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%
Jose Bautista TOR 1B, OF 1B, OF 28.9 45.6 6.7 28.5 25.4 6.9 4.5 1.9 4.9 0.3 2.9 4.8 0.273 0.382 0.520 0.903 100
Miguel Cabrera DET 1B, 3B 1B, 3B 27.0 44.8 6.2 27.4 25.0 8.2 4.3 1.4 4.8 0.1 2.1 4.8 0.328 0.406 0.571 0.977 100
Jose Altuve HOU 2B 2B 26.4 28.8 5.7 26.4 25.3 8.2 3.6 0.4 2.9 1.7 1.0 2.9 0.323 0.363 0.446 0.808 100
Mike Trout LAA OF OF 25.1 35.6 5.7 25.8 23.5 6.8 4.0 1.1 3.5 0.9 2.2 6.3 0.291 0.384 0.509 0.893 100
Edwin Encarnacion TOR 1B 1B, 3B 22.6 40.0 6.7 27.9 25.5 6.9 4.1 1.7 4.9 0.2 2.1 4.6 0.272 0.356 0.517 0.873 100
Nelson Cruz BAL OF OF 22.2 32.6 6.7 29.0 27.2 7.1 3.9 1.6 4.6 0.4 1.7 6.3 0.262 0.323 0.485 0.808 100
David Ortiz BOS DH 1B 18.7 25.3 4.6 19.6 17.8 5.2 3.2 1.3 3.9 0.1 1.8 3.4 0.290 0.392 0.586 0.978 100
Adrian Beltre TEX 3B 3B 18.5 29.0 6.7 27.6 26.1 8.1 3.6 1.2 4.4 0.1 1.4 3.5 0.309 0.362 0.508 0.870 100
Jose Reyes TOR SS SS 17.9 24.4 6.7 29.8 28.5 8.3 4.1 0.6 3.0 1.1 1.2 3.5 0.290 0.337 0.423 0.760 100
Andrew McCutchen PIT OF OF 17.7 30.6 6.7 28.2 25.8 7.7 3.7 1.0 3.8 0.7 2.3 5.3 0.298 0.377 0.490 0.867 100
Chris Carter HOU 1B, OF 1B, OF 17.7 20.6 5.4 23.4 21.2 5.1 3.2 1.6 4.0 0.1 1.9 7.7 0.243 0.336 0.501 0.837 100
Jacoby Ellsbury NYA OF OF 17.6 31.8 6.3 27.0 25.5 7.1 3.7 0.8 3.1 1.6 1.3 3.9 0.280 0.333 0.440 0.773 100
Brian McCann NYA C,1B C, 1B 17.4 19.6 6.4 25.9 24.1 6.3 3.4 1.4 4.2 0.0 1.7 4.4 0.260 0.324 0.475 0.800 98
Adam Jones BAL OF OF 17.4 25.3 6.4 27.4 26.3 7.4 3.5 1.2 4.1 0.4 1.0 5.0 0.280 0.320 0.470 0.790 100
Yoenis Cespedes BOS OF OF 17.2 27.5 5.2 22.4 21.2 5.8 3.1 1.1 3.7 0.4 1.0 5.2 0.275 0.323 0.500 0.823 99
Victor Martinez DET 1B 1B 17.1 33.1 6.7 29.3 27.4 8.6 4.0 1.0 4.4 0.1 1.7 2.7 0.316 0.376 0.492 0.867 100
Evan Longoria TB 3B 3B 16.9 19.1 5.7 24.8 23.0 6.4 3.4 1.2 4.0 0.1 1.8 5.1 0.277 0.355 0.503 0.858 100
J.D. Martinez DET OF OF 16.6 27.9 6.7 29.3 27.8 7.8 3.6 1.1 4.2 0.3 1.4 7.4 0.280 0.327 0.469 0.796 100
Ian Kinsler DET 2B 2B 16.5 22.9 6.7 30.5 28.8 7.8 4.1 0.8 3.3 0.8 1.6 3.7 0.271 0.324 0.422 0.745 100
Ben Zobrist TB 2B, SS, OF 2B, SS, OF 15.5 15.1 5.7 27.2 24.8 6.9 3.8 0.6 3.1 0.5 2.2 4.1 0.280 0.369 0.431 0.800 100
Mark Trumbo ARI 1B, OF 1B, OF 15.4 20.3 5.7 23.2 22.2 6.0 2.9 1.3 3.8 0.3 1.0 6.1 0.269 0.311 0.480 0.792 89
Robinson Cano SEA 2B 2B 15.1 19.0 6.7 26.4 25.0 7.5 3.4 0.8 3.8 0.3 1.3 3.3 0.300 0.358 0.461 0.818 100
Bryce Harper WAS OF OF 15.1 26.4 5.7 24.3 22.1 6.4 3.2 0.9 3.3 0.5 1.9 5.4 0.288 0.369 0.479 0.849 100
Carlos Santana CLE C, 1B, 3B C, 1B, 3B 14.7 14.4 5.7 24.5 21.6 5.4 3.1 0.9 3.2 0.2 2.7 5.1 0.251 0.367 0.436 0.803 100
Josh Donaldson OAK 3B 3B 14.7 27.3 6.3 28.1 25.8 6.9 3.6 1.1 3.9 0.3 2.2 5.6 0.268 0.353 0.460 0.812 100
Mookie Betts BOS OF 2B, OF 14.4 23.1 5.4 23.5 21.9 6.3 3.2 0.6 2.6 1.2 1.4 3.5 0.288 0.348 0.431 0.780 96
Carlos Beltran NYA OF OF 14.3 20.7 6.1 24.7 23.0 6.4 3.3 1.2 3.8 0.2 1.6 4.2 0.278 0.338 0.498 0.837 61
Matt Holliday STL OF OF 14.2 22.7 5.7 25.2 23.0 6.7 3.4 0.9 3.5 0.1 2.0 4.4 0.289 0.377 0.481 0.859 100
Carlos Gomez MIL OF OF 14.1 26.2 5.7 26.4 24.7 6.3 3.2 0.8 2.8 1.4 1.6 6.4 0.254 0.317 0.428 0.744 100
Torii Hunter DET OF OF 14.0 23.4 6.2 28.4 27.2 8.1 3.7 0.8 3.7 0.3 1.1 5.5 0.296 0.335 0.450 0.785 99
Jose Abreu CHA 1B 1B 13.8 33.3 6.5 27.3 25.5 6.9 3.5 1.5 4.1 0.1 1.6 6.6 0.271 0.342 0.516 0.857 100
Ryan Braun MIL OF OF 13.6 23.6 5.2 22.6 21.0 5.9 2.9 1.0 3.0 0.6 1.5 4.5 0.279 0.348 0.482 0.829 96
Desmond Jennings TB OF OF 12.9 14.7 5.7 27.2 25.1 6.5 3.6 0.7 2.8 1.0 1.8 5.6 0.258 0.334 0.409 0.742 62
Jason Heyward ATL OF OF 12.9 19.0 6.7 29.2 26.4 7.2 3.8 0.9 3.2 0.7 2.4 5.1 0.273 0.366 0.428 0.794 100
Dustin Pedroia BOS 2B 2B 12.7 16.5 5.7 25.9 24.2 6.8 3.3 0.6 3.0 0.5 1.6 2.9 0.282 0.348 0.426 0.774 69
Ian Desmond WAS SS SS 12.6 19.6 5.7 24.9 23.7 6.4 2.8 0.7 2.9 0.9 1.2 6.6 0.269 0.316 0.405 0.722 100
Albert Pujols LAA 1B 1B 12.5 18.4 5.7 24.1 22.7 6.4 3.1 1.1 3.6 0.2 1.3 2.9 0.280 0.344 0.481 0.825 100
Anthony Rendon WAS 2B, 3B 2B, 3B 12.4 19.3 5.4 25.2 23.6 6.7 3.3 0.6 2.7 0.4 1.4 4.3 0.282 0.349 0.429 0.778 100
Jayson Werth WAS OF OF 12.2 23.0 5.7 25.5 23.3 6.7 3.3 0.7 3.1 0.4 1.9 5.0 0.286 0.376 0.443 0.819 100
Jonathan Lucroy MIL C,1B C, 1B 11.9 9.2 5.7 25.3 23.5 6.4 2.8 0.6 2.7 0.3 1.6 3.2 0.271 0.341 0.418 0.759 100
Matt Kemp LAN OF OF 11.4 17.9 5.7 23.4 22.0 5.9 2.9 0.9 3.3 0.5 1.3 6.8 0.270 0.333 0.462 0.795 100
Leonys Martin TEX OF OF 11.2 17.4 6.3 27.9 26.6 7.3 3.1 0.6 2.9 1.4 1.3 5.7 0.273 0.326 0.409 0.735 98
Justin Upton ATL OF OF 11.2 16.6 6.7 27.8 25.1 6.8 3.4 1.0 3.6 0.4 2.4 7.1 0.273 0.367 0.455 0.822 100
Coco Crisp OAK OF OF 10.7 22.9 5.6 26.3 24.4 6.4 3.6 0.7 2.6 1.0 1.9 3.7 0.262 0.342 0.405 0.747 94
Hanley Ramirez LAN SS SS 10.6 13.0 5.2 21.0 19.5 5.3 2.6 0.7 2.6 0.6 1.2 3.5 0.270 0.339 0.442 0.781 100
Alejandro De Aza BAL OF OF 10.6 13.0 5.3 22.9 21.5 6.2 3.0 0.6 2.7 1.0 1.3 4.4 0.289 0.347 0.453 0.800 85
Derek Norris OAK C C 10.6 9.8 6.2 25.1 22.7 5.5 2.9 0.9 3.0 0.3 2.2 5.1 0.242 0.341 0.407 0.748 40
Freddie Freeman ATL 1B 1B 10.4 16.6 6.7 29.2 26.3 7.7 3.7 0.9 3.7 0.1 2.5 6.3 0.292 0.382 0.454 0.837 100
Josh Harrison PIT 2B, 3B, OF 2B, SS, 3B, OF 10.3 15.0 5.8 26.1 25.0 6.9 3.1 0.5 2.6 0.9 0.8 3.6 0.274 0.310 0.412 0.722 100
Yasiel Puig LAN OF OF 10.3 15.8 4.9 21.9 20.4 5.9 3.0 0.7 2.6 0.5 1.3 4.6 0.287 0.356 0.468 0.825 100
Nick Markakis BAL OF OF 10.3 10.8 6.4 29.3 27.4 7.8 4.0 0.7 3.0 0.2 1.7 3.2 0.285 0.357 0.436 0.793 92
Alex Gordon KC OF OF 10.1 15.4 6.7 27.6 25.4 6.7 3.4 1.0 3.5 0.5 1.9 6.3 0.266 0.342 0.450 0.793 100
Neil Walker PIT 2B 2B 9.9 13.2 6.4 27.2 25.4 6.9 3.2 0.9 3.4 0.2 1.6 4.9 0.271 0.338 0.434 0.771 99
Allen Craig BOS 1B, OF 1B, OF 9.8 15.6 5.4 22.4 20.9 5.9 2.9 0.8 3.2 0.1 1.1 4.5 0.284 0.342 0.467 0.809 48
Denard Span WAS OF OF 9.7 19.3 5.7 27.2 25.7 7.6 3.6 0.2 2.1 1.1 1.3 2.9 0.296 0.345 0.383 0.728 100
Dexter Fowler HOU OF OF 9.7 8.8 5.7 25.4 22.4 5.9 3.5 0.6 2.8 0.7 2.4 6.2 0.263 0.373 0.421 0.795 64
Corey Dickerson COL OF OF 9.6 12.8 5.3 22.9 21.5 5.7 2.8 0.8 2.9 0.5 1.2 4.8 0.263 0.320 0.474 0.794 100
Mike Napoli BOS 1B 1B 9.6 17.4 5.1 22.2 19.7 4.9 3.1 1.2 3.4 0.1 2.0 7.2 0.250 0.349 0.469 0.818 96
Javier Baez CHN 2B, SS 2B, SS 9.6 10.1 5.7 23.8 22.8 5.1 2.9 0.9 2.6 0.7 0.9 8.0 0.225 0.269 0.424 0.693 85
Miguel Montero ARI C C 9.4 4.8 5.4 21.4 19.8 5.4 2.6 0.6 2.7 0.2 1.6 4.2 0.273 0.355 0.422 0.777 76
Rajai Davis DET OF OF 9.3 18.6 5.9 23.5 22.4 6.3 3.0 0.3 2.4 1.7 0.8 4.0 0.281 0.317 0.394 0.711 99
Anthony Rizzo CHN 1B 1B 9.1 15.2 5.4 21.2 19.4 5.2 2.8 1.0 2.9 0.3 1.5 4.6 0.269 0.348 0.495 0.842 96
Jason Castro HOU C C 8.9 2.5 4.8 20.3 18.6 4.8 2.5 0.7 2.8 0.1 1.4 5.5 0.258 0.334 0.427 0.760 39
Adrian Gonzalez LAN 1B 1B 8.9 21.0 5.6 24.3 22.9 6.5 3.0 0.9 3.4 0.1 1.3 4.1 0.286 0.342 0.452 0.794 100
Steve Pearce BAL 1B, OF 1B, OF 8.7 14.0 5.0 20.7 18.9 5.1 2.8 0.9 2.8 0.3 1.6 4.0 0.271 0.349 0.458 0.807 62
Michael Cuddyer COL 1B, OF 1B, OF 8.6 9.0 5.7 23.5 21.9 6.2 2.8 0.7 3.0 0.4 1.2 4.2 0.281 0.341 0.452 0.793 86
Charlie Blackmon COL OF OF 8.4 11.2 5.5 25.9 24.6 6.5 3.1 0.7 2.4 0.9 1.4 4.6 0.265 0.310 0.409 0.720 100
Brian Dozier MIN 2B 2B 8.3 8.1 6.5 28.4 26.2 6.5 3.5 0.7 2.9 0.7 2.0 6.1 0.248 0.326 0.389 0.715 99
Jhonny Peralta STL SS SS 8.3 7.5 5.6 24.0 22.4 5.9 2.6 0.7 3.1 0.1 1.5 4.4 0.264 0.327 0.415 0.742 100
Buster Posey SF C,1B C, 1B 8.3 8.9 6.3 26.0 24.4 6.7 2.9 0.8 3.1 0.1 1.4 3.3 0.273 0.336 0.425 0.760 100
Mark Teixeira NYA 1B 1B 8.2 14.5 6.2 25.2 22.9 5.5 3.4 1.4 3.9 0.1 2.2 5.3 0.241 0.334 0.471 0.804 81
Aaron Hill ARI 2B 2B, 3B 8.1 6.2 5.7 23.2 22.2 6.0 2.7 0.7 2.8 0.3 0.9 3.4 0.269 0.315 0.432 0.747 61
David Wright NYN 3B 3B 8.1 11.9 5.7 23.9 22.5 6.2 2.8 0.6 2.8 0.4 1.3 4.5 0.274 0.342 0.423 0.764 71
Eric Hosmer KC 1B 1B 8.0 9.9 6.7 25.6 23.9 6.5 3.1 0.9 3.4 0.4 1.4 4.3 0.270 0.331 0.449 0.780 92
Billy Hamilton CIN OF OF 8.0 18.7 5.3 22.2 21.3 5.2 2.3 0.3 1.5 2.6 0.9 4.4 0.244 0.285 0.328 0.613 99
Wil Myers TB OF OF 7.8 6.9 5.1 21.7 20.1 5.3 2.7 0.8 2.9 0.3 1.5 4.7 0.261 0.334 0.441 0.776 89
Justin Morneau COL 1B 1B 7.8 11.8 5.5 24.3 22.8 6.3 2.9 0.9 3.3 0.1 1.4 3.3 0.278 0.342 0.480 0.822 96
Starling Marte PIT OF OF 7.8 16.7 6.7 26.2 25.0 6.7 3.1 0.6 2.8 1.4 1.3 6.1 0.266 0.320 0.420 0.740 100
Adam LaRoche WAS 1B 1B 7.7 16.2 5.7 24.3 21.9 5.8 3.0 0.9 3.3 0.1 2.0 4.8 0.264 0.365 0.451 0.816 100
Kole Calhoun LAA OF OF 7.7 10.2 5.5 25.6 24.2 6.4 3.3 0.7 2.7 0.4 1.4 4.7 0.264 0.324 0.423 0.747 100
Alex Rios TEX OF OF 7.6 13.2 6.3 24.9 24.0 6.8 2.7 0.6 3.0 1.0 0.9 4.3 0.281 0.318 0.430 0.748 76
Dee Gordon LAN 2B, SS 2B, SS 7.3 19.2 5.5 26.3 25.2 6.6 3.0 0.1 1.8 2.2 1.0 4.9 0.261 0.301 0.320 0.621 100
Wilin Rosario COL C C 6.9 3.8 4.5 18.5 17.8 4.7 2.1 0.7 2.5 0.1 0.7 3.5 0.262 0.307 0.450 0.758 61
Carl Crawford LAN OF OF 6.8 14.3 5.0 20.8 19.9 5.5 2.4 0.4 2.3 1.0 0.8 3.5 0.279 0.314 0.399 0.714 96
Asdrubal Cabrera WAS 2B, SS 2B, SS 6.6 7.9 5.7 23.8 22.1 5.9 2.8 0.6 2.5 0.4 1.3 4.1 0.266 0.332 0.409 0.741 99
Adam Lind TOR 1B 1B 6.5 14.2 6.1 23.2 21.7 6.1 3.0 1.0 3.7 0.0 1.2 4.5 0.282 0.336 0.475 0.811 68
Russell Martin PIT C C 6.4 1.2 6.0 24.9 22.5 5.3 2.6 0.7 2.7 0.3 2.1 5.5 0.236 0.328 0.368 0.696 65
Wilson Ramos WAS C C 6.4 7.1 4.5 18.2 17.5 4.9 1.9 0.6 2.4 0.1 0.7 2.8 0.279 0.321 0.427 0.749 76
Chris Owings ARI 2B, SS 2B, SS 6.4 5.9 5.1 22.4 21.8 6.0 2.5 0.4 2.5 0.6 0.4 4.1 0.276 0.296 0.406 0.702 27
Robbie Grossman HOU OF OF 6.3 5.2 4.9 22.7 20.6 5.5 2.9 0.5 2.3 0.7 2.0 5.4 0.266 0.353 0.390 0.744 2
Kyle Seager SEA 3B 3B 6.3 10.5 6.7 25.7 24.3 6.5 3.1 0.9 3.4 0.3 1.3 4.3 0.266 0.326 0.420 0.745 100
Yadier Molina STL C C, 1B 6.3 5.9 4.8 19.8 18.8 5.4 2.2 0.5 2.4 0.1 0.9 2.6 0.285 0.342 0.432 0.774 93
Elvis Andrus TEX SS SS 6.3 11.2 6.4 28.7 26.9 7.5 3.2 0.2 2.4 1.4 1.5 4.0 0.279 0.337 0.359 0.696 86
Austin Jackson SEA OF OF 6.1 10.6 6.7 29.2 27.5 7.3 3.6 0.5 2.8 0.7 1.5 6.7 0.266 0.329 0.388 0.717 94
Brett Gardner NYA OF OF 6.1 12.2 5.8 23.7 21.9 5.8 3.1 0.6 2.4 0.9 1.6 4.7 0.266 0.336 0.417 0.753 95
Matt Carpenter STL 2B, 3B 2B, 3B 6.1 6.0 5.7 26.4 24.1 6.7 3.5 0.4 2.3 0.3 2.1 4.3 0.280 0.371 0.404 0.775 100
Daniel Nava BOS OF 1B, OF 6.0 7.0 5.4 21.9 19.9 5.5 2.7 0.6 2.7 0.3 1.6 4.6 0.276 0.363 0.447 0.810 6
Brandon Moss OAK 1B, OF 1B, OF 6.0 17.5 6.5 24.8 22.9 5.6 3.1 1.1 3.5 0.1 1.8 6.8 0.246 0.328 0.451 0.779 76
Daniel Murphy NYN 2B 1B, 2B, 3B 5.9 5.8 5.7 24.5 23.9 6.9 2.7 0.4 2.4 0.5 0.6 3.4 0.290 0.318 0.395 0.712 86
Dioner Navarro TOR C C 5.8 4.4 5.4 21.0 19.7 5.3 2.5 0.7 2.6 0.1 0.9 3.5 0.268 0.319 0.409 0.728 57
Matt Adams STL 1B 1B 5.4 9.9 4.9 21.3 20.5 5.6 2.4 0.8 3.0 0.1 0.8 4.2 0.274 0.315 0.444 0.759 99
A.J. Pollock ARI OF OF 5.4 7.6 4.5 18.8 18.1 5.2 2.3 0.4 2.1 0.7 0.7 3.2 0.286 0.320 0.417 0.737 65
Danny Santana MIN SS, OF SS, OF 5.3 7.5 6.0 27.2 26.1 7.1 3.1 0.3 2.2 1.1 0.8 5.9 0.270 0.301 0.369 0.671 99
Joe Mauer MIN C,1B C, 1B 5.3 2.6 6.5 27.8 25.4 7.2 3.2 0.4 3.0 0.1 2.1 5.0 0.281 0.370 0.399 0.770 100
Michael Brantley CLE OF OF 5.2 13.5 5.6 24.1 22.6 6.4 2.7 0.4 2.6 0.6 1.3 2.9 0.281 0.341 0.400 0.741 100
Evan Gattis ATL C, OF C, OF 5.1 4.6 5.3 22.0 20.6 5.2 2.3 0.9 2.9 0.0 1.1 5.9 0.251 0.311 0.446 0.757 89
Jonathan Villar HOU SS SS 5.1 2.9 5.1 18.4 17.1 4.2 2.2 0.5 2.0 1.3 1.1 5.4 0.244 0.308 0.371 0.678 14
Pedro Alvarez PIT 3B 1B, 3B 5.0 10.7 6.3 23.6 22.1 5.4 2.7 1.1 3.3 0.3 1.4 7.2 0.245 0.310 0.440 0.750 57
Yan Gomes CLE C C 5.0 3.3 4.5 18.5 17.6 4.9 2.1 0.7 2.4 0.0 0.7 4.4 0.277 0.313 0.446 0.759 96
Howie Kendrick LAA 2B 2B 4.9 2.9 5.7 24.1 22.9 6.4 2.6 0.4 2.6 0.4 1.1 4.5 0.278 0.328 0.397 0.725 100
Christian Yelich MIA OF OF 4.9 9.2 5.7 26.6 24.7 6.7 3.2 0.4 2.1 0.9 1.6 6.0 0.269 0.333 0.379 0.713 100
Jason Kipnis CLE 2B 2B 4.8 8.7 5.3 21.9 20.5 5.0 2.5 0.5 2.2 0.7 1.4 4.9 0.244 0.323 0.370 0.693 99
Kolten Wong STL 2B 2B 4.5 4.0 4.9 19.8 19.0 5.0 2.1 0.4 2.1 0.7 0.8 3.1 0.264 0.309 0.375 0.684 98
Kelly Johnson BAL 1B, 2B, 3B, OF 1B, 2B, 3B, OF 4.4 3.3 3.5 14.2 12.9 3.3 1.9 0.6 1.9 0.3 1.2 3.6 0.256 0.333 0.442 0.775 10
Rougned Odor TEX 2B 2B 4.3 2.6 6.2 24.5 23.7 6.1 2.5 0.6 2.7 0.7 0.8 4.1 0.260 0.298 0.398 0.696 42
Aramis Ramirez MIL 3B 3B 4.3 10.2 5.7 24.2 22.5 6.1 2.7 0.8 3.0 0.1 1.4 3.6 0.270 0.331 0.438 0.770 98
Will Middlebrooks BOS 3B 3B 4.2 7.0 4.6 18.2 17.3 4.3 2.1 0.8 2.6 0.2 0.8 4.7 0.249 0.290 0.433 0.723 23
Jay Bruce CIN OF OF 4.2 6.6 5.0 19.0 17.6 4.3 2.2 0.9 2.5 0.3 1.2 5.1 0.245 0.313 0.442 0.755 93
Lucas Duda NYN 1B, OF 1B, OF 4.0 6.1 5.4 22.7 20.6 5.2 2.5 0.9 2.9 0.1 1.8 5.6 0.250 0.334 0.414 0.747 100
Josh Reddick OAK OF OF 3.8 14.2 6.4 25.2 23.4 5.9 2.9 0.9 3.3 0.3 1.7 4.6 0.251 0.315 0.427 0.742 52
Todd Frazier CIN 1B, 3B 1B, 3B 3.8 7.3 5.7 23.5 21.9 5.1 2.4 0.8 2.6 0.6 1.2 5.3 0.235 0.293 0.399 0.692 100
Chase Headley NYA 3B 1B, 3B 3.8 5.2 5.8 20.8 19.2 5.2 2.6 0.7 2.7 0.3 1.6 5.0 0.270 0.346 0.447 0.793 81
Ender Inciarte ARI OF OF 3.8 5.7 5.4 23.1 22.4 6.2 2.6 0.2 2.1 1.0 0.8 3.3 0.277 0.309 0.368 0.677 38
Brock Holt BOS 2B, SS, 3B, OF 1B,3B,OF 3.7 4.4 3.5 17.2 16.2 4.7 2.2 0.1 1.5 0.5 0.7 3.0 0.287 0.341 0.418 0.759 56
David Peralta ARI OF OF 3.7 4.9 3.6 14.6 14.3 4.2 1.8 0.4 1.9 0.2 0.4 2.0 0.293 0.326 0.452 0.778 17
Kendrys Morales SEA 1B 1B 3.5 10.1 6.7 25.7 24.5 6.5 3.1 1.0 3.8 0.0 1.3 5.0 0.264 0.316 0.430 0.746 58
Jon Singleton HOU 1B 1B 3.5 0.1 5.4 21.1 18.6 4.4 2.6 0.9 2.8 0.2 2.1 6.6 0.235 0.344 0.417 0.761 40
Colby Rasmus TOR OF OF 3.5 5.6 5.3 20.0 18.6 4.5 2.5 0.9 2.8 0.1 1.2 6.2 0.242 0.302 0.441 0.743 54
Derek Jeter NYA SS SS 3.4 5.8 6.2 26.5 25.2 6.8 3.1 0.4 2.5 0.4 1.1 4.3 0.271 0.323 0.368 0.692 20
Jorge Soler CHN OF OF 3.4 5.1 4.2 16.5 15.5 4.1 1.9 0.6 2.3 0.1 0.8 4.0 0.266 0.321 0.476 0.797 95
Khris Davis MIL OF OF 3.3 7.3 5.3 22.5 20.8 5.1 2.4 0.8 2.7 0.3 1.5 5.0 0.243 0.314 0.430 0.744 88
Jake Marisnick HOU OF OF 3.3 2.3 4.9 19.3 18.2 4.7 2.2 0.4 2.2 0.9 0.8 4.6 0.255 0.303 0.394 0.697 2
Xander Bogaerts BOS SS, 3B SS, 3B 3.3 2.4 4.6 18.7 17.5 4.5 2.2 0.5 2.2 0.2 0.9 4.5 0.256 0.310 0.404 0.714 95
Josh Hamilton LAA OF OF 3.1 3.4 5.1 20.6 19.2 4.8 2.4 0.7 2.6 0.2 1.3 5.5 0.252 0.316 0.419 0.736 80
Drew Stubbs COL OF OF 3.0 3.2 3.8 16.4 15.3 3.9 1.9 0.4 1.7 0.7 1.0 4.8 0.256 0.318 0.392 0.710 67
Arismendy Alcantara CHN 2B, OF 2B, OF 3.0 1.9 5.4 20.9 19.9 4.9 2.1 0.5 2.0 0.8 0.7 5.9 0.246 0.287 0.385 0.672 69
Jimmy Paredes BAL 3B, OF 3B, OF 2.9 2.5 3.5 13.9 13.3 3.6 1.5 0.4 1.5 0.5 0.6 3.3 0.267 0.303 0.418 0.721 0
Stephen Vogt OAK C, 1B, OF C, 1B, OF 2.9 3.8 3.1 12.6 12.0 3.3 1.6 0.3 1.6 0.1 0.6 1.8 0.273 0.327 0.433 0.760 37
Kevin Kiermaier TB OF OF 2.8 2.7 4.0 15.6 14.8 4.1 2.0 0.3 1.8 0.6 0.8 3.0 0.274 0.327 0.415 0.742 15
Kennys Vargas MIN 1B 1B 2.6 8.2 6.3 28.2 26.6 6.7 3.1 1.0 3.6 0.0 1.4 6.0 0.250 0.307 0.409 0.716 99
Oswaldo Arcia MIN OF OF 2.6 4.6 6.1 24.3 22.7 5.6 2.7 0.9 3.0 0.2 1.3 7.3 0.246 0.307 0.425 0.732 64
Nick Castellanos DET 3B 3B, OF 2.5 7.3 6.5 28.1 26.7 7.2 3.0 0.7 3.2 0.2 1.3 6.9 0.269 0.317 0.409 0.726 81
Travis d’Arnaud NYN C C 2.3 -0.4 5.2 20.4 19.5 4.9 2.1 0.6 2.4 0.1 1.0 3.3 0.251 0.302 0.405 0.707 38
J.J. Hardy BAL SS SS 2.3 -0.3 5.3 20.8 19.9 5.0 2.2 0.6 2.4 0.1 0.8 3.2 0.253 0.302 0.399 0.701 89
Nolan Arenado COL 3B 3B 2.3 0.7 5.0 21.4 20.5 5.6 2.3 0.5 2.5 0.1 0.7 2.8 0.271 0.315 0.422 0.737 100
Ryan Rua TEX 1B 1B, OF 2.2 3.5 4.3 17.4 16.6 4.2 1.9 0.6 2.0 0.3 0.9 3.3 0.256 0.312 0.405 0.717 0
Alex Presley HOU OF OF 2.1 1.9 2.6 9.2 8.8 2.6 1.3 0.3 1.2 0.3 0.5 1.2 0.296 0.352 0.460 0.813 0
Josh Rutledge COL 2B, SS 2B, SS, 3B 2.0 -1.7 4.8 19.3 18.4 4.9 2.1 0.4 1.9 0.4 0.9 4.4 0.267 0.316 0.395 0.710 29
Norichika Aoki KC OF OF 2.0 5.1 5.3 22.0 20.5 5.8 2.6 0.3 1.8 0.7 1.2 1.7 0.281 0.344 0.395 0.739 55
Matt Joyce TB OF OF 1.9 0.7 5.3 20.4 18.5 4.6 2.6 0.6 2.6 0.2 1.6 4.7 0.251 0.347 0.425 0.772 35
Christian Vazquez BOS C C 1.9 -3.4 4.4 17.3 16.3 4.1 1.9 0.3 1.7 0.2 0.9 3.2 0.251 0.302 0.358 0.661 1
Michael McKenry COL C C 1.8 -1.3 3.5 14.1 13.1 3.4 1.5 0.4 1.6 0.1 0.9 3.0 0.256 0.328 0.410 0.739 1
Ryan Flaherty BAL 2B, SS, 3B 2B, SS, 3B 1.8 0.2 3.2 13.4 12.6 3.0 1.5 0.4 1.6 0.1 0.8 3.0 0.241 0.305 0.414 0.719 5
J.P. Arencibia TEX C,1B C, 1B 1.8 1.6 2.9 11.1 10.7 2.4 1.2 0.6 1.6 0.0 0.4 3.2 0.226 0.272 0.428 0.700 10
Curtis Granderson NYN OF OF 1.8 3.5 5.5 22.7 20.9 4.9 2.6 0.8 2.5 0.3 1.7 6.5 0.234 0.313 0.397 0.709 77
Jarrod Dyson KC OF OF 1.7 2.9 3.5 13.5 12.7 3.2 1.5 0.1 1.1 1.3 0.8 2.8 0.249 0.307 0.351 0.658 45
Chris Coghlan CHN OF 3B, OF 1.7 2.3 4.7 20.4 19.0 5.0 2.4 0.3 1.9 0.5 1.1 4.2 0.264 0.332 0.397 0.729 24
Gregory Polanco PIT OF OF 1.7 6.1 6.0 23.5 22.3 5.8 2.6 0.4 2.2 1.0 1.2 4.0 0.260 0.308 0.372 0.680 42
Salvador Perez KC C C 1.7 4.5 6.7 27.6 26.4 6.8 2.8 0.7 3.1 0.0 0.8 3.9 0.259 0.290 0.392 0.682 95
Matt Dominguez HOU 3B 3B 1.7 0.0 4.5 17.5 16.5 4.1 2.0 0.7 2.3 0.1 0.7 3.3 0.247 0.297 0.409 0.706 15
Jed Lowrie OAK 2B, SS 2B, SS 1.6 3.4 6.7 26.9 25.0 6.6 3.0 0.6 2.9 0.0 1.8 4.2 0.262 0.334 0.396 0.730 73
Hunter Pence SF OF OF 1.6 6.2 6.7 27.7 26.3 6.7 3.0 0.7 2.8 0.5 1.3 6.1 0.253 0.301 0.394 0.695 100
James Loney TB 1B 1B 1.5 1.2 5.5 22.8 21.7 6.2 2.6 0.4 2.7 0.1 1.0 2.7 0.284 0.337 0.410 0.747 88
Kevin Pillar TOR OF OF 1.5 3.5 4.2 16.2 15.5 4.4 1.8 0.3 1.8 0.6 0.5 2.5 0.282 0.305 0.399 0.704 0
Jose Ramirez CLE 2B, SS 2B, SS 1.5 6.4 5.4 24.7 23.7 6.2 2.6 0.1 2.2 1.0 0.9 3.4 0.260 0.301 0.342 0.643 58
Eduardo Nunez MIN SS, 3B, OF SS, 3B, OF 1.4 1.7 2.4 10.8 10.3 2.8 1.1 0.2 1.2 0.3 0.4 2.1 0.276 0.319 0.392 0.711 1
Devin Mesoraco CIN C C 1.4 -0.2 4.5 17.6 16.4 3.8 1.8 0.6 2.1 0.1 1.0 4.1 0.228 0.291 0.402 0.693 100
Marwin Gonzalez HOU 2B, SS, 3B 2B, SS, 3B 1.4 -0.8 3.6 14.4 13.6 3.6 1.6 0.3 1.4 0.4 0.6 2.1 0.265 0.313 0.391 0.704 1
Chris Young NYA OF OF 1.3 3.3 2.6 10.3 9.5 2.2 1.3 0.5 1.4 0.3 0.8 2.8 0.230 0.309 0.416 0.724 60
Dustin Ackley SEA 2B, OF 1B, 2B, OF 1.3 1.0 5.5 23.0 21.6 5.6 2.6 0.4 2.4 0.3 1.2 4.0 0.257 0.316 0.377 0.692 57
David Ross BOS C C 1.2 0.4 1.6 6.1 5.6 1.2 0.8 0.3 0.8 0.1 0.3 2.3 0.216 0.287 0.386 0.673 0
Logan Morrison SEA 1B 1B, OF 1.2 3.3 4.3 15.8 14.8 3.8 1.9 0.7 2.1 0.1 1.0 3.5 0.258 0.328 0.417 0.745 7
Tomas Telis TEX C C 1.1 -2.2 3.8 15.5 15.1 4.1 1.3 0.2 1.6 0.2 0.4 2.0 0.269 0.294 0.367 0.662 0
Rickie Weeks MIL 2B 2B 1.0 1.2 2.0 8.5 7.6 1.9 1.1 0.3 1.0 0.0 0.8 3.0 0.247 0.337 0.410 0.747 4
Alexei Ramirez CHA SS SS 1.0 4.9 6.5 27.1 26.3 6.8 2.6 0.4 2.5 0.8 0.8 3.2 0.260 0.289 0.361 0.650 96
Andre Ethier LAN OF OF 0.9 3.6 4.5 19.1 17.8 4.7 2.0 0.4 2.2 0.1 1.1 3.5 0.262 0.330 0.397 0.727 11
Nick Hundley BAL C C 0.9 -0.6 2.9 11.0 10.5 2.5 1.2 0.3 1.2 0.1 0.5 2.9 0.240 0.293 0.387 0.680 0
Mike Zunino SEA C C 0.8 -1.3 4.1 14.6 14.0 3.0 1.6 0.6 1.9 0.1 0.8 4.6 0.214 0.267 0.382 0.649 27
Corey Hart SEA 1B OF 0.8 3.1 6.0 20.7 19.6 5.1 2.6 0.8 2.9 0.1 1.2 4.8 0.260 0.316 0.438 0.754 24
Christian Bethancourt ATL C C 0.7 -1.0 2.0 8.1 7.8 1.9 0.7 0.1 0.7 0.2 0.3 1.9 0.249 0.284 0.340 0.624 0
Luis Valbuena CHN 2B, 3B 2B, 3B 0.7 -1.4 5.3 20.8 19.1 4.7 2.2 0.6 2.3 0.1 1.6 4.7 0.246 0.327 0.408 0.735 62
Jedd Gyorko SD 2B 2B, 3B 0.7 -2.9 5.9 24.4 22.9 5.5 2.3 0.7 2.7 0.2 1.3 5.3 0.238 0.296 0.380 0.676 68
Randal Grichuk STL OF OF 0.6 0.7 1.7 7.4 7.1 1.8 0.9 0.3 1.1 0.0 0.3 1.9 0.247 0.291 0.425 0.715 0
Pablo Sandoval SF 3B 3B 0.6 3.4 6.6 26.7 25.2 6.5 2.8 0.9 3.4 0.0 1.2 4.9 0.260 0.309 0.433 0.741 100
Ben Revere PHI OF OF 0.6 6.3 5.5 25.3 24.6 6.7 2.5 0.0 1.6 1.3 0.8 2.2 0.271 0.304 0.297 0.601 100
Brandon Guyer TB OF OF 0.6 0.6 2.6 10.9 10.3 2.8 1.2 0.2 1.2 0.2 0.5 1.9 0.268 0.319 0.400 0.719 0
David Lough BAL OF OF 0.6 0.7 1.5 6.3 6.0 1.7 0.7 0.2 0.7 0.2 0.3 0.9 0.277 0.324 0.425 0.749 1
Emilio Bonifacio ATL 2B, OF 2B, 3B, OF 0.5 -0.1 3.0 12.9 12.2 3.1 1.3 0.0 0.9 0.7 0.7 3.1 0.259 0.316 0.323 0.639 36
Robinson Chirinos TEX C C 0.5 -0.4 2.6 10.1 9.5 2.4 1.0 0.3 1.1 0.1 0.6 1.8 0.251 0.310 0.399 0.709 2
Ezequiel Carrera DET OF OF 0.4 0.7 0.8 3.6 3.4 1.0 0.3 0.1 0.3 0.2 0.2 0.5 0.279 0.337 0.375 0.712 1
Erick Aybar LAA SS SS 0.4 -1.6 5.7 22.4 21.4 5.8 2.3 0.3 2.2 0.6 0.9 2.9 0.271 0.314 0.374 0.687 100
Cody Ross ARI OF OF 0.4 -0.7 4.5 17.0 16.2 4.4 1.9 0.4 2.0 0.1 0.7 3.5 0.273 0.317 0.420 0.737 0
Marc Krauss HOU 1B, OF 1B, OF 0.3 0.1 1.3 4.8 4.4 1.1 0.7 0.2 0.7 0.0 0.4 1.4 0.251 0.344 0.434 0.777 0
Matt McBride COL OF 1B 0.3 0.0 1.5 5.1 5.0 1.4 0.6 0.2 0.8 0.0 0.2 0.3 0.277 0.313 0.451 0.764 0
Stefen Romero SEA OF OF 0.2 0.2 1.1 3.7 3.6 1.0 0.5 0.2 0.5 0.0 0.1 0.3 0.270 0.297 0.413 0.710 0
Josmil Pinto MIN C C 0.2 0.0 1.3 5.7 5.2 1.4 0.6 0.2 0.6 0.0 0.3 0.9 0.267 0.334 0.414 0.748 2
Brennan Boesch LAA OF OF 0.2 0.1 2.0 7.5 7.1 1.8 0.8 0.2 0.9 0.2 0.4 1.7 0.251 0.300 0.407 0.706 0
Travis Snider PIT OF OF 0.2 1.1 3.9 14.8 14.0 3.6 1.6 0.5 1.7 0.1 0.8 3.3 0.256 0.317 0.408 0.725 10
Dayan Viciedo CHA OF OF 0.2 6.0 6.2 25.1 24.0 5.8 2.5 0.9 3.0 0.1 1.1 5.9 0.242 0.288 0.405 0.693 49
Juan Francisco TOR 1B, 3B 1B, 3B 0.1 0.1 1.0 3.3 3.1 0.7 0.4 0.2 0.5 0.0 0.2 1.1 0.233 0.294 0.457 0.751 19
Ryan Raburn CLE OF OF 0.1 0.1 1.1 4.0 3.8 0.9 0.5 0.2 0.6 0.0 0.2 1.7 0.250 0.306 0.422 0.728 0
Andrew Lambo PIT OF OF 0.1 0.3 1.6 5.8 5.5 1.4 0.6 0.2 0.7 0.1 0.3 1.3 0.257 0.304 0.427 0.731 0
Omar Infante KC 2B 2B 0.1 1.3 6.0 25.5 24.4 6.4 2.7 0.3 2.4 0.4 0.9 3.6 0.261 0.299 0.366 0.666 39
Nate Schierholtz WAS OF OF 0.1 0.2 0.9 3.6 3.5 0.9 0.4 0.1 0.4 0.1 0.2 0.7 0.254 0.304 0.405 0.709 8
John Mayberry TOR 1B, OF 1B, OF 0.1 0.2 0.9 3.2 3.0 0.8 0.4 0.1 0.5 0.0 0.2 1.3 0.248 0.314 0.426 0.740 0
Ike Davis PIT 1B 1B 0.1 1.4 3.5 11.6 10.4 2.7 1.4 0.5 1.6 0.1 1.1 2.5 0.257 0.356 0.451 0.807 11
Delmon Young BAL OF OF 0.1 0.5 2.0 7.8 7.5 2.0 0.9 0.2 1.0 0.0 0.3 1.4 0.267 0.308 0.417 0.725 0
Max Stassi HOU C C 0.1 0.0 0.6 2.3 2.2 0.5 0.3 0.1 0.3 0.0 0.1 0.6 0.234 0.282 0.371 0.653 0
Joc Pederson LAN OF OF 0.1 0.3 0.8 3.5 3.2 0.7 0.3 0.1 0.3 0.1 0.3 0.5 0.233 0.317 0.374 0.691 18
Jesus Guzman HOU 1B, OF 1B, OF 0.1 0.1 0.8 2.7 2.5 0.7 0.3 0.1 0.4 0.0 0.2 1.0 0.265 0.326 0.411 0.737 0
JR Murphy NYA C C 0.1 0.1 0.7 2.9 2.7 0.6 0.3 0.1 0.4 0.0 0.1 1.1 0.235 0.287 0.380 0.666 0
Daniel Butler BOS C C 0.0 0.0 0.3 1.2 1.1 0.3 0.1 0.0 0.1 0.0 0.1 0.3 0.239 0.300 0.377 0.677 0
Hernan Perez DET 2B 2B 0.0 0.0 0.4 1.2 1.2 0.3 0.1 0.0 0.1 0.0 0.0 0.2 0.262 0.297 0.362 0.659 0
Tyler Moore WAS 1B, OF 1B, OF 0.0 0.0 0.3 1.1 1.0 0.3 0.1 0.0 0.1 0.0 0.1 0.3 0.249 0.309 0.406 0.714 0
Nick Franklin TB 2B 2B, SS 0.0 0.0 0.5 2.0 1.9 0.5 0.2 0.0 0.2 0.1 0.1 0.4 0.257 0.323 0.384 0.707 2
Carlos Rivero BOS SS SS 0.0 0.0 0.3 1.2 1.2 0.3 0.1 0.0 0.1 0.0 0.1 0.3 0.251 0.292 0.373 0.665 0
Nick Ahmed ARI SS SS 0.0 0.0 0.3 1.2 1.2 0.3 0.1 0.0 0.1 0.0 0.0 0.1 0.258 0.290 0.349 0.638 0
Steve Clevenger BAL C C 0.0 0.0 0.4 1.2 1.2 0.3 0.1 0.0 0.1 0.0 0.1 0.2 0.281 0.337 0.407 0.744 0
Sandy Leon WAS C C 0.0 -0.1 0.3 1.1 1.0 0.2 0.1 0.0 0.1 0.0 0.1 0.2 0.223 0.292 0.305 0.597 0
Michael Taylor WAS OF OF 0.0 0.0 0.3 1.2 1.2 0.3 0.1 0.0 0.1 0.1 0.1 0.3 0.239 0.290 0.338 0.628 1
James Jones SEA OF OF 0.0 0.0 0.7 2.5 2.4 0.6 0.2 0.0 0.2 0.1 0.1 0.4 0.245 0.285 0.335 0.620 8
Paul Konerko CHA 1B 1B 0.0 0.5 1.4 5.6 5.3 1.4 0.6 0.2 0.6 0.0 0.3 0.4 0.256 0.316 0.402 0.718 1
Jordany Valdespin MIA 2B, OF 2B, OF 0.0 0.0 0.6 1.9 1.8 0.5 0.2 0.0 0.2 0.1 0.1 0.3 0.267 0.306 0.376 0.682 0
A.J. Pierzynski STL C C 0.0 -0.2 1.0 4.3 4.2 1.1 0.4 0.1 0.5 0.0 0.1 0.7 0.266 0.293 0.368 0.662 14
Michael Saunders SEA OF OF 0.0 0.1 1.1 3.9 3.6 0.9 0.5 0.1 0.5 0.1 0.2 1.0 0.246 0.325 0.410 0.735 8
Tyler Collins DET OF OF 0.0 0.0 0.4 1.2 1.2 0.3 0.1 0.0 0.1 0.0 0.1 0.1 0.247 0.297 0.373 0.671 0
Grant Green LAA 2B, OF 2B, 3B, OF 0.0 0.0 0.4 1.3 1.2 0.3 0.1 0.0 0.1 0.0 0.0 0.2 0.270 0.305 0.375 0.679 1
Shawn O’Malley LAA SS SS 0.0 0.0 0.3 1.2 1.1 0.3 0.1 0.0 0.1 0.0 0.1 0.3 0.242 0.303 0.316 0.618 0
Michael Choice TEX OF OF 0.0 0.6 4.1 15.1 14.1 3.6 1.7 0.5 1.7 0.1 1.0 3.2 0.256 0.325 0.411 0.736 0
Tony Campana LAA OF OF 0.0 0.0 0.3 1.4 1.3 0.3 0.1 0.0 0.1 0.1 0.1 0.2 0.236 0.285 0.290 0.574 0
Steven Souza WAS OF OF 0.0 0.1 0.3 1.1 1.0 0.3 0.1 0.0 0.1 0.1 0.1 0.3 0.271 0.329 0.404 0.733 0
Jordan Pacheco ARI C,1B C, 1B 0.0 0.0 0.3 1.0 1.0 0.3 0.1 0.0 0.1 0.0 0.0 0.0 0.265 0.297 0.358 0.655 0
Carlos Peguero KC OF OF 0.0 0.1 0.7 2.4 2.3 0.6 0.3 0.1 0.3 0.0 0.1 1.0 0.242 0.299 0.446 0.746 0
Luis Jimenez LAA 3B 3B 0.0 0.0 0.3 1.1 1.0 0.3 0.1 0.0 0.1 0.0 0.0 0.2 0.244 0.277 0.367 0.644 0
Jeff Kobernus WAS OF OF 0.0 0.0 0.3 1.1 1.0 0.3 0.1 0.0 0.1 0.1 0.0 0.2 0.271 0.314 0.330 0.644 0
Xavier Scruggs STL 1B 1B 0.0 0.0 0.5 1.6 1.5 0.4 0.2 0.1 0.2 0.0 0.1 0.6 0.241 0.315 0.403 0.719 0
Brett Jackson ARI OF OF 0.0 0.0 0.3 1.0 1.0 0.2 0.1 0.0 0.1 0.0 0.1 0.3 0.238 0.300 0.385 0.685 0
Nolan Reimold ARI OF OF 0.0 0.0 0.3 1.1 1.0 0.2 0.1 0.0 0.1 0.0 0.1 0.3 0.235 0.298 0.398 0.696 0
Scott Hairston WAS OF OF 0.0 0.0 0.3 1.1 1.0 0.2 0.1 0.0 0.1 0.0 0.0 0.3 0.241 0.280 0.378 0.659 0
Cameron Rupp PHI C C 0.0 0.0 0.3 1.1 1.0 0.2 0.1 0.0 0.1 0.0 0.1 0.5 0.214 0.271 0.305 0.576 0
Christian Walker BAL 1B 1B 0.0 0.0 0.4 1.2 1.2 0.3 0.1 0.0 0.2 0.0 0.1 0.3 0.254 0.306 0.399 0.704 0
Carlos Corporan HOU C C 0.0 -0.5 1.0 3.9 3.6 0.9 0.4 0.1 0.5 0.0 0.2 1.3 0.237 0.296 0.382 0.678 0
Ben Paulsen COL 1B 1B 0.0 -0.1 0.7 2.5 2.3 0.6 0.2 0.1 0.2 0.0 0.1 0.4 0.238 0.298 0.402 0.699 2
Jayson Nix KC 2B, SS, 3B 2B, SS, 3B 0.0 -0.2 0.4 1.2 1.1 0.2 0.1 0.0 0.1 0.0 0.1 0.4 0.211 0.266 0.318 0.584 0
Moises Sierra CHA OF OF 0.0 0.0 0.5 1.6 1.5 0.4 0.2 0.1 0.2 0.0 0.1 0.6 0.234 0.280 0.365 0.644 0
Erik Kratz KC C C 0.0 0.0 0.4 1.2 1.1 0.3 0.1 0.0 0.1 0.0 0.1 0.4 0.227 0.280 0.384 0.663 0
Enrique Hernandez MIA OF SS, OF 0.0 -0.1 0.4 1.3 1.2 0.3 0.1 0.0 0.1 0.0 0.0 0.3 0.250 0.288 0.341 0.629 0
Austin Romine NYA C C 0.0 0.0 0.4 1.2 1.2 0.3 0.1 0.1 0.2 0.0 0.1 0.5 0.238 0.289 0.367 0.656 0
Jesus Aguilar CLE 1B 1B 0.0 0.1 0.9 3.2 3.0 0.7 0.4 0.2 0.5 0.0 0.2 1.2 0.249 0.318 0.401 0.719 0
Chris Herrmann MIN C, OF C, OF 0.0 -0.2 0.6 2.0 1.9 0.4 0.1 0.0 0.1 0.0 0.1 0.3 0.227 0.293 0.329 0.622 0
Ryan Doumit ATL C, OF C, OF -0.1 -0.2 0.9 3.7 3.5 0.8 0.4 0.0 0.4 0.0 0.2 0.5 0.244 0.308 0.374 0.682 0
Donald Lutz CIN OF 1B, OF -0.1 -0.1 0.8 2.8 2.7 0.6 0.2 0.1 0.3 0.1 0.1 1.2 0.232 0.267 0.367 0.634 0
Kevin Frandsen WAS 1B, 2B, 3B, OF 1B, 2B, 3B, OF -0.1 -0.2 0.6 2.3 2.2 0.6 0.2 0.0 0.2 0.0 0.1 0.4 0.284 0.319 0.350 0.669 0
Danny Espinosa WAS 2B 2B, SS -0.1 -0.2 0.6 2.3 2.2 0.5 0.2 0.0 0.2 0.1 0.1 0.8 0.228 0.288 0.346 0.634 6
Chris Gimenez CLE C C, 1B -0.1 -0.1 0.4 1.5 1.4 0.3 0.1 0.0 0.1 0.0 0.1 0.5 0.249 0.315 0.346 0.661 0
Logan Schafer MIL OF OF -0.1 -0.1 0.5 1.9 1.8 0.4 0.1 0.0 0.1 0.0 0.1 0.3 0.223 0.294 0.324 0.618 0
Alex Avila DET C C -0.1 -1.8 5.1 21.0 18.9 4.4 2.3 0.5 2.3 0.1 1.9 6.9 0.232 0.326 0.367 0.694 2
Kirk Nieuwenhuis NYN OF OF -0.1 -0.1 1.0 4.2 4.0 0.9 0.4 0.1 0.4 0.1 0.2 1.2 0.234 0.292 0.381 0.673 1
Ramiro Pena ATL 2B, SS, 3B 2B, SS, 3B -0.1 -0.1 0.6 2.0 1.8 0.5 0.2 0.0 0.2 0.0 0.1 0.4 0.249 0.309 0.326 0.635 0
Tuffy Gosewisch ARI C C -0.1 -0.1 0.6 2.3 2.3 0.5 0.2 0.1 0.3 0.0 0.1 0.5 0.233 0.266 0.345 0.610 0
Zach Walters CLE 3B OF -0.1 0.9 3.1 11.5 10.9 2.6 1.3 0.5 1.5 0.1 0.5 2.8 0.241 0.277 0.420 0.697 6
James McCann DET C C -0.1 -0.2 0.8 2.7 2.6 0.7 0.3 0.0 0.3 0.0 0.1 0.2 0.256 0.284 0.358 0.642 0
Jemile Weeks BOS 2B 2B -0.1 -0.2 1.1 4.2 3.8 1.1 0.5 0.0 0.4 0.1 0.2 0.9 0.282 0.345 0.410 0.755 1
Craig Gentry OAK OF OF -0.1 0.3 1.8 7.2 6.7 1.8 0.7 0.0 0.6 0.4 0.5 1.4 0.262 0.341 0.346 0.687 0
Tucker Barnhart CIN C C -0.1 -0.2 0.5 1.6 1.6 0.4 0.1 0.0 0.1 0.0 0.1 0.5 0.227 0.278 0.305 0.583 0
Doug Bernier MIN SS SS, 3B -0.1 -0.1 0.5 1.8 1.6 0.4 0.2 0.0 0.2 0.0 0.1 0.3 0.256 0.317 0.344 0.660 0
Yorman Rodriguez CIN OF OF -0.1 -0.2 0.5 1.7 1.7 0.4 0.1 0.0 0.1 0.0 0.1 0.5 0.213 0.247 0.304 0.551 0
Justin Turner LAN 2B, SS, 3B 1B, 2B, SS, 3B -0.1 -1.1 3.3 13.4 12.7 3.4 1.4 0.2 1.3 0.2 0.7 2.3 0.265 0.317 0.365 0.681 40
Caleb Joseph BAL C C -0.1 -3.3 4.1 14.8 14.1 3.4 1.5 0.4 1.5 0.1 0.6 3.2 0.243 0.285 0.362 0.647 2
Jake Elmore CIN SS 2B, SS, OF -0.1 -0.2 0.5 1.6 1.5 0.4 0.1 0.0 0.1 0.1 0.1 0.5 0.229 0.292 0.302 0.594 0
Nick Punto OAK 2B, SS, 3B 2B, SS, 3B -0.1 -0.2 0.6 2.2 2.0 0.5 0.2 0.0 0.2 0.0 0.2 0.2 0.239 0.319 0.307 0.626 0
Tim Federowicz LAN C C -0.1 -0.1 0.4 1.5 1.4 0.3 0.1 0.0 0.1 0.0 0.1 0.2 0.225 0.278 0.346 0.625 0
Ed Lucas MIA 1B, 2B, SS, 3B 1B, 2B, SS, 3B, OF -0.1 -0.1 0.4 1.3 1.2 0.3 0.1 0.0 0.1 0.0 0.0 0.3 0.242 0.283 0.314 0.597 0
Michael Taylor CHA OF OF -0.1 0.1 1.4 5.1 4.7 1.2 0.5 0.2 0.6 0.0 0.3 2.0 0.243 0.316 0.383 0.699 1
Eric Fryer MIN C C -0.1 -0.6 1.2 4.7 4.4 1.0 0.5 0.1 0.4 0.1 0.3 1.5 0.230 0.301 0.333 0.634 0
Mark Ellis STL 2B 2B -0.1 -0.1 0.5 1.6 1.5 0.4 0.2 0.0 0.1 0.0 0.1 0.2 0.253 0.312 0.351 0.663 0
Jon Jay STL OF OF -0.1 -0.1 4.6 19.8 18.5 5.3 2.1 0.2 1.9 0.3 1.2 3.8 0.289 0.349 0.378 0.727 49
Pete Kozma STL SS SS -0.1 -0.2 0.7 2.4 2.3 0.5 0.2 0.0 0.3 0.1 0.1 0.5 0.230 0.291 0.329 0.620 0
Marcell Ozuna MIA OF OF -0.1 0.2 5.7 24.3 23.4 5.8 2.4 0.6 2.7 0.2 1.0 6.4 0.248 0.290 0.393 0.683 100
Cesar Hernandez PHI 2B, 3B, OF 2B, 3B, OF -0.1 -0.2 0.5 1.9 1.8 0.5 0.2 0.0 0.1 0.0 0.1 0.1 0.261 0.300 0.301 0.601 0
Mark Reynolds MIL 1B, 3B 1B, 3B -0.1 0.1 1.8 6.6 6.0 1.2 0.7 0.3 0.8 0.1 0.6 2.0 0.205 0.309 0.408 0.717 29
Junior Lake CHN OF OF -0.1 0.0 0.7 2.1 2.0 0.5 0.2 0.1 0.2 0.1 0.1 1.1 0.238 0.264 0.370 0.634 17
Guilder Rodriguez TEX SS SS -0.1 -0.1 0.4 1.7 1.6 0.4 0.1 0.0 0.1 0.0 0.1 0.3 0.245 0.307 0.298 0.605 0
Brandon Barnes COL OF OF -0.1 -0.5 1.9 7.3 7.0 1.7 0.7 0.2 0.8 0.2 0.3 2.1 0.245 0.292 0.381 0.673 0
Matt Duffy SF 2B 2B, SS -0.2 -0.2 0.8 2.9 2.8 0.6 0.2 0.0 0.2 0.1 0.1 0.5 0.227 0.271 0.293 0.563 0
Chris Denorfia SEA OF OF -0.2 -0.2 3.3 11.7 11.1 3.0 1.4 0.2 1.3 0.2 0.5 1.9 0.271 0.331 0.395 0.726 1
Josh Phegley CHA C C -0.2 -0.2 1.1 4.1 3.9 0.9 0.3 0.1 0.4 0.0 0.1 0.8 0.234 0.274 0.380 0.654 0
J.B. Shuck CLE OF OF -0.2 -0.3 0.7 2.3 2.2 0.6 0.2 0.0 0.1 0.0 0.1 0.1 0.264 0.316 0.332 0.648 0
Charlie Culberson COL 2B, SS, 3B, OF 2B, SS, 3B, OF -0.2 -0.7 1.6 5.3 5.1 1.3 0.5 0.1 0.5 0.2 0.2 1.2 0.252 0.287 0.368 0.654 0
Jimmy Rollins PHI SS SS -0.2 1.4 5.4 24.4 23.0 5.5 2.6 0.4 1.8 0.8 1.4 4.1 0.239 0.302 0.326 0.628 79
Jason Bourgeois CIN OF OF -0.2 -0.2 0.8 2.9 2.8 0.7 0.2 0.0 0.2 0.1 0.1 0.1 0.244 0.278 0.316 0.594 0
Adam Duvall SF 1B 1B -0.2 -0.2 0.8 2.9 2.8 0.6 0.2 0.1 0.3 0.0 0.1 0.5 0.209 0.248 0.339 0.587 0
Marcus Semien CHA 2B, 3B 2B, 3B -0.2 0.0 2.2 8.8 8.2 1.9 0.9 0.2 0.9 0.2 0.5 2.1 0.231 0.299 0.374 0.673 7
Justin Bour MIA 1B 1B -0.2 -0.2 0.8 3.3 3.2 0.8 0.3 0.1 0.3 0.0 0.2 0.6 0.246 0.301 0.369 0.669 0
Jackson Williams COL C C -0.2 -0.4 0.9 3.4 3.2 0.7 0.3 0.1 0.3 0.0 0.2 0.9 0.227 0.289 0.320 0.609 0
Jason Giambi CLE DH DH -0.2 -0.2 0.7 2.3 2.1 0.4 0.3 0.1 0.2 0.0 0.2 0.4 0.205 0.299 0.347 0.646 0
Anthony Recker NYN C C -0.2 -0.3 1.0 3.7 3.6 0.8 0.4 0.1 0.3 0.0 0.2 1.5 0.216 0.270 0.357 0.627 0
Leury Garcia CHA 2B, 3B, OF 2B, SS, 3B, OF -0.2 -0.3 1.0 3.6 3.5 0.8 0.3 0.0 0.2 0.2 0.1 0.5 0.216 0.249 0.288 0.538 0
Martin Maldonado MIL C C, 1B -0.2 -0.5 2.0 7.1 6.7 1.4 0.7 0.3 0.9 0.0 0.4 2.5 0.215 0.292 0.360 0.653 0
Clint Barmes PIT 2B, SS 2B, SS -0.2 -0.3 0.8 2.9 2.8 0.6 0.2 0.1 0.3 0.0 0.1 0.8 0.217 0.266 0.317 0.583 0
Raul Ibanez KC OF 1B, OF -0.2 -0.1 1.7 5.8 5.4 1.2 0.6 0.2 0.7 0.1 0.4 1.2 0.232 0.302 0.420 0.722 2
Tony Gwynn PHI OF OF -0.2 -0.2 0.5 1.9 1.8 0.4 0.1 0.0 0.1 0.0 0.1 0.1 0.204 0.270 0.242 0.513 0
Hector Gomez MIL SS SS -0.2 -0.2 0.6 2.2 2.1 0.5 0.2 0.0 0.2 0.0 0.1 0.3 0.230 0.267 0.352 0.618 0
Darwin Barney LAN 2B 2B -0.2 -0.2 0.8 3.2 3.0 0.7 0.3 0.0 0.3 0.0 0.1 0.6 0.228 0.279 0.316 0.595 0
Alfredo Marte ARI OF OF -0.2 -0.7 2.7 10.2 9.7 2.4 1.1 0.3 1.2 0.2 0.4 2.3 0.250 0.294 0.382 0.675 0
Jeff Baker MIA 1B, 2B, OF 1B, 2B, 3B, OF -0.2 -0.6 1.2 4.3 4.1 1.0 0.4 0.1 0.4 0.0 0.2 1.1 0.254 0.292 0.367 0.659 0
Brent Morel PIT 3B 3B -0.3 -0.3 0.9 3.8 3.7 0.9 0.3 0.0 0.3 0.0 0.2 0.4 0.237 0.284 0.333 0.617 0
Drew Butera LAN C C -0.3 -0.6 0.8 2.8 2.7 0.5 0.3 0.1 0.2 0.0 0.1 0.5 0.192 0.242 0.279 0.521 0
Cliff Pennington ARI 2B, SS 2B, SS, 3B -0.3 -0.9 2.4 9.5 9.0 2.3 1.0 0.1 0.9 0.3 0.6 1.6 0.254 0.320 0.357 0.678 2
Justin Smoak SEA 1B 1B -0.3 -0.4 1.1 3.7 3.5 0.9 0.4 0.0 0.4 0.0 0.2 0.2 0.251 0.315 0.385 0.700 18
Cory Spangenberg SD 2B 3B -0.3 -0.7 2.3 8.7 8.4 2.0 0.8 0.1 0.7 0.4 0.2 2.5 0.242 0.280 0.354 0.634 5
Adrian Nieto CHA C C -0.3 -0.7 1.3 4.5 4.2 0.9 0.4 0.1 0.4 0.1 0.3 0.7 0.214 0.269 0.310 0.579 0
Chris Taylor SEA SS SS -0.3 -0.9 4.4 15.0 14.2 3.9 1.7 0.2 1.5 0.5 0.8 2.9 0.274 0.329 0.367 0.695 1
Don Kelly DET 1B, 3B, OF 1B, 3B, OF -0.4 -0.4 1.9 7.4 6.9 1.7 0.8 0.1 0.7 0.1 0.5 1.0 0.244 0.321 0.349 0.669 0
Erisbel Arruebarrena LAN SS SS -0.4 -0.6 0.9 3.3 3.1 0.6 0.3 0.0 0.3 0.0 0.1 1.2 0.206 0.246 0.284 0.531 0
Ryan Hanigan TB C C -0.4 -3.1 2.9 11.3 10.3 2.6 1.2 0.2 1.1 0.1 0.9 1.6 0.254 0.339 0.349 0.689 0
Chris Heisey CIN OF OF -0.4 -0.2 1.7 6.5 6.1 1.4 0.6 0.2 0.6 0.2 0.3 1.8 0.231 0.267 0.371 0.637 4
Trevor Plouffe MIN 3B 3B -0.4 0.6 6.5 26.5 24.7 6.2 2.9 0.8 3.2 0.1 1.6 5.3 0.252 0.316 0.418 0.734 77
Elian Herrera MIL SS, 3B, OF 2B, SS, 3B, OF -0.4 -0.6 1.0 3.5 3.3 0.7 0.3 0.0 0.3 0.1 0.2 0.7 0.227 0.291 0.292 0.583 0
Michael Bourn CLE OF OF -0.4 4.2 5.6 25.8 24.3 6.1 2.9 0.2 1.9 0.9 1.4 6.5 0.250 0.306 0.337 0.643 52
Miguel Rojas LAN SS, 3B SS, 3B -0.4 -0.5 0.9 3.0 2.9 0.6 0.2 0.0 0.2 0.1 0.1 0.5 0.222 0.263 0.280 0.543 0
Nate Freiman OAK 1B 1B -0.4 0.0 2.1 7.0 6.4 1.6 0.8 0.3 0.8 0.0 0.5 1.4 0.257 0.332 0.424 0.756 0
Jordan Schafer MIN OF OF -0.4 2.0 5.7 21.4 19.8 4.6 2.3 0.2 1.7 1.8 1.4 5.1 0.233 0.299 0.308 0.606 31
Reed Johnson MIA OF OF -0.4 -0.7 1.1 4.1 4.0 1.0 0.4 0.1 0.4 0.1 0.1 1.1 0.249 0.281 0.335 0.616 0
Mike Aviles CLE 2B, SS, 3B, OF 2B, SS, 3B, OF -0.4 -0.8 2.9 10.0 9.8 2.5 1.0 0.2 1.0 0.3 0.3 1.4 0.257 0.286 0.377 0.663 8
Chris Parmelee MIN 1B, OF 1B, OF -0.5 -0.8 1.9 7.9 7.4 1.8 0.8 0.2 0.8 0.0 0.5 1.2 0.243 0.313 0.376 0.689 1
Logan Forsythe TB 2B 2B, SS, 3B, OF -0.5 -1.8 2.6 9.9 9.3 2.3 1.0 0.2 1.0 0.1 0.7 2.1 0.245 0.319 0.370 0.690 4
Matthew Clark MIL 1B 1B -0.5 0.1 2.1 7.5 7.0 1.7 0.9 0.3 0.9 0.0 0.5 1.9 0.248 0.313 0.428 0.740 0
Tony Cruz STL C C -0.5 -0.8 1.1 3.7 3.5 0.8 0.3 0.0 0.3 0.0 0.2 0.6 0.235 0.284 0.337 0.621 0
Jack Hannahan CIN 1B, 3B 1B, 3B -0.5 -0.6 1.0 3.8 3.5 0.8 0.3 0.1 0.3 0.0 0.2 0.7 0.222 0.287 0.324 0.611 0
Jake Smolinski TEX OF OF -0.5 -1.0 3.5 15.3 14.3 3.7 1.5 0.3 1.7 0.0 1.0 3.2 0.255 0.325 0.388 0.713 0
Jose Lobaton WAS C C -0.5 -0.9 1.5 6.6 6.1 1.4 0.6 0.1 0.6 0.0 0.5 1.8 0.235 0.313 0.338 0.651 0
Francisco Cervelli NYA C C -0.5 -0.6 1.8 6.3 5.9 1.5 0.6 0.2 0.6 0.0 0.4 1.2 0.251 0.310 0.368 0.678 0
Matt den Dekker NYN OF OF -0.5 -0.5 3.0 11.8 11.3 2.9 1.1 0.2 1.2 0.3 0.5 2.5 0.254 0.301 0.370 0.671 0
Jose Molina TB C C -0.5 -1.4 1.4 4.8 4.5 1.0 0.4 0.1 0.5 0.0 0.2 1.1 0.230 0.283 0.318 0.600 0
Avisail Garcia CHA OF OF -0.6 5.1 6.3 26.4 25.3 6.4 2.5 0.6 2.8 0.4 0.9 5.6 0.253 0.293 0.378 0.670 60
Yunel Escobar TB SS SS -0.6 -7.6 5.3 20.9 19.4 5.3 2.2 0.3 2.2 0.1 1.2 2.6 0.272 0.336 0.375 0.711 2
Welington Castillo CHN C C -0.6 -4.6 4.7 17.4 16.4 4.0 1.7 0.5 1.9 0.1 1.1 4.9 0.242 0.301 0.398 0.699 1
Danny Valencia TOR 1B, 3B 1B, 2B, 3B -0.6 1.5 5.8 22.5 21.5 5.4 2.3 0.7 2.8 0.1 0.7 4.6 0.252 0.290 0.401 0.690 0
Eric Young NYN OF OF -0.6 -0.6 2.1 8.1 7.7 1.8 0.8 0.0 0.6 0.5 0.4 1.8 0.240 0.294 0.309 0.603 39
Jacob Lamb ARI 3B 3B -0.6 -1.6 4.2 15.5 14.7 3.9 1.6 0.4 1.9 0.1 0.7 3.8 0.262 0.319 0.415 0.734 0
Hank Conger LAA C C -0.6 -2.4 2.6 9.3 8.7 2.1 0.9 0.2 0.9 0.1 0.6 2.2 0.241 0.297 0.354 0.651 0
Josh Thole TOR C C -0.7 -2.1 2.6 8.5 8.0 2.0 0.9 0.1 0.9 0.1 0.5 1.8 0.254 0.322 0.367 0.689 0
Gerald Laird ATL C C -0.7 -1.1 1.4 5.4 4.9 1.2 0.5 0.0 0.4 0.0 0.4 0.6 0.242 0.311 0.313 0.624 0
Kurt Suzuki MIN C C -0.7 -4.1 4.7 19.0 17.8 4.7 1.8 0.3 1.9 0.1 1.0 2.8 0.262 0.315 0.374 0.689 13
Curt Casali TB C C -0.7 -1.6 1.6 6.0 5.5 1.3 0.6 0.1 0.5 0.0 0.4 1.6 0.239 0.305 0.342 0.647 0
Zelous Wheeler NYA 3B 3B, OF -0.7 -0.7 2.0 5.6 5.4 1.4 0.7 0.2 0.7 0.0 0.3 1.0 0.257 0.312 0.421 0.733 0
Luis Sardinas TEX 2B, SS 2B, SS, 3B -0.7 -0.7 2.2 8.5 8.3 2.2 0.8 0.0 0.7 0.3 0.2 0.9 0.266 0.297 0.344 0.641 0
Rafael Ynoa COL 2B 2B -0.8 -1.6 2.1 9.5 9.0 2.3 0.9 0.0 0.8 0.2 0.4 1.7 0.252 0.302 0.340 0.642 0
Yasmani Grandal SD C,1B C, 1B -0.8 -7.2 5.7 24.0 21.9 4.9 2.2 0.7 2.4 0.1 2.1 6.2 0.225 0.316 0.375 0.691 4
Jonny Gomes OAK OF OF -0.8 -0.9 2.1 6.3 5.5 1.4 0.8 0.2 0.7 0.0 0.6 1.9 0.256 0.358 0.409 0.767 2
Bryan Holaday DET C C -0.8 -1.7 2.9 11.0 10.5 2.6 1.1 0.2 1.1 0.1 0.4 2.5 0.244 0.288 0.344 0.632 0
Maikel Franco PHI 3B 3B -0.8 -0.5 3.4 13.9 13.4 3.4 1.5 0.4 1.5 0.0 0.5 2.6 0.250 0.289 0.375 0.663 5
Mike Olt CHN 1B, 3B 1B, 3B -0.8 -1.0 1.9 7.0 6.4 1.3 0.6 0.2 0.8 0.0 0.4 2.5 0.200 0.274 0.382 0.656 11
Marlon Byrd PHI OF OF -0.8 -0.5 5.3 21.9 20.9 5.4 2.1 0.6 2.5 0.1 0.9 5.9 0.258 0.306 0.389 0.695 96
Anthony Gose TOR OF OF -0.8 -0.6 2.8 8.6 8.1 1.9 1.0 0.2 0.9 0.5 0.4 2.7 0.234 0.299 0.358 0.657 5
Matt Szczur CHN OF OF -0.8 -0.7 1.6 5.2 5.0 1.2 0.4 0.0 0.4 0.2 0.2 1.7 0.240 0.280 0.328 0.607 0
Sam Fuld OAK OF OF -0.9 5.0 5.5 23.3 21.7 5.2 2.6 0.2 2.1 1.0 1.6 4.0 0.240 0.317 0.340 0.657 2
Lyle Overbay MIL 1B 1B -0.9 -1.0 1.5 5.5 5.0 1.1 0.5 0.1 0.6 0.0 0.4 1.1 0.225 0.308 0.348 0.656 0
Daniel Robertson TEX OF OF -0.9 -1.5 2.5 10.2 9.6 2.6 1.1 0.0 0.8 0.2 0.6 1.6 0.267 0.330 0.361 0.691 0
Adam Dunn OAK 1B 1B, OF -1.0 6.6 5.3 20.7 18.7 3.8 2.4 1.0 2.7 0.1 2.0 6.5 0.205 0.318 0.392 0.710 54
Mike Moustakas KC 3B 3B -1.0 -0.6 6.7 24.1 22.9 5.5 2.7 0.9 3.1 0.1 1.3 4.7 0.241 0.299 0.433 0.732 26
Gregorio Petit HOU SS SS, 3B -1.0 -3.4 2.9 9.2 8.8 2.3 1.0 0.2 1.0 0.1 0.4 1.6 0.263 0.304 0.379 0.683 0
Sean Rodriguez TB 1B, 2B, OF 1B, 2B, SS, 3B, OF -1.0 -2.2 2.2 6.6 6.3 1.5 0.8 0.2 0.8 0.0 0.4 1.4 0.231 0.301 0.410 0.711 1
Chris Stewart PIT C C -1.0 -1.1 1.5 5.2 4.8 1.1 0.4 0.0 0.4 0.0 0.3 0.4 0.234 0.296 0.312 0.608 0
Andres Blanco PHI 3B 2B, SS, 3B -1.1 -1.2 1.4 5.3 5.0 1.2 0.4 0.0 0.3 0.0 0.2 0.2 0.233 0.281 0.299 0.580 0
Scott Van Slyke LAN 1B, OF 1B, OF -1.1 -0.8 2.0 6.1 5.6 1.3 0.7 0.2 0.7 0.0 0.5 1.6 0.232 0.327 0.416 0.743 1
Stephen Drew NYA 2B, SS 2B, SS -1.1 -4.3 5.5 19.1 17.6 3.9 2.1 0.6 2.2 0.2 1.4 4.9 0.222 0.300 0.386 0.686 4
Ichiro Suzuki NYA OF OF -1.1 0.7 4.7 16.7 16.2 4.5 1.8 0.1 1.8 0.6 0.4 2.7 0.280 0.317 0.385 0.702 0
Skip Schumaker CIN 2B, OF 2B, OF -1.1 -1.4 2.0 7.4 7.0 1.8 0.6 0.1 0.6 0.1 0.3 1.8 0.255 0.305 0.330 0.635 0
Jake Goebbert SD 1B 1B, OF -1.1 -1.8 2.2 6.5 6.0 1.4 0.6 0.2 0.7 0.1 0.3 1.6 0.238 0.298 0.388 0.686 0
Gerardo Parra MIL OF OF -1.1 0.5 4.6 20.0 18.7 4.8 2.0 0.4 1.7 0.4 1.1 3.5 0.255 0.314 0.361 0.675 46
John Baker CHN C C -1.1 -2.2 1.7 6.4 5.9 1.4 0.5 0.1 0.6 0.0 0.4 1.4 0.235 0.293 0.303 0.596 0
Scooter Gennett MIL 2B 2B -1.2 -1.7 5.3 22.0 20.9 5.6 2.2 0.3 1.9 0.4 0.7 3.2 0.266 0.304 0.364 0.668 56
Jose Tabata PIT OF OF -1.2 -0.9 1.9 6.6 6.2 1.6 0.6 0.0 0.5 0.0 0.3 0.3 0.263 0.320 0.378 0.698 0
Phil Gosselin ATL 2B 2B, 3B -1.2 -3.4 4.6 20.1 19.1 5.2 1.9 0.2 1.7 0.3 0.8 3.6 0.271 0.311 0.344 0.655 0
Ryan Kalish CHN OF OF -1.2 -2.1 2.6 8.9 8.3 2.1 0.8 0.1 0.9 0.3 0.4 1.6 0.257 0.306 0.395 0.701 0
Angel Pagan SF OF OF -1.2 1.4 5.7 24.8 23.8 6.1 2.6 0.3 1.9 0.8 0.9 3.3 0.257 0.297 0.378 0.676 95
Gaby Sanchez PIT 1B 1B -1.2 -0.8 2.3 7.9 7.3 1.8 0.8 0.2 0.9 0.0 0.6 1.9 0.251 0.320 0.391 0.711 0
Adam Eaton CHA OF OF -1.2 2.4 5.9 25.1 23.5 6.2 2.8 0.3 1.8 0.7 1.3 4.3 0.263 0.327 0.355 0.682 92
Jackie Bradley Jr. BOS OF OF -1.3 -3.0 4.5 16.9 15.6 4.0 1.9 0.3 1.9 0.3 0.9 4.1 0.255 0.320 0.401 0.721 2
Logan Watkins CHN 2B 2B -1.3 -3.2 3.0 9.4 8.8 2.2 0.9 0.1 0.9 0.4 0.4 2.1 0.254 0.308 0.355 0.664 1
Starlin Castro CHN SS SS -1.3 -5.0 5.7 20.0 19.4 5.3 2.0 0.4 2.2 0.3 0.8 4.1 0.275 0.310 0.416 0.726 75
Grady Sizemore PHI OF OF -1.3 -1.6 1.7 6.9 6.5 1.4 0.6 0.1 0.6 0.0 0.4 2.2 0.220 0.284 0.316 0.600 8
Steve Tolleson TOR 2B, 3B 2B, 3B, OF -1.3 -2.1 2.1 7.3 6.8 1.7 0.7 0.1 0.5 0.0 0.5 2.9 0.251 0.324 0.362 0.686 1
Brendan Ryan NYA 2B, SS 2B, SS -1.4 -1.9 1.9 6.2 5.8 1.3 0.6 0.0 0.5 0.1 0.3 1.4 0.222 0.276 0.301 0.578 0
Collin Cowgill LAA OF OF -1.4 -2.2 2.6 9.5 9.0 2.1 1.0 0.2 0.9 0.2 0.6 2.4 0.234 0.298 0.340 0.637 1
Oscar Taveras STL OF OF -1.4 -2.2 3.5 12.6 12.2 3.5 1.3 0.2 1.4 0.1 0.5 1.8 0.284 0.320 0.393 0.713 63
Lorenzo Cain KC OF OF -1.4 2.3 6.0 23.7 22.5 5.7 2.4 0.3 2.2 1.0 1.2 6.4 0.252 0.298 0.358 0.656 90
Didi Gregorius ARI 2B, SS 2B, SS -1.4 -6.5 5.4 19.4 18.4 4.9 2.1 0.3 2.2 0.2 0.8 2.9 0.265 0.315 0.385 0.700 2
Andy Parrino OAK SS 2B, SS -1.5 -2.0 2.1 6.9 6.4 1.5 0.6 0.1 0.6 0.1 0.4 1.9 0.230 0.306 0.330 0.635 0
Andrew Romine DET 2B, SS, 3B 2B, SS, 3B -1.5 -1.8 2.7 9.6 9.0 2.1 0.9 0.1 0.8 0.3 0.5 1.9 0.237 0.303 0.310 0.612 2
Daniel Descalso STL 2B, SS, 3B 2B, SS, 3B -1.5 -2.6 2.2 8.3 7.8 2.0 0.8 0.0 0.7 0.1 0.5 0.9 0.252 0.312 0.338 0.650 0
Eugenio Suarez DET SS SS -1.5 -1.9 4.2 15.7 14.7 3.6 1.6 0.3 1.6 0.3 0.9 3.2 0.243 0.299 0.357 0.655 2
Eric Campbell NYN 1B, 3B, OF 1B, 3B, OF -1.5 -2.0 2.4 9.0 8.4 2.1 0.8 0.2 0.9 0.0 0.6 2.2 0.249 0.315 0.342 0.657 0
Tommy La Stella ATL 2B 2B -1.5 -3.1 3.6 13.0 11.9 3.3 1.4 0.1 1.1 0.1 1.0 1.5 0.276 0.358 0.353 0.711 19
Jean Segura MIL SS SS -1.5 -1.0 4.6 17.3 16.6 4.3 1.6 0.2 1.4 0.7 0.8 2.4 0.258 0.302 0.354 0.656 86
Andrelton Simmons ATL SS SS -1.6 -5.8 6.5 26.4 24.8 6.5 2.6 0.4 2.4 0.3 1.2 2.9 0.264 0.315 0.366 0.681 57
Wil Nieves PHI C C -1.6 -3.0 2.1 7.1 6.9 1.6 0.5 0.1 0.6 0.0 0.2 1.2 0.240 0.276 0.300 0.576 0
Roberto Perez CLE C C -1.6 -3.7 2.4 8.8 8.0 1.7 0.8 0.2 0.8 0.1 0.6 1.8 0.212 0.291 0.303 0.593 0
Carlos Ruiz PHI C C -1.6 -4.2 4.2 16.9 15.7 4.3 1.5 0.2 1.5 0.0 1.1 2.7 0.272 0.345 0.365 0.710 10
Jordan Danks CHA OF OF -1.6 -1.7 2.7 9.3 8.6 2.0 0.9 0.2 0.9 0.2 0.6 2.7 0.227 0.307 0.363 0.669 0
Endy Chavez SEA OF OF -1.6 -2.0 3.0 10.1 9.7 2.5 1.1 0.1 0.9 0.2 0.4 1.5 0.263 0.302 0.350 0.652 0
Eric Sogard OAK 2B, SS 2B, SS -1.7 0.2 4.6 15.4 14.4 3.7 1.7 0.2 1.5 0.5 0.8 1.9 0.254 0.326 0.356 0.683 0
Joaquin Arias SF 1B, 2B, SS, 3B 1B, 2B, SS, 3B -1.7 -2.5 1.9 6.5 6.5 1.4 0.4 0.0 0.5 0.0 0.2 1.5 0.222 0.250 0.289 0.539 0
Tommy Medica SD 1B, OF 1B, OF -1.7 -2.4 2.6 8.5 7.9 1.8 0.8 0.2 0.9 0.0 0.6 1.6 0.227 0.303 0.367 0.670 7
Tyler Holt CLE OF OF -1.7 -1.2 2.6 9.1 8.5 2.1 0.8 0.0 0.8 0.4 0.6 1.7 0.250 0.316 0.328 0.644 0
Jordy Mercer PIT 2B, SS 2B, SS -1.7 -4.0 6.1 24.0 22.9 5.8 2.3 0.5 2.4 0.3 1.1 4.1 0.255 0.301 0.382 0.683 85
Aaron Hicks MIN OF OF -1.8 -3.0 2.6 9.8 8.9 2.1 1.0 0.1 0.8 0.3 0.7 2.7 0.237 0.317 0.341 0.658 6
Josh Willingham KC OF OF -1.8 4.2 6.7 26.9 23.8 5.2 3.0 1.0 3.2 0.1 2.7 8.0 0.219 0.318 0.388 0.706 27
Brayan Pena CIN C,1B C, 1B -1.8 -5.1 3.8 13.3 12.9 3.3 1.1 0.3 1.2 0.1 0.4 2.1 0.255 0.284 0.356 0.640 1
David DeJesus TB OF OF -1.8 -3.8 4.5 16.9 15.5 3.9 2.0 0.3 1.7 0.2 1.2 2.9 0.251 0.333 0.388 0.721 0
Travis Ishikawa SF 1B 1B -1.9 -2.1 3.1 12.8 12.0 2.7 1.2 0.4 1.4 0.0 0.7 3.7 0.227 0.294 0.389 0.684 0
Kristopher Negron CIN 2B, 3B 2B, 3B -1.9 -3.6 2.3 8.5 8.1 1.7 0.7 0.1 0.7 0.2 0.4 2.4 0.208 0.248 0.303 0.551 0
Andrew Susac SF C C -1.9 -2.8 2.4 9.8 9.1 1.9 0.8 0.2 0.8 0.0 0.6 2.1 0.210 0.278 0.317 0.595 0
Lonnie Chisenhall CLE 1B, 3B 1B, 3B -2.0 1.9 4.9 19.3 18.3 4.6 2.0 0.5 2.2 0.1 0.8 4.4 0.252 0.305 0.400 0.705 82
Jeff Mathis MIA C C -2.0 -3.6 1.9 6.2 5.9 1.2 0.5 0.1 0.5 0.0 0.3 2.1 0.196 0.242 0.279 0.521 0
David Freese LAA 3B 3B -2.1 -4.2 5.5 20.9 19.5 5.0 2.2 0.5 2.3 0.1 1.2 5.5 0.256 0.330 0.387 0.717 50
Ramon Santiago CIN 2B, SS, 3B 2B, SS, 3B -2.1 -3.6 2.3 7.8 7.3 1.7 0.6 0.1 0.6 0.1 0.5 1.7 0.230 0.297 0.304 0.601 0
Alberto Callaspo OAK 1B, 2B, 3B 1B, 2B, 3B -2.2 -2.2 4.1 15.4 14.2 3.6 1.6 0.3 1.5 0.1 1.1 1.8 0.256 0.334 0.356 0.689 1
Efren Navarro LAA 1B, OF 1B, OF -2.2 -3.0 2.6 8.3 7.7 1.9 0.8 0.1 0.8 0.1 0.5 1.8 0.251 0.318 0.351 0.669 0
Darin Ruf PHI 1B, OF 1B, OF -2.2 -2.3 3.7 13.4 12.4 3.1 1.3 0.4 1.4 0.0 0.9 2.9 0.246 0.324 0.381 0.705 0
C.J. Cron LAA 1B 1B -2.2 -4.2 4.5 15.4 14.9 3.8 1.6 0.5 1.8 0.1 0.5 3.1 0.253 0.295 0.404 0.699 17
Jarrod Saltalamacchia MIA C C -2.3 -7.1 4.3 17.4 16.0 3.5 1.5 0.4 1.7 0.1 1.2 5.9 0.221 0.295 0.351 0.645 7
Wilmer Flores NYN 2B, SS, 3B 2B, SS, 3B -2.4 -6.1 5.2 20.3 19.8 4.9 1.8 0.4 2.2 0.1 0.5 3.6 0.250 0.279 0.371 0.650 13
Jesus Sucre SEA C C -2.4 -3.9 2.9 9.2 9.0 2.3 0.9 0.0 0.8 0.0 0.2 1.9 0.259 0.276 0.330 0.606 0
Munenori Kawasaki TOR 2B, SS, 3B 2B, SS, 3B -2.6 -3.8 3.0 9.2 8.7 2.2 0.9 0.1 0.8 0.1 0.5 1.9 0.255 0.315 0.338 0.653 0
Abraham Almonte SD OF OF -2.8 -4.0 4.0 17.0 16.1 3.7 1.5 0.3 1.2 0.4 0.8 3.7 0.228 0.292 0.336 0.628 2
Billy Butler KC 1B 1B -2.9 4.1 6.3 24.2 22.6 6.0 2.7 0.6 2.9 0.0 1.4 4.8 0.267 0.329 0.408 0.738 73
Chris Johnson ATL 3B 1B, 3B -2.9 -4.2 5.9 24.1 22.7 6.3 2.3 0.4 2.5 0.1 1.0 6.0 0.279 0.320 0.385 0.705 52
Peter Bourjos STL OF OF -2.9 -2.9 4.8 18.2 17.4 4.2 1.8 0.3 1.9 0.4 1.0 4.2 0.244 0.298 0.377 0.676 5
Brad Miller SEA SS 2B, SS -2.9 -5.7 6.0 20.1 19.1 4.8 2.2 0.4 2.2 0.3 1.0 4.0 0.249 0.302 0.373 0.675 45
Chris Iannetta LAA C C -2.9 -9.5 4.7 17.0 15.0 3.4 1.9 0.4 1.7 0.1 1.8 5.2 0.224 0.337 0.353 0.689 0
Ryan Goins TOR 2B, SS 2B, SS -2.9 -4.4 3.0 8.8 8.6 2.1 0.8 0.1 0.8 0.1 0.3 2.1 0.249 0.279 0.338 0.617 0
Seth Smith SD OF OF -2.9 -5.5 6.1 25.7 23.5 5.7 2.7 0.6 2.6 0.1 1.9 5.1 0.244 0.321 0.406 0.728 36
Juan Uribe LAN 3B 3B -3.1 -4.0 4.4 16.9 16.2 4.0 1.6 0.4 1.9 0.1 0.6 3.1 0.249 0.294 0.385 0.680 32
Juan Perez SF OF OF -3.2 -4.0 3.5 13.6 13.1 3.0 1.1 0.3 1.1 0.2 0.4 3.2 0.226 0.257 0.315 0.573 0
Andy Wilkins CHA 1B 1B -3.2 -1.1 4.9 18.1 17.1 4.0 1.8 0.7 2.0 0.1 0.8 4.3 0.234 0.281 0.387 0.668 0
Jonathan Schoop BAL 2B, 3B 2B, 3B -3.2 -6.6 5.8 21.2 20.3 4.8 2.2 0.6 2.3 0.2 0.9 4.6 0.238 0.278 0.363 0.640 24
DJ LeMahieu COL 2B 2B, 3B -3.2 -9.0 5.3 19.2 18.3 5.0 1.7 0.2 1.7 0.6 0.8 3.1 0.274 0.318 0.349 0.667 32
Ruben Tejada NYN SS SS -3.3 -5.3 2.7 9.5 8.8 2.2 0.8 0.0 0.7 0.0 0.6 1.8 0.250 0.310 0.307 0.617 0
Garrett Jones MIA 1B, OF 1B, OF -3.3 -4.7 5.3 19.9 18.7 4.5 1.9 0.6 2.3 0.1 1.1 4.6 0.239 0.302 0.399 0.700 35
Eduardo Escobar MIN SS, 3B 2B, SS, 3B -3.4 -6.0 4.8 18.0 17.2 4.3 1.7 0.3 1.7 0.1 0.6 4.1 0.251 0.297 0.349 0.646 7
Casey McGehee MIA 3B 3B -3.9 -6.1 5.6 24.5 23.1 6.0 2.2 0.4 2.5 0.1 1.4 4.2 0.260 0.319 0.353 0.672 87
Dilson Herrera NYN 2B 2B -3.9 -7.4 5.1 19.4 18.8 4.4 1.5 0.3 1.8 0.5 0.6 4.5 0.235 0.276 0.337 0.612 1
Ryan Ludwick CIN OF OF -4.0 -4.3 4.5 17.6 16.5 3.8 1.6 0.5 1.9 0.1 0.9 4.7 0.227 0.279 0.366 0.646 2
Tyler Flowers CHA C C -4.2 -6.2 5.3 19.4 18.2 3.8 1.9 0.6 1.9 0.1 1.1 6.8 0.207 0.266 0.349 0.615 11
Chris Valaika CHN 1B 1B, 2B, SS, 3B -4.4 -6.1 3.8 14.0 13.4 3.3 1.2 0.2 1.3 0.1 0.5 3.6 0.246 0.279 0.355 0.634 4
Chase Utley PHI 2B 2B -4.4 -4.0 5.7 24.1 22.4 5.4 2.4 0.4 2.2 0.3 1.6 4.2 0.242 0.314 0.341 0.655 100
David Murphy CLE OF OF -4.6 -4.9 4.5 14.9 14.0 3.6 1.5 0.3 1.5 0.2 0.8 2.3 0.258 0.311 0.371 0.681 21
Juan Lagares NYN OF OF -4.6 -5.7 5.4 22.1 21.5 5.6 2.1 0.2 2.0 0.5 0.5 5.0 0.259 0.286 0.346 0.632 88
Gordon Beckham LAA 2B 2B, 3B -4.6 -9.7 5.1 18.4 17.7 4.3 1.9 0.3 1.8 0.2 0.8 3.3 0.240 0.294 0.353 0.647 12
Will Venable SD OF OF -4.7 -6.9 6.0 20.6 19.6 4.6 2.0 0.6 2.0 0.6 1.1 5.8 0.235 0.289 0.387 0.677 46
Alcides Escobar KC SS SS -4.8 -2.9 6.7 25.6 24.6 5.9 2.4 0.2 2.2 1.1 0.8 4.0 0.239 0.279 0.330 0.609 96
Brandon Phillips CIN 2B 2B -4.9 -6.8 5.5 20.5 19.5 4.7 1.9 0.5 2.0 0.2 0.8 3.7 0.241 0.286 0.362 0.648 86
Yangervis Solarte SD 2B, 3B SS -5.0 -10.2 6.1 26.4 25.0 6.2 2.5 0.4 2.1 0.1 1.3 3.9 0.249 0.306 0.358 0.664 50
Freddy Galvis PHI 2B, SS, 3B 2B, SS, 3B, OF -5.1 -7.5 3.9 13.2 12.8 3.1 1.1 0.2 1.2 0.0 0.4 2.6 0.241 0.272 0.316 0.587 0
Rymer Liriano SD OF OF -5.3 -7.4 4.6 16.9 16.1 3.7 1.3 0.2 1.5 0.5 0.9 4.5 0.231 0.286 0.325 0.612 11
Donovan Solano MIA 2B 2B -5.6 -12.3 5.4 24.7 23.6 6.0 2.2 0.2 1.9 0.3 0.9 4.6 0.256 0.291 0.314 0.605 5
B.J. Upton ATL OF OF -5.6 -6.7 6.7 25.0 22.9 4.9 2.7 0.5 2.2 0.9 1.8 8.2 0.216 0.306 0.354 0.660 44
A.J. Ellis LAN C C -5.8 -11.6 4.8 17.7 15.9 3.6 1.6 0.3 1.6 0.1 1.5 3.3 0.229 0.325 0.324 0.649 0
Carlos Sanchez CHA 2B 2B -6.2 -7.9 5.2 19.5 18.6 4.6 1.7 0.1 1.5 0.5 0.7 4.3 0.245 0.287 0.317 0.604 0
Michael Morse SF 1B, OF 1B, OF -6.8 -7.8 6.3 23.1 22.1 5.2 2.1 0.7 2.6 0.0 1.0 6.6 0.236 0.283 0.381 0.664 65
Rene Rivera SD C C -6.8 -12.5 5.4 20.2 19.2 4.4 1.7 0.5 1.8 0.0 1.0 4.2 0.228 0.283 0.341 0.624 2
Domonic Brown PHI OF OF -7.2 -5.9 5.3 20.9 19.7 4.7 1.8 0.4 1.9 0.2 1.2 4.2 0.239 0.291 0.338 0.630 42
Gregor Blanco SF OF OF -7.3 -8.5 5.5 22.0 20.5 4.7 2.0 0.2 1.6 0.7 1.4 5.4 0.228 0.296 0.336 0.632 68
Cody Asche PHI 3B 3B -7.4 -7.3 4.7 17.9 17.1 4.1 1.5 0.3 1.6 0.1 0.9 4.6 0.238 0.285 0.324 0.610 8
Zack Cozart CIN SS SS -7.5 -12.4 4.5 14.9 14.4 3.3 1.2 0.3 1.3 0.1 0.5 2.4 0.229 0.261 0.337 0.598 8
Conor Gillaspie CHA 3B 1B, 3B -7.6 -6.9 6.4 24.7 23.2 5.7 2.3 0.5 2.4 0.1 1.4 4.6 0.246 0.303 0.367 0.669 30
Joe Panik SF 2B 2B -8.1 -12.1 6.0 27.0 25.7 6.3 2.3 0.3 2.0 0.2 1.1 2.4 0.246 0.286 0.343 0.629 42
Cameron Maybin SD OF OF -8.6 -12.1 5.9 19.1 18.1 4.3 1.6 0.3 1.7 0.5 1.0 4.1 0.237 0.301 0.342 0.642 0
Adeiny Hechavarria MIA SS SS -8.9 -17.1 5.7 22.7 21.9 5.5 1.7 0.2 1.9 0.4 0.6 4.3 0.251 0.280 0.323 0.603 15
Brandon Crawford SF SS SS -11.0 -18.1 6.4 24.0 22.5 5.0 2.0 0.4 2.1 0.1 1.4 5.8 0.222 0.281 0.354 0.635 13
Ryan Howard PHI 1B 1B -11.4 -7.4 5.7 24.1 22.3 4.7 2.1 0.6 2.3 0.0 1.8 9.1 0.209 0.285 0.331 0.616 83
Alexi Amarista SD 2B, SS, 3B, OF 2B, SS, 3B, OF -12.6 -19.8 6.3 23.7 22.8 5.5 1.9 0.2 1.9 0.2 1.0 4.7 0.241 0.274 0.335 0.610 6
Geovany Soto OAK C C 1.6 5.4 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:
                    (link)

                    @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:
    (link)

    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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