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Fantasydraft - MLB
2018-04-15
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Pos Team Opp Win % Runs vs. Pitcher Hand ERA/AVG wOBA ISO Avg innings K/9 WHIP Order Salary Ceiling Avg FC Proj My Proj
Exp.
Used
Con. Value Actual Score Actual Val
Danny Valencia
IF BAL @ BOS 31.3% 2.56 Sale, L 1.06 R 0.143 0.279 0.191 0.00 0.0 0.00 5 5800 15.8 5.0 3.43 3.43 % % 38 0.6 2.00 0.3
Hanley Ramirez
IF BOS vs BAL 68.8% 3.94 Bundy, R 1.35 R 0.362 0.436 0.255 0.00 0.0 0.00 3 9200 25.4 12.8 9.41 9.41 % % 69 1 0.00
Christian Vazquez
IF BOS vs BAL 68.8% 3.94 Bundy, R 1.35 R 0.237 0.250 0.053 0.00 0.0 0.00 7 6400 11.2 4.7 3.95 3.95 % % 61 0.6 0.00
Caleb Joseph
IF BAL @ BOS 31.3% 2.56 Sale, L 1.06 R 0.103 0.132 0.069 0.00 0.0 0.00 9 5400 9.2 2.5 1.57 1.57 % % 24 0.3 0.00
Jackie Bradley Jr.
OF BOS vs BAL 68.8% 3.94 Bundy, R 1.35 L 0.209 0.284 0.070 0.00 0.0 0.00 1 6800 16.2 5.8 6.87 6.87 % % 60 1 7.00 1
Adam Jones
OF BAL @ BOS 31.3% 2.56 Sale, L 1.06 R 0.234 0.275 0.156 0.00 0.0 0.00 4 7700 20.2 6.4 5.29 5.29 % % 42 0.7 0.00
Craig Gentry
OF BAL @ BOS 31.3% 2.56 Sale, L 1.06 R 0.250 0.225 0.000 0.00 0.0 0.00 2 4700 17.9 4.0 3.34 3.34 % % 9 0.7 12.00 2.6
Chris Sale
P BOS vs BAL 68.8% 2.56 Bundy, R 1.35 L 1.06 0.000 0.000 5.70 12.2 1.00 23800 40.4 24.7 31.07 31.07 % % 81 1.3 22.85 1
Rafael Devers
IF BOS vs BAL 68.8% 3.94 Bundy, R 1.35 L 0.245 0.313 0.151 0.00 0.0 0.00 6 7800 18.5 7.2 6.47 6.47 % % 58 0.8 5.00 0.6
Brock Holt
IF BOS vs BAL 68.8% 3.94 Bundy, R 1.35 L 0.150 0.266 0.050 0.00 0.0 0.00 8 5800 9.6 3.9 3.40 3.40 % % 60 0.6 3.00 0.5
Manny Machado
IF BAL @ BOS 31.3% 2.56 Sale, L 1.06 R 0.311 0.401 0.213 0.00 0.0 0.00 3 9300 26.4 9.1 7.08 7.08 % % 47 0.8 7.00 0.8
Dylan Bundy
P BAL @ BOS 31.3% 3.94 Sale, L 1.06 R 1.35 0.000 0.000 6.70 11.1 0.95 14500 20.3 25.9 16.28 16.28 % % 92 1.1 17.35 1.2
Trey Mancini
IF/OF BAL @ BOS 31.3% 2.56 Sale, L 1.06 R 0.288 0.341 0.085 0.00 0.0 0.00 1 6400 13.5 6.7 4.90 4.90 % % 68 0.8 5.00 0.8
J.D. Martinez
OF BOS vs BAL 68.8% 3.94 Bundy, R 1.35 R 0.283 0.353 0.264 0.00 0.0 0.00 4 9000 25.1 9.5 9.75 9.75 % % 60 1.1 4.00 0.4
Chris Davis
IF/OF BAL @ BOS 31.3% 2.56 Sale, L 1.06 L 0.143 0.228 0.082 0.00 0.0 0.00 6 6800 13.2 3.7 3.26 3.26 % % 33 0.5 0.00
Mitch Moreland
IF BOS vs BAL 68.8% 3.94 Bundy, R 1.35 L 0.217 0.282 0.087 0.00 0.0 0.00 5 5600 14.2 3.5 6.28 6.28 % % 43 1.1 15.00 2.7
Tim Beckham
IF BAL @ BOS 31.3% 2.56 Sale, L 1.06 R 0.183 0.221 0.100 0.00 0.0 0.00 7 5600 13.3 5.4 2.82 2.82 % % 51 0.5 0.00
Tzu-Wei Lin
IF BOS vs BAL 68.8% 3.94 Bundy, R 1.35 L 0.500 0.538 0.125 0.00 0.0 0.00 9 5800 11.9 5.5 2.38 2.38 % % 57 0.4 10.00 1.7
Anthony Santander
OF BAL @ BOS 31.3% 2.56 Sale, L 1.06 B 0.205 0.272 0.154 0.00 0.0 0.00 8 5800 17 5.6 2.25 2.25 % % 34 0.4 0.00
Andrew Benintendi
OF BOS vs BAL 68.8% 3.94 Bundy, R 1.35 L 0.229 0.337 0.104 0.00 0.0 0.00 2 8200 24.9 8.4 9.19 9.19 % % 53 1.1 23.00 2.8
Eric Thames
IF MIL @ NYM 32.8% 2.82 Syndergaard, R 3.94 L 0.233 0.393 0.395 0.00 0.0 0.00 2 9000 24.2 8.3 7.20 7.20 % % 49 0.8 0.00
Jett Bandy
IF MIL @ NYM 32.8% 2.82 Syndergaard, R 3.94 R 0.200 0.332 0.200 0.00 0.0 0.00 8 5400 12.5 5.0 2.48 2.48 % % 50 0.5 3.00 0.6
Noah Syndergaard
P NYM vs MIL 67.2% 2.82 Chacin, R 6.59 R 3.94 0.000 0.000 5.30 12.4 1.19 20700 32.6 20.7 24.02 24.02 % % 79 1.2 32.20 1.6
Jhoulys Chacin
P MIL @ NYM 32.8% 4.18 Syndergaard, R 3.94 R 6.59 0.000 0.000 4.60 4.5 1.90 11100 22.5 2.9 9.41 9.41 % % 0 0.8 10.20 0.9
Tomas Nido
IF NYM vs MIL 67.2% 4.18 Chacin, R 6.59 R 0.000 0.000 0.000 0.00 0.0 0.00 8 5100 3.1 0.0 3.12 3.12 % % 0 0.6 0.00
Hernan Perez
IF/OF MIL @ NYM 32.8% 2.82 Syndergaard, R 3.94 R 0.154 0.238 0.231 0.00 0.0 0.00 6 5900 15.8 3.2 3.38 3.38 % % 3 0.6 8.00 1.4
Jose Reyes
IF NYM vs MIL 67.2% 4.18 Chacin, R 6.59 B 0.000 0.055 0.000 0.00 0.0 0.00 7 5500 3.7 0.0 3.72 3.72 % % 0 0.7 0.00
Jonathan Villar
IF MIL @ NYM 32.8% 2.82 Syndergaard, R 3.94 B 0.298 0.298 0.085 0.00 0.0 0.00 1 5900 14 5.1 4.37 4.37 % % 53 0.7 9.00 1.5
Yoenis Cespedes
OF NYM vs MIL 67.2% 4.18 Chacin, R 6.59 R 0.208 0.301 0.189 0.00 0.0 0.00 3 8400 23.2 8.0 9.62 9.62 % % 58 1.1 0.00
Michael Conforto
OF NYM vs MIL 67.2% 4.18 Chacin, R 6.59 L 0.250 0.394 0.208 0.00 0.0 0.00 2 9200 21.8 7.6 10.09 10.09 % % 62 1.1 5.00 0.5
Brandon Nimmo
OF NYM vs MIL 67.2% 4.18 Chacin, R 6.59 L 0.300 0.464 0.100 0.00 0.0 0.00 1 5600 16 5.1 6.81 6.81 % % 55 1.2 27.00 4.8
Lorenzo Cain
OF MIL @ NYM 32.8% 2.82 Syndergaard, R 3.94 R 0.278 0.325 0.130 0.00 0.0 0.00 3 7500 21.1 8.2 5.83 5.83 % % 53 0.8 8.00 1.1
Domingo Santana
OF MIL @ NYM 32.8% 2.82 Syndergaard, R 3.94 R 0.283 0.315 0.019 0.00 0.0 0.00 5 5800 9.4 5.2 4.39 4.39 % % 76 0.8 3.00 0.5
Travis Shaw
IF MIL @ NYM 32.8% 2.82 Syndergaard, R 3.94 L 0.283 0.343 0.200 0.00 0.0 0.00 4 7400 17.9 7.7 6.34 6.34 % % 63 0.9 0.00
Wilmer Flores
IF NYM vs MIL 67.2% 4.18 Chacin, R 6.59 R 0.190 0.294 0.238 0.00 0.0 0.00 5 6800 18.1 3.4 6.13 6.13 % % 12 0.9 16.00 2.4
Todd Frazier
IF NYM vs MIL 67.2% 4.18 Chacin, R 6.59 R 0.293 0.417 0.244 0.00 0.0 0.00 4 7200 25.4 9.2 9.16 9.16 % % 56 1.3 9.00 1.3
Orlando Arcia
IF MIL @ NYM 32.8% 2.82 Syndergaard, R 3.94 R 0.178 0.224 0.089 0.00 0.0 0.00 7 5600 11.1 4.1 2.71 2.71 % % 49 0.5 0.00
Amed Rosario
IF NYM vs MIL 67.2% 4.18 Chacin, R 6.59 R 0.244 0.257 0.098 0.00 0.0 0.00 6 6500 15.6 5.3 5.19 5.19 % % 51 0.8 4.00 0.6
Joe Wendle
IF TB vs PHI 58% 4.35 Lively, R 5.56 L 0.278 0.365 0.222 0.00 0.0 0.00 7 4600 15.1 5.7 4.12 4.12 % % 52 0.9 9.00 2
Daniel Robertson
IF TB vs PHI 58% 4.35 Lively, R 5.56 R 0.316 0.436 0.053 0.00 0.0 0.00 9 5600 13.9 5.7 2.79 2.79 % % 51 0.5 0.00
Rhys Hoskins
IF PHI @ TB 42% 3.65 Yarbrough, L 2.25 R 0.317 0.437 0.268 0.00 0.0 0.00 4 10300 26.5 9.8 10.63 10.63 % % 59 1 20.00 1.9
Carlos Santana
IF PHI @ TB 42% 3.65 Yarbrough, L 2.25 B 0.167 0.265 0.188 0.00 0.0 0.00 2 8000 22.2 7.9 8.64 8.64 % % 57 1.1 2.00 0.3
Jesus Sucre
IF TB vs PHI 58% 4.35 Lively, R 5.56 R 0.250 0.228 0.000 0.00 0.0 0.00 8 4500 9.3 3.8 3.25 3.25 % % 60 0.7 13.00 2.9
Mallex Smith
OF TB vs PHI 58% 4.35 Lively, R 5.56 L 0.343 0.367 0.086 0.00 0.0 0.00 5 5600 22.3 5.6 5.94 5.94 % % 27 1.1 15.00 2.7
Kevin Kiermaier
OF TB vs PHI 58% 4.35 Lively, R 5.56 L 0.143 0.213 0.071 0.00 0.0 0.00 3 5700 15.1 4.7 6.73 6.73 % % 55 1.2 5.00 0.9
Denard Span
OF TB vs PHI 58% 4.35 Lively, R 5.56 L 0.194 0.291 0.083 0.00 0.0 0.00 1 5900 17.4 5.5 6.73 6.73 % % 51 1.1 21.00 3.6
Andrew Knapp
IF PHI @ TB 42% 3.65 Yarbrough, L 2.25 B 0.176 0.243 0.000 0.00 0.0 0.00 8 5800 10.1 3.4 3.27 3.27 % % 50 0.6 5.00 0.9
Odubel Herrera
IF/OF PHI @ TB 42% 3.65 Yarbrough, L 2.25 L 0.348 0.373 0.109 0.00 0.0 0.00 3 7700 18.7 7.4 7.31 7.31 % % 62 0.9 6.00 0.8
Matt Duffy
IF TB vs PHI 58% 4.35 Lively, R 5.56 R 0.259 0.289 0.093 0.00 0.0 0.00 6 5900 15.1 6.6 5.41 5.41 % % 63 0.9 3.00 0.5
Cesar Hernandez
IF PHI @ TB 42% 3.65 Yarbrough, L 2.25 B 0.277 0.392 0.170 0.00 0.0 0.00 1 8400 20 9.2 8.64 8.64 % % 69 1 11.00 1.3
Ryan Yarbrough
P TB vs PHI 58% 3.65 Lively, R 5.56 L 2.25 0.000 0.000 2.70 6.7 1.75 10400 20.7 5.9 10.69 10.69 % % 15 1 6.90 0.7
Carlos Gomez
OF TB vs PHI 58% 4.35 Lively, R 5.56 R 0.192 0.268 0.173 0.00 0.0 0.00 2 6700 20.9 6.0 7.58 7.58 % % 44 1.1 0.00
Aaron Altherr
OF PHI @ TB 42% 3.65 Yarbrough, L 2.25 R 0.065 0.194 0.097 0.00 0.0 0.00 7 5900 17.8 4.0 3.65 3.65 % % 12 0.6 18.00 3.1
Ben Lively
P PHI @ TB 42% 4.35 Yarbrough, L 2.25 R 5.56 0.000 0.000 5.70 9.5 1.59 12200 13.4 11.8 10.22 10.22 % % 0 0.8 8.80 0.7
C.J. Cron
IF TB vs PHI 58% 4.35 Lively, R 5.56 R 0.213 0.260 0.128 0.00 0.0 0.00 4 5400 15.4 4.8 6.73 6.73 % % 55 1.2 7.00 1.3
Maikel Franco
IF PHI @ TB 42% 3.65 Yarbrough, L 2.25 R 0.242 0.338 0.273 0.00 0.0 0.00 6 7300 30.8 8.9 6.21 6.21 % % 31 0.9 9.00 1.2
Pedro Florimon
IF PHI @ TB 42% 3.65 Yarbrough, L 2.25 B 0.200 0.270 0.000 0.00 0.0 0.00 9 4500 5.8 1.2 2.05 2.05 % % 23 0.5 7.00 1.6
Scott Kingery
IF PHI @ TB 42% 3.65 Yarbrough, L 2.25 R 0.267 0.349 0.267 0.00 0.0 0.00 5 7700 20.8 8.8 7.37 7.37 % % 62 1 16.00 2.1
Ivan Nova
P PIT @ MIA 57.4% 3.91 Urena, R 5.06 R 4.81 0.000 0.000 6.10 7.1 1.19 17000 26.6 14.0 12.26 12.26 % % 49 0.7 26.80 1.6
Chad Wallach
IF MIA vs PIT 42.6% 3.91 Nova, R 4.81 R 0.148 0.179 0.037 0.00 0.0 0.00 8 3900 11.7 3.0 2.72 2.72 % % 25 0.7 0.00
Jose Urena
P MIA vs PIT 42.6% 4.60 Nova, R 4.81 R 5.06 0.000 0.000 5.30 7.3 1.19 11000 32.6 10.3 9.46 9.46 % % 0 0.9 7.25 0.7
Cameron Maybin
OF MIA vs PIT 42.6% 3.91 Nova, R 4.81 R 0.243 0.303 0.081 0.00 0.0 0.00 6 5400 14.1 3.7 4.33 4.33 % % 34 0.8 7.00 1.3
Starling Marte
OF PIT @ MIA 57.4% 4.60 Urena, R 5.06 R 0.241 0.348 0.222 0.00 0.0 0.00 3 8000 25.2 9.0 11.30 11.30 % % 62 1.4 32.00 4
Lewis Brinson
OF MIA vs PIT 42.6% 3.91 Nova, R 4.81 R 0.140 0.166 0.000 0.00 0.0 0.00 7 5900 12.6 3.2 3.55 3.55 % % 29 0.6 0.00
Francisco Cervelli
IF PIT @ MIA 57.4% 4.60 Urena, R 5.06 R 0.326 0.450 0.326 0.00 0.0 0.00 6 7600 25.2 10.3 6.83 6.83 % % 55 0.9 7.00 0.9
J.B. Shuck
OF MIA vs PIT 42.6% 3.91 Nova, R 4.81 L 0.571 0.623 0.286 0.00 0.0 0.00 1 3900 23.5 11.5 4.50 4.50 % % 0 1.2 7.00 1.8
Derek Dietrich
IF/OF MIA vs PIT 42.6% 3.91 Nova, R 4.81 L 0.290 0.333 0.097 0.00 0.0 0.00 4 6000 18.6 7.3 6.47 6.47 % % 59 1.1 3.00 0.5
Corey Dickerson
OF PIT @ MIA 57.4% 4.60 Urena, R 5.06 L 0.370 0.432 0.241 0.00 0.0 0.00 5 7300 24.1 11.7 10.04 10.04 % % 70 1.4 10.00 1.4
Colin Moran
IF PIT @ MIA 57.4% 4.60 Urena, R 5.06 L 0.317 0.378 0.122 0.00 0.0 0.00 7 6300 21.7 7.2 5.89 5.89 % % 45 0.9 3.00 0.5
Miguel Rojas
IF MIA vs PIT 42.6% 3.91 Nova, R 4.81 R 0.291 0.341 0.146 0.00 0.0 0.00 2 5700 16.4 7.2 6.04 6.04 % % 64 1.1 3.00 0.5
Starlin Castro
IF MIA vs PIT 42.6% 3.91 Nova, R 4.81 R 0.298 0.318 0.035 0.00 0.0 0.00 3 6800 14.4 7.3 7.02 7.02 % % 75 1 3.00 0.4
Gregory Polanco
OF PIT @ MIA 57.4% 4.60 Urena, R 5.06 L 0.216 0.371 0.373 0.00 0.0 0.00 2 8100 36.7 11.6 12.83 12.83 % % 49 1.6 5.00 0.6
Josh Bell
IF PIT @ MIA 57.4% 4.60 Urena, R 5.06 B 0.286 0.335 0.125 0.00 0.0 0.00 4 8400 20.9 7.9 10.88 10.88 % % 68 1.3 19.00 2.3
Sean Rodriguez
IF PIT @ MIA 57.4% 4.60 Urena, R 5.06 R 0.214 0.298 0.214 0.00 0.0 0.00 8 4600 16.7 4.3 3.87 3.87 % % 26 0.8 2.00 0.4
Josh Harrison
IF PIT @ MIA 57.4% 4.60 Urena, R 5.06 R 0.232 0.252 0.018 0.00 0.0 0.00 1 7400 22.1 6.5 10.32 10.32 % % 55 1.4 2.00 0.3
Yadier Molina
IF STL @ CIN 59.8% 4.99 Bailey, R 3.24 R 0.268 0.342 0.286 0.00 0.0 0.00 5 7400 24.2 8.9 10.35 10.35 % % 61 1.4 8.00 1.1
Tucker Barnhart
IF CIN vs STL 40.2% 4.01 Martinez, R 2.41 B 0.265 0.379 0.235 0.00 0.0 0.00 6 5500 16.9 6.1 4.46 4.46 % % 49 0.8 7.00 1.3
Adam Duvall
IF/OF CIN vs STL 40.2% 4.01 Martinez, R 2.41 R 0.130 0.210 0.152 0.00 0.0 0.00 5 6000 16.1 4.3 5.28 5.28 % % 37 0.9 19.00 3.2
Tommy Pham
OF STL @ CIN 59.8% 4.99 Bailey, R 3.24 R 0.327 0.413 0.164 0.00 0.0 0.00 2 9400 32.1 10.5 13.47 13.47 % % 56 1.4 1.00 0.1
Dexter Fowler
OF STL @ CIN 59.8% 4.99 Bailey, R 3.24 B 0.196 0.277 0.143 0.00 0.0 0.00 1 7700 24.6 7.0 11.05 11.05 % % 52 1.4 0.00
Phillip Ervin
OF CIN vs STL 40.2% 4.01 Martinez, R 2.41 R 0.200 0.270 0.000 0.00 0.0 0.00 8 5500 9.9 3.3 3.19 3.19 % % 50 0.6 2.00 0.4
Billy Hamilton
OF CIN vs STL 40.2% 4.01 Martinez, R 2.41 B 0.167 0.248 0.024 0.00 0.0 0.00 1 6600 18.6 6.2 6.88 6.88 % % 53 1 14.00 2.1
Jose Martinez
IF/OF STL @ CIN 59.8% 4.99 Bailey, R 3.24 R 0.373 0.455 0.235 0.00 0.0 0.00 4 7500 32.5 9.2 10.89 10.89 % % 41 1.5 7.00 0.9
Jose Peraza
IF CIN vs STL 40.2% 4.01 Martinez, R 2.41 R 0.250 0.232 0.063 0.00 0.0 0.00 2 5900 17.7 4.8 6.09 6.09 % % 40 1 7.00 1.2
Kolten Wong
IF STL @ CIN 59.8% 4.99 Bailey, R 3.24 L 0.162 0.227 0.000 0.00 0.0 0.00 8 5400 10.5 2.6 4.55 4.55 % % 43 0.8 0.00
Scooter Gennett
IF CIN vs STL 40.2% 4.01 Martinez, R 2.41 L 0.328 0.332 0.069 0.00 0.0 0.00 4 5700 16 6.4 6.77 6.77 % % 64 1.2 0.00
Homer Bailey
P CIN vs STL 40.2% 4.99 Martinez, R 2.41 R 3.24 0.000 0.000 5.60 6.4 1.08 11100 27.5 12.7 9.06 9.06 % % 27 0.8 14.15 1.3
Harrison Bader
OF STL @ CIN 59.8% 4.99 Bailey, R 3.24 R 0.143 0.235 0.000 0.00 0.0 0.00 7 5600 11 2.4 4.79 4.79 % % 36 0.9 16.00 2.9
Joey Votto
IF CIN vs STL 40.2% 4.01 Martinez, R 2.41 L 0.250 0.248 0.000 0.00 0.0 0.00 3 7500 17.5 4.4 9.02 9.02 % % 52 1.2 2.00 0.3
Alex Blandino
IF CIN vs STL 40.2% 4.01 Martinez, R 2.41 R 0.091 0.082 0.000 0.00 0.0 0.00 7 5700 6 0.6 3.57 3.57 % % 0 0.6 0.00
Matt Carpenter
IF STL @ CIN 59.8% 4.99 Bailey, R 3.24 L 0.174 0.324 0.174 0.00 0.0 0.00 3 6800 22.9 7.3 11.05 11.05 % % 60 1.6 0.00
Greg Garcia
IF STL @ CIN 59.8% 4.99 Bailey, R 3.24 L 0.333 0.445 0.444 0.00 0.0 0.00 6 5700 27.7 5.1 6.69 6.69 % % 0 1.2 4.00 0.7
Carlos Martinez
P STL @ CIN 59.8% 4.01 Bailey, R 3.24 R 2.41 0.000 0.000 6.20 9.1 1.29 19300 43.9 19.3 15.63 15.63 % % 27 0.8 37.55 1.9
Chris Iannetta
IF COL @ WSH 32.8% 2.82 Strasburg, R 2.21 R 0.300 0.374 0.125 0.00 0.0 0.00 2 6700 16.9 6.9 5.05 5.05 % % 57 0.8 0.00
Trea Turner
IF/OF WSH vs COL 67.2% 4.18 Anderson, L 5.65 R 0.211 0.296 0.070 0.00 0.0 0.00 1 8400 22.1 7.4 10.09 10.09 % % 60 1.2 8.00 1
Michael Taylor
OF WSH vs COL 67.2% 4.18 Anderson, L 5.65 R 0.167 0.176 0.019 0.00 0.0 0.00 8 5700 11.5 4.3 3.60 3.60 % % 54 0.6 21.00 3.7
Charlie Blackmon
OF COL @ WSH 32.8% 2.82 Strasburg, R 2.21 L 0.279 0.435 0.395 0.00 0.0 0.00 3 9800 25.4 11.6 7.97 7.97 % % 63 0.8 25.00 2.6
Stephen Strasburg
P WSH vs COL 67.2% 2.82 Anderson, L 5.65 R 2.21 0.000 0.000 6.80 9.3 1.03 22400 49.6 24.2 31.35 31.35 % % 62 1.4 12.50 0.6
Wilmer Difo
IF WSH vs COL 67.2% 4.18 Anderson, L 5.65 R 0.286 0.358 0.107 0.00 0.0 0.00 2 5400 14.4 4.2 5.87 5.87 % % 49 1.1 0.00
DJ LeMahieu
IF COL @ WSH 32.8% 2.82 Strasburg, R 2.21 R 0.308 0.402 0.262 0.00 0.0 0.00 1 8100 27.3 9.4 6.85 6.85 % % 46 0.8 18.00 2.2
Tyler Anderson
P COL @ WSH 32.8% 4.18 Strasburg, R 2.21 L 5.65 0.000 0.000 4.80 9.4 1.53 11700 36 10.4 9.78 9.78 % % 0 0.8 15.70 1.3
Gerardo Parra
OF COL @ WSH 32.8% 2.82 Strasburg, R 2.21 L 0.245 0.287 0.082 0.00 0.0 0.00 5 5800 13.2 4.7 4.16 4.16 % % 52 0.7 0.00
Ian Desmond
OF COL @ WSH 32.8% 2.82 Strasburg, R 2.21 R 0.185 0.236 0.185 0.00 0.0 0.00 6 7700 20.5 6.0 4.47 4.47 % % 33 0.6 14.00 1.8
Bryce Harper
OF WSH vs COL 67.2% 4.18 Anderson, L 5.65 L 0.292 0.463 0.396 0.00 0.0 0.00 3 10600 33.3 12.3 12.56 12.56 % % 58 1.2 20.00 1.9
Carlos Gonzalez
OF COL @ WSH 32.8% 2.82 Strasburg, R 2.21 L 0.236 0.304 0.236 0.00 0.0 0.00 4 7300 22.5 7.2 6.08 6.08 % % 43 0.8 5.00 0.7
Moises Sierra
OF WSH vs COL 67.2% 4.18 Anderson, L 5.65 R 0.222 0.276 0.222 0.00 0.0 0.00 7 4900 10.9 3.5 3.33 3.33 % % 46 0.7 0.00
Howie Kendrick
IF/OF WSH vs COL 67.2% 4.18 Anderson, L 5.65 R 0.319 0.369 0.192 0.00 0.0 0.00 5 6600 15.4 7.2 6.87 6.87 % % 71 1 3.00 0.5
Matt Wieters
IF WSH vs COL 67.2% 4.18 Anderson, L 5.65 B 0.214 0.348 0.214 0.00 0.0 0.00 6 5600 20.1 6.4 4.73 4.73 % % 40 0.8 16.00 2.9
Ryan McMahon
IF COL @ WSH 32.8% 2.82 Strasburg, R 2.21 L 0.087 0.152 0.000 0.00 0.0 0.00 8 7400 7.1 1.1 2.93 2.93 % % 6 0.4 0.00
Ryan Zimmerman
IF WSH vs COL 67.2% 4.18 Anderson, L 5.65 R 0.136 0.219 0.114 0.00 0.0 0.00 4 7600 18.1 3.6 7.63 7.63 % % 27 1 0.00
Trevor Story
IF COL @ WSH 32.8% 2.82 Strasburg, R 2.21 R 0.190 0.289 0.190 0.00 0.0 0.00 7 7700 16.6 6.6 3.73 3.73 % % 51 0.5 0.00
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Unique Players

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Max salary is $100,000 if left blank.

FLEX Position

Hitters vs Pitcher

Global Exposure Setting
apply exposure as

Randomness
Use Randomness
Players Per Team Change All MAX
MIN MAX MIN MAX
BAL
@
BOS
STL
@
CIN
TOR
@
CLE
NYY
@
DET
MIL
@
NYM
PIT
@
MIA
PHI
@
TB
COL
@
WSH
CWS
@
MIN
LAA
@
KC
ATL
@
CHC
ARI
@
LAD
SF
@
SD
OAK
@
SEA
NYY
@
DET
TEX
@
HOU
Add Stack (you can add up to 3) Click here for more info

If you want to create lineups with players from the same team (otherwise known as stacking) this is where to do it. This only applies to Hitters, and you can add a single stack with the remaining hitters not needing to be from the same team, or you can add multiple stacks per lineup so that all of the hitters are paired with other hitters from the same team.

To get started, click on the Add Stack link. You will need to select which teams you would like possibly used for the first stack. You can pick as many teams as you wish. You then will need to select a stack size, which is the number of hitters used from one of the selected teams.

If you want, you can add a 2nd and 3rd stack the same way as above. This is how you can create a lineup with 4 batters from 1 team, and 4 batters from another.

Positional Stacking
Create New Stacking Rule
Stack with of Positions From
Stacking Rules
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Load Playerpool
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Load Saved Crunches
Name Number of Teams Last Saved Delete
Name Number of Teams
  1. Take a tour

    Check out the features of Lineup Rewind.

  2. Sport Selection

    Select a sport (NBA, NFL) from this drop down menu.

  3. Site Selection

    Select a site (Fanduel, Draftkings etc.) from this drop down menu.

  4. Game Filter

    Use the Game Filter to remove any games you dont want to use. Useful for contests like Late Night NBA, or Sun/Mon night NFL.

  5. Score filter

    Select between projected score and actual scores from the day.

  6. Calculate Teams

    Hit 'calculate' to have Fantasy Cruncher create the best teams based on the actual data.

  7. Tour End

    Thanks for checking out the tour! If you want to use this tool to crunch numbers for fresh games, use lineup cruncher instead! If you have any more questions, check out our tutorials, browse the forums, or send us a message at support@fantasycruncher.com.