 1.0 3.6 3.4 0.8 0.3 0.1 0.3 0.0 0.1 0.8 0.222 0.253 0.324 0.577 98
Trevor Plouffe MIN 3B 3B -16.5 -16.0 0.8 3.0 2.9 0.7 0.2 0.0 0.2 0.0 0.1 0.7 0.229 0.260 0.368 0.628 86
Chris Coghlan CHN OF 3B, OF -17.0 -16.8 0.9 3.8 3.5 0.8 0.3 0.0 0.2 0.0 0.2 0.9 0.231 0.303 0.396 0.699 32
Aaron Hicks MIN OF OF -17.1 -17.0 0.8 2.9 2.7 0.5 0.2 0.0 0.3 0.0 0.2 0.7 0.182 0.245 0.283 0.528 2
Adeiny Hechavarria MIA SS SS -17.3 -17.0 1.0 3.2 3.1 0.7 0.2 0.0 0.3 0.1 0.0 0.6 0.212 0.229 0.293 0.522 12
DJ LeMahieu COL 2B 2B, 3B -17.4 -17.8 0.9 3.0 3.0 0.6 0.2 0.0 0.2 0.1 0.1 0.6 0.212 0.236 0.253 0.489 32
Emilio Bonifacio ATL 2B, OF 2B, 3B, OF -17.5 -17.9 0.9 3.3 3.1 0.6 0.2 0.0 0.3 0.0 0.1 0.9 0.194 0.243 0.272 0.515 32
Andrelton Simmons ATL SS SS -17.5 -18.5 1.0 3.3 3.2 0.7 0.3 0.0 0.3 0.0 0.1 0.4 0.206 0.257 0.335 0.592 54
Brian Dozier MIN 2B 2B -17.8 -18.3 0.9 3.5 3.4 0.7 0.3 0.0 0.3 0.0 0.2 0.7 0.216 0.262 0.344 0.606 99
David Freese LAA 3B 3B -17.9 -17.2 0.9 2.7 2.6 0.5 0.2 0.0 0.2 0.0 0.1 0.9 0.194 0.256 0.296 0.552 74
Gregor Blanco SF OF OF -18.0 -17.9 0.9 3.8 3.5 0.8 0.3 0.0 0.2 0.0 0.2 0.9 0.231 0.300 0.310 0.610 52
Casey McGehee MIA 3B 3B -18.5 -17.7 1.0 3.6 3.5 0.8 0.3 0.0 0.3 0.0 0.1 0.6 0.216 0.261 0.317 0.578 85
Freddie Freeman ATL 1B 1B -18.8 -17.8 1.0 3.6 3.3 0.8 0.3 0.0 0.3 0.0 0.2 1.0 0.229 0.279 0.351 0.630 100
Oswaldo Arcia MIN OF OF -18.8 -18.7 0.9 3.0 2.9 0.6 0.2 0.0 0.2 0.0 0.1 0.9 0.206 0.233 0.311 0.544 77
Nolan Arenado COL 3B 3B -19.3 -18.2 1.0 3.5 3.4 0.7 0.3 0.1 0.3 0.0 0.1 0.5 0.194 0.234 0.300 0.534 63
Chris Johnson ATL 3B 1B, 3B -21.5 -20.8 1.0 3.3 3.2 0.8 0.3 0.0 0.2 0.0 0.1 0.8 0.235 0.262 0.357 0.619 49
Donovan Solano MIA 2B 2B -23.1 -23.3 0.9 3.5 3.4 0.7 0.2 0.0 0.2 0.0 0.1 0.7 0.211 0.238 0.285 0.523 0
B.J. Upton ATL OF OF -27.2 -27.0 1.0 3.2 3.0 0.6 0.2 0.0 0.2 0.0 0.2 1.0 0.188 0.257 0.329 0.586 45
Geovany Soto OAK C C 0.2 0.8 0

Hittertron Info

Razzball Hittertron (aka Hitter-Tron):  This tool is designed to identify attractive short-term hitter pickups and to determine when to start/sit hitters on your roster.  (For Daily Fantasy Baseball games, check out DFSBot)  The higher the $ value, the more attractive the start.  Hittertron projections rely on Steamer Rest of Season projections as a foundation and then adjust based on several game-specific factors that include quality of opposing starting pitcher, hitter’s performance vs. the handedness of opposing starting pitcher, park factors, whether the game is home or away, and predicted batting order spot (for Runs, RBIs, and Plate Appearances).

What Is The Expected Accuracy Of Hittertron Projections?:  Please see the Razzball Ombotsman for correlations between the Hittertron projections and actual stats.

Filtering Results:  You can filter multiple fields at the same time.  The text fields below the column headers enable several methods for filtering the data.  Here are some examples:

Function Symbol Example Explanation
ANY MATCH ‘B’ in Pos Typing B in Pos will filter to any player with 1B, 2B, or 3B eligibility.  Type in more details to filter further – e.g., “1B’, “1B, 3B”, etc.
OR | 2B|SS Requires exact match on both sides – so 2B|SS returns anyone who has 2B or SS eligibility but not anyone with 2B/SS, 2B/3B, etc.
NOT ! !OF All players who do not have OF eligibility.
NOR ! | !1B|OF All players who do not have 1B eligibility NOR OF eligibility.  Just use the ! once.
GREATER THAN > >30 in $ All players whose $ is greater than 30.  Does not work for Date.
LESS THAN < <30 in $ All players whose $ is less than 30.  Does not work for Date.
GREATER THAN OR EQUAL TO >= >=30 in $ All players whose $ is greater than or equal to 30.  Does not work for date.
LESS THAN OR EQUAL TO <= <=30 in $ All players whose $ is less than or equal to 30.  Does not work for Date.

Position Eligibility – 20 Games in last season for ESPN and ’2 Catcher’ formats.   5 Games for Yahoo.

$ Values – A hitter’s projected stats for the game are multiplied by 150 and then valued for a 12-team MLB league using the ESPN/CBSSports roster format (13 hitters, 9 pitchers) and a $260 team budget.  While the $ values would vary for any other league format, we would expect the rankings to remain relatively the same.   For 12-team leagues, $8 is about the ‘average’ hitter start. The ‘$’ estimate takes position value into account.  The ‘$U’ estimate is position-neutral and is the value to use when looking at players for Utility slots.

Own%  Based on ownership within the Razzball Commenter Leagues which consists of 84 12-team MLB leagues using the standard ESPN roster format.

 

  1. franky2times says:
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    This looks like the wrong place to post comments but first of all, everything on this site is the tits, and is there or will there ever be some sort of tool where i can input my whole time and rank by $ value for the week ahead?

    • @franky2times: thanks. i’ll start valuing readers’ next 7 days when grey starts covering that in the roundup. “franky2times – Didn’t even leave the house on Sunday. Add him if your team needs help in counting stats like ‘Eating Cheetos’ and ‘Leisurely defecation’.

  2. Note: Removed SLG from this table as it was causing display issues on iPads (the table went behind the ad on the right side). The SLG data can be found on the player pages as well as the weekly hitter data.

  3. Note: Removed SLG from this table as it was causing display issues on iPads (the table went behind the ad on the right side). The SLG data can be found on the player pages as well as the weekly hitter data.

  4. Richard Kenno says:
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    It seems today for some reason, I can’t access the Razzball tools spreadsheet lists, e.g. Hitter-Tron, Stream-o-Nator, etc. but am seeing the comments. Are the lists down temporarily? Thanks for the hard work, these tools are amazing!

  5. ZACJAMESBITCH says:
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    the hittertron is the best tool in fantasy but what the hell is with its obsession with David freaking Murphy?

    • @ZACJAMESBITCH: Thanks. It likes Murphy this week b/c they have seven home games (in a great hitter park) and they face only 2 lefties.

      • Kevin S says:
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        @Rudy Gamble:

        I bet it also has to do with how well he played last year. This year he has been terrible but all the back data shows him as a better player.

  6. goodfold2 says:
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    it appears avila is expected to get less at bats and less total stats for the next 7 days than Ruiz, but yet rates higher at his position. The only way this makes sense is to say that the more time a shitty stats gathering catcher gets, the worse he is for the team. I’m trying to find a catcher better than Zunino. I used to have Ruiz (sidenote, why does Hitter T project a better slugging for Ruiz than Avila/Ellis/Zunino? He seems to have the worst slugging in real life this season)
    best catchers out there are
    ruiz (probably best avg, plays almost every day, but worst power, probably most likely to be injured)
    avila (more likely to get homers, in good lineup, also likeliest to have worst avg,biggest upside)
    ellis (playing the best right now, lineup’s hot,but sits out the most too)
    zunino (gets off 2nd most days of these guys, has terrible avg, on pretty weak lineup too, he’s the dropped one, but for which of the above?)
    This is a 16 team h2h league with hits/avg/total bases all as categories. That probably helps Ruiz. Grey pretty much says they’re all crap but just play the hottest hitting currently. Which would be Ellis.

    • goodfold2 says:
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      @goodfold2: another factor i just noticed. in my league next “week” is actually both the next 7 day week plus the 3 days after all star break, so fri-sun 19-21. The only reason this affects anything is that we still only have 5 weekly pickups in this the 10 day week. Further complicating matters is i’m using probably nearly all 5 of these (one of them the catcher one) late tonight. I have needs, such as
      1. Aramis injury (who knows how much time he misses over next few weeks.) have to pickup Beckham (moved up to 2nd in order today, got his usual 2 hits) and move Dj lemehieu to 3rd (or wallace at 3rd) dropping Rutledge (which will leave me without backup at SS for Aybar, but he pretty much never sits anyway) since Rutledge pretty much doesn’t perform anymore and only plays like 60% of the time, usually in the worst part of the order.
      2. Dropping Kendrick’s ugly ass lately for Kluber yet again
      3.dropping either Robertson/Smyly/Fausto Carmona (after his Monday start)/Wallace for Porcello after his great start recently.
      4. Span getting hits, and more importantly the next 3 guys also are, upping his run scoring value again, so dropping Quentin (at home, where he sucks, for next 7 days) for Span.
      5. Catcher flip in question

  7. hankp101 says:
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    It looks like some players are missing from the hittertron. I’m looking at the weekly version and both Pujols and Bautista are missing from my roster.

  8. malamoney

    malamoney says:
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    I feel like HitterTron should include projected strikeouts.

  9. malamoney

    malamoney says:
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    Also, where can I find past results? I’d like to see how accurate HitterTron and Stream-o-nator were last week and the week before, etc.

    • @malamoney: Still on the long-term to-do list. Not easy to display that type of data in a way that’s going to be relevant to our readers.

      • malamoney

        malamoney says:
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        @Rudy Gamble: My suggestion would be just to list the actual results of each column in a column next to the projection column.

        So you have Games, PA, AB, H, R, HR, RBI, SB, BB, SO

        Why not add one extra column for each of the above the contains the actual values and let the users (consumers) of your tools do what they want with it.

        I can do this manually, but it is a nightmare. I am guessing you have better access to daily stats in which you could put together a few functions to populate these columns.

        Without this data, I have no way of know how accurate these tools are. What I typically do is cut and paste your data into a spreadsheet and plug the projections into a formula based on my league’s scoring system to figure out how many fantasy points each will have for the week. I use this to help me decide on my lineup for the week.

        I do this each week (just started this season) so I can manually look at what HitterTron and Streamonator projected vs. what each of my players actually did. This helps me get an idea of their accuracies, but it’s only a small sample size of players (just the guys on my roster).

        I love these tools, or at least the concept of them, but think they a few tweaks away from being awesome.

        • The reality is that the vast majority of our users do not know how to gauge the accuracy of projections vs actual results. I would rather present the results of such tests than encourage false conclusions.

          I can already tell you that daily data is only slightly predictive (at best) once you account for the underlying hitter/pitcher talent (e.g., predicting Miggy will be better than Don Kelly isn’t an accomplishment). My goal is to leverage the various daily factors like park, opposing pitcher/lineup to improve upon each player’s baseline which should net out – in the long run – to a slight advantage (in less time and more effectively) than most people can do by following their gut.

          • malamoney

            malamoney says:
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            @Rudy Gamble: Weekly prediction results would be fine. If HitterTron says Ryan Braun is going to put up the following line this week:

            23AB, 9H, 3HR, 7RBI, 1SB, 5R, 3BB, 6K

            At the end of the week, I’d like to be able to easily compare that line to his actual line. And when I say easily, I am asking if it is possible for you put the data next to each other.

            On the player details pages under Projections, you have “Next 7 Days (HitterTron”), why not have a section called “Projection Results” that shows “Last 7 Days (HitterTron”) and under that “Last 7 Days (Actual)”?

            • @malamoney: I will work on a way that provides a statistically sound way to compare the accuracy of the projections. I am not going to clutter the player pages to do so. The ‘test’ you want to do – “how far off were the projections last day/week” – are going to fail miserably for every baseball projection source forever. The sample sizes are too small. Look at Miggy Cabrera’s last 7 days. I can guarantee he was probably a top 5 projected hitter. Massively off! There is no value to be gained here.

              If you disagree, you are more than welcome to copy the ‘Next 7 Day’ projections on Mondays and the ‘Last 7 Day’ projections the following Monday to compare. It’ll take you 5 minutes a week to cut/paste.

              • malamoney

                malamoney says:
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                @Rudy Gamble: Where do I find “Last 7 Days (Actual)” for a given player?

                I agree that there is no value in comparing daily stat projections. However, weekly stats are another story, especially since most of us play in weekly leagues.

                Why do we use tools such as HitterTron and Stream-o-nator? Because they help us. Or at least we think or hope they help us. Perhaps they do, but it also just as possible that they do not. How would I know?

                I use the tools to help push me one way or another when I am on the fence about who to start, but I’d really like to know if it makes sense for me to continue using the tools.

                I am not trying to be insulting. I think what you have here is potentially awesome and I respect the effort you put into it, but I think it’s possible to make these tools even more powerful and back them up with proof that validate their awesomeness. At the end of the day fancy numbers don’t impress me, results do.

                If I am trying to decide whether to start Gyorko or Moss I’d like to turn to HitterTron to tell me what to do. So let’s say it says to start Moss. At the end of the week I’d like see if HitterTron did me a solid or not. That I can do easily.

                I think weekly is the best unit of stat projection measurement. Daily is way too small and monthly becomes an aggregate that will mask accurate and inaccurate weeks.

                Think of players like stocks. Each week you project the players performance for that week. At the end of the week you evaluate your projections. Perhaps define a threshold for defining successful accuracy. Define a formula for determining a player’s performance. In my case I use our league’s scoring system. I plug in your projections and get a projected fantasy points value. Then at the end of the week compare. If HitterTron was within let’s say 20%, then it was a success. If not, a failure. Perhaps success and failure are too strong of words, but you get the point. You could also indicate that whether HitterTron’s projections were too high or too low.

                So for a player you might see:

                Paul Goldschmidt’s HitterTron Results:

                Week 1: Projected: 29 points, Actual 33, -13% (green because within 20% threshold)
                Week 2: Projected: 35, Actual 25, +28% (red)
                Week 3: Projected: 42, Actual 42, The Price Is Right!

                Season: Projected: 106, Actual 100, +5% (green)

                I think something like this would be extremely valuable.

                Anyway, just the ramblings of a fantasy baseball loving computer programmer.

                • @malamoney: Last 7 Day and Last 30 Day Stats are accessible via ‘Stats’ in the main menu (7 day is http://razzball.com/mlbhittingstats-last7days/). You can also access it by clicking the ‘Last 7 Days’ hyperlink from the Player Page.

                  I agree that a weekly accuracy comparison will have less sample-related noise than daily (though not that much less) and I already have a solid metric to compare against (my 5×5 $). I also want to compare for each hitting category to communicate which are more reliable than others.

                  But we disagree on your proposed method above. You cannot really make the comparison at the player level and pretend it has any relevance. Miguel Cabrera’s last week is the perfect example. The ‘accuracy’ test has to be done on the aggregate of players (perhaps removing players who didn’t start). If you look at the weekly projections, you can see that it’s a game of decimals – e.g, 1.6 HR vs. 1.8 HR. If you focus on one player, all you’ll see is statistical noise. If I can present it in the aggregate, the noise will be neutralized enough that you can make some statistical assumptions.

                  Just to give you some perspective, my rankings tests that compare pre-season rankings against end of year rankings (http://razzball.com/fantasy-baseball-rankings-review-2013/) show that a rankings system is LUCKY to even correlate at 20% for hitting. Only 3 of 17 ranking systems hit that mark! While daily/weekly has the advantage of factoring in the opposing pitcher and doesn’t get penalized by injured players (e.g., 2013 Kemp), the smaller samples are debilitating. My point here is that if you looked at the pre-season ranking systems (or projections) and compared against each player, you’d never be able to tell which system was more accurate. Too much noise.

                  So to do this test right – and to have it update every day/week – takes some thinking. Once I figure it out, I can guarantee I’ll have the most transparently tested system out there. Whether that will inspire more/less confidence in you given the abstractness of the necessary testing (e.g., correlation testing), will be another matter.

                  • malamoney

                    malamoney says:
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                    @Rudy Gamble: I find very little value in aggregate stats as I feel they have too strong a potential to mask issues. An aggregate is like an average. I’m not looking for averages. Here’s an example. Let’s say we are looking at home run projections for 10 players:

                    Projected (these are made up projections):
                    Braun 25, Goldschmidt 25, Jones 20, Chris Davis 44, Posey 15, Fielder 48, Cespedes 23, Cabrera 40, Moss 15 and Gyorko 15

                    Actual:
                    Braun 35, Goldschmidt 35, Jones 30, Chris Davis 20, Posey 25, Fielder 20, Cespedes 33, Cabrera 25, Moss 25 and Gyorko 25

                    If you take the aggregate of the above the projections say 270HR and the actual is 273HR. That would point to some excellent, and accurate, projections. But if you look at each player, the projections are actually horrible and misleading and most importantly, useless.

                    When a fantasy owner is evaluating a player they are doing it at a per player level. They are trying to decide whether to draft one player over another, whether to start one player over another and/or whether to trade one player for another. The emphasis and importance needs to be on the per player level. Not daily stats, but last 7, last 30, season-to-date, next 7, next 30, rest of season.

                    I just don’t see there be any value in aggregate stat projections, especially across different players. I think the best way to evaluate a projection system is to say something like “this system was very accurate on 150 of the 350 (43%) players it provided projections for”. Perhaps even have a breakdown of accuracy levels: very accurate, accurate, not very accurate, way off.

                    Very accurate: 70 of 350 players (20%)
                    Accurate: 120 of 350 players (34%)
                    Not very accurate: 100 of 350 players (28%)
                    Way off: 60 of 350 players (17%)

                    Perhaps you can click on each of the above and expand to show a list of the players that fell into that category.

                    What is your formula for calculating your 5×5 $ value?

                    Would you consider adding “Last 7 days (HitterTron)” to the projections section of the player details page? It’s just one row, but it puts all the player data on the same page.

                    • When I say testing in aggregate, it is not adding up all the stats and comparing. A correlation test (which is what I’m thinking of doing) looks at each player comparison and determines how closely the two data sets compare. The test ranges from 100% to -100% with 100% meaning the values are perfectly aligned and -100% meaning they are completely negative aligned. Assuming that the sums are right (and I’m not projected, like, 4x the SB), this test should provide solid guidance for the accuracy of the projections. Bucketing them as you’re suggesting will not be effective. As I’ve mentioned before, with a little cutting/pasting, you can evaluate my projections how you see fit. But I’m not going to clutter the player pages or build extra reports for site visitors to facilitate incorrect judgments.

                      Sorry if that comes off dickish. I think fantasy baseball is an awesome mix of statistical rigor, common sense, and ‘gut’. Based on this thread, there’s no statistical rigor that is likely to satisfy your gut and your gut is not able to measure accuracy with any statistical rigor. So either you can believe in the science or just have faith that it works. Or use your gut more in making the final decisions. All fine by me.

    • I have archived them but we do not display on the interface.

  10. Charles says:
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    What time are these updated each morning? I use them for weekly Baseball Challenge but have to enter my lineup early Monday mornings.

    • malamoney

      malamoney says:
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      @Charles: Agreed. I find that on Monday mornings, it still includes Sunday’s games until about noon EST. Any chance of having the cutover be around midnight so that Monday morning it’s fresh for the coming week?

      • @malamoney: The updates happen usually by 10:30AM EST. I’m looking into a way that I can project ‘Next Calendar Week’ starting on Friday or Saturdays (requires some guesswork/extrapolation on probable starters).

  11. steve says:
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    Hey Rudy

    Alcides Escobar is on fire, but Hitter Tron views his next 7 very poorly. How do you utilize Hitter Tron when you see a (possible) discrepancy like this one? Is there a way to include some measure/value to see how well hitter tron has been doing with regard to it’s prognosis?

    It predicted the Neil Walker breakout last week!

    Thanks man.
    Steve

  12. Eddy says:
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    Hey Rudy,

    Was the feature of comparing multiple players by putting a | in between removed? Can’t seem to get it to work.

    • @Eddy: It’s still there but you now have to type in each player’s full name on each side of the ‘|’

  13. Simply Fred

    simply fred says:
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    Rudy, i have a simple mind. for next 7, in a 5X5 league, i add up the $values for R,HR,RBI,SB (sans avg since a $ isn’t provided)…expecting to get a total number relative to the ‘$’column.

    for Goldschmidt i get:
    R=4.2
    HR=.8
    RBI=2.6
    SB=.3
    tot=7.9
    avg=.286

    for J.D.Martinez i get:
    R=5.7
    HR=.8
    RBI=3.1
    SB=.2
    tot=8.8
    avg=.289

    so, sum for Martinez at 8.8 is greater than Goldy at 7.9.

    yet, $ for Goldy = 26.3, for Martinez = 22.8

    with avg nearly identical, doesn’t make sense to me that the sum doesn’t equal the parts…?

    bottom line, it makes more sense to me to rely on the sum of the identifiable parts, rather than the $ value (which isn’t quite as clear to me from the formula)…?

    • @simply fred: The R/HR/RBI/SB/AVG data are the projections not $ but you are right that the $ estimation is sub-optimal. Long story short, was doing an average $ for the week vs doing a complete $ calculation like I do with Player Rater and ‘Next Calendar Week’. Looks like my adjustment to handle extra games (Detroit has a doubleheader) is insufficient. When I have a chance, will need to create a ‘next 7 day’ player rater to get the $ right

  14. Simply Fred

    simply fred says:
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    still trying to figure streaming hitters…
    jaso ranks #22 for the next 7 days (i am set to add him).
    why don’t you have him rostered over guys you currently have:
    arcia #139
    adduci #170
    valdespin #176
    ? (he would fit your utility slot)
    (btw: did get francisco, #127 and odor, #108 today for a nice return!)

    • @simply fred: for RCL, I’m all about daily value. I’ve got Rosario right now at C and Rutledge at UT so no room to consider another catcher. I used Navarro yesterday as fill-in catcher because i knew he was starting and hitting cleanup (lineup posted). When in doubt, grab the sure things (Ruggiano ended up with an 0 for 0 b/c he didn’t end up starting).

      Nice on Juan-Fran! My streaming sucked yesterday aside from Navarro.

  15. Simply Fred

    simply fred says:
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    thanks! daily answers it.

    streaming daily has it’s downside. when those matchups look tasty, but there is an early start and the manager sits our guy, left with nuttin’ for that slot. (most of the time can juggle, but occasionally on a fabulous kayaking junket :-) and can’t get at the lineup :-(

    having fun!!

  16. Chuckles Tiddlesworth says:
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    Hey Rudy! Not sure if this is simply a quirk of me using the “Next 7 days” sort … but seems your “H” and “R” column headers are switched. Everyone is scoring more runs than they have hits. Probably the opposite, eh? That said, Hittertron rules. Thanks so much for this. You guys are the best.

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