WhatIfSports NL Wild Card prediction: Bumgarner and the Giants top the Mets
WhatIfSports played the 2016 National League Wild Card game 1,001 times to predict which team -- the San Francisco Giants or the New York Mets -- will move on to play the Chicago Cubs in the NLDS.
The prediction engine favors San Francisco, winners in 61.4 percent of simulations. The visiting Giants averaged 4.77 runs, compared to 3.15 runs for the Mets. In Giants victories, the team won by an average score of 6.22-2.18. In Mets wins, the average score was 4.69-2.46.
Interested in the simulation details? View an example box score, including play-by-play and player stats.
The simulation predicts a strong performance from Madison Bumgarner. The Giants pitcher posted a 2.99 ERA and earned a win 51.5 percent of the time, with 25.7 percent of his starts producing a loss. The remaining 22.8 percent resulted in a no decision. Noah Syndergaard was less successful for the Mets. He had a 4.46 ERA and won 26.7 percent of his starts, with 47.5 percent resulting in a loss.
As a team, the Giants hit .278 with a .335 OBP. Brandon Crawford led the Giants in both categories (.356 BA, .403 OBP). The Mets didn't hit as efficiently, with a .214 team batting average and .267 OBP, but the Mets averaged 1.1 home runs per game, compared to just 0.4 for the Giants. Check out some more player stats from the simulation:
| San Francisco Giants Batting Stats from Simulation | ||||
| Player | AVG | OBP | SLG | OPS |
| Span, Denard | 0.276 | 0.315 | 0.361 | 0.676 |
| Belt, Brandon | 0.295 | 0.378 | 0.439 | 0.817 |
| Pence, Hunter | 0.319 | 0.382 | 0.447 | 0.829 |
| Crawford, Brandon | 0.356 | 0.403 | 0.482 | 0.885 |
| Posey, Buster | 0.278 | 0.345 | 0.373 | 0.717 |
| Pagan, Angel | 0.272 | 0.31 | 0.357 | 0.667 |
| Panik, Joe | 0.249 | 0.308 | 0.358 | 0.666 |
| Gillaspie, Conor | 0.278 | 0.326 | 0.397 | 0.723 |
| Bumgarner, Madison | 0.177 | 0.235 | 0.265 | 0.5 |
| Parker, Jarrett | 0.231 | 0.305 | 0.288 | 0.594 |
| Tomlinson, Kelby | 0.217 | 0.321 | 0.239 | 0.56 |
| Hernandez, Gorkys | 0.19 | 0.261 | 0.333 | 0.594 |
| Adrianza, Ehire | 0.188 | 0.235 | 0.188 | 0.423 |
| Blanco, Gregor | 0.125 | 0.167 | 0.125 | 0.292 |
| Brown, Trevor | 0.077 | 0.143 | 0.154 | 0.297 |
| New York Mets Batting Stats from Simulation | ||||
| Player | AVG | OBP | SLG | OPS |
| Reyes, Jose | 0.239 | 0.288 | 0.359 | 0.647 |
| Cabrera, Asdrubal | 0.228 | 0.271 | 0.391 | 0.662 |
| Cespedes, Yoenis | 0.243 | 0.31 | 0.46 | 0.771 |
| Bruce, Jay | 0.177 | 0.221 | 0.351 | 0.571 |
| Rivera, T.J. | 0.299 | 0.338 | 0.402 | 0.74 |
| Granderson, Curtis | 0.144 | 0.218 | 0.298 | 0.517 |
| Loney, James | 0.223 | 0.231 | 0.337 | 0.569 |
| Rivera, Rene | 0.208 | 0.286 | 0.303 | 0.589 |
| Syndergaard, Noah | 0.121 | 0.19 | 0.293 | 0.484 |
| Johnson, Kelly | 0.273 | 0.322 | 0.345 | 0.667 |
| d'Arnaud, Travis | 0.222 | 0.3 | 0.315 | 0.615 |
| Kelly, Ty | 0.209 | 0.306 | 0.302 | 0.608 |
| Lagares, Juan | 0.086 | 0.135 | 0.086 | 0.221 |
| Conforto, Michael | 0.316 | 0.435 | 0.684 | 1.119 |
| Plawecki, Kevin | 0.222 | 0.222 | 0.389 | 0.611 |
Interested in simulating the game yourself? Try MLB SimMatchup. Or, create your own Dream Team of current and historical players to challenge your favorite club.
