The National League MVP Award is given to the best player from that league in any given year. Brewers outfielder Christian Yelich took home the award in 2018 with an all-around great performance. He finds himself with just the sixth best odds in the field this year with the Phillies Bryce Harper currently listed as the odds-on favorite.
Below you will find the latest odds to win the NL MVP along with some advanced metrics for each player last year. We’ve included each players’ Weighted Runs Created Plus (wRC+) as well as their Wins Above Replacement (WAR) from the previous season. Below the odds you will find more detailed information about these metrics. A player with a DNQ (Did Not Qualify) for their wRC+ last year simply means they did not have enough plate appearances to accurately assess their performance.
The final column represents the implied probability of each player winning the award given the current market odds.
MVP odds courtesy of BetOnline
Player | Team | 2018 WRC+ | 2018 WAR | Odds | Change | MVP |
---|---|---|---|---|---|---|
Bryce Harper | Phillies | 135 | 3.5 | +500 | New | 13.01% |
Nolan Arenado | Rockies | 132 | 5.7 | +650 | New | 10.40% |
Paul Goldschmidt | Cardinals | 145 | 5.1 | +900 | New | 7.80% |
Kris Bryant | Cubs | DNQ | 2.3 | +1200 | New | 6.00% |
Manny Machado | Padres | 141 | 6.2 | +1200 | New | 6.00% |
Christian Yelich | Brewers | 166 | 7.6 | +1600 | New | 4.59% |
Anthony Rendon | Nationals | 140 | 6.2 | +2000 | New | 3.72% |
Rhys Hoskins | Phillies | 129 | 2.9 | +2000 | New | 3.72% |
Ronald Acuna Jr. | Braves | DNQ | 3.7 | +2000 | New | 3.72% |
Trea Turner | Nationals | 105 | 4.8 | +2000 | New | 3.72% |
Eugenio Suarez | Reds | 135 | 3.9 | +2200 | New | 3.39% |
Freddie Freeman | Braves | 137 | 5.2 | +2200 | New | 3.39% |
Anthony Rizzo | Cubs | 125 | 2.9 | +2500 | New | 3.00% |
Cody Bellinger | Dodgers | 120 | 3.6 | +2800 | New | 2.69% |
Corey Seager | Dodgers | DNQ | 0.5 | +3300 | New | 2.30% |
Javier Baez | Cubs | 131 | 5.3 | +3300 | New | 2.30% |
Joey Votto | Reds | 131 | 3.5 | +3300 | New | 2.30% |
Juan Soto | Nationals | DNQ | 3.7 | +3300 | New | 2.30% |
Justin Turner | Dodgers | DNQ | 4.2 | +3300 | New | 2.30% |
Trevor Story | Rockies | 127 | 5 | +3300 | New | 2.30% |
Charlie Blackmon | Rockies | 116 | 2.8 | +4000 | New | 1.90% |
Eric Hosmer | Padres | 95 | -0.1 | +5000 | New | 1.53% |
Josh Donaldson | Braves | DNQ | 1.3 | +5000 | New | 1.53% |
Lorenzo Cain | Brewers | 124 | 5.7 | +5000 | New | 1.53% |
Matt Carpenter | Cardinals | 138 | 4.9 | +5000 | New | 1.53% |
Max Scherzer | Nationals | Pitcher | 8.1 | +5000 | New | 1.53% |
Michael Conforto | Mets | 120 | 3 | +5000 | New | 1.53% |
Robinson Cano | Mets | DNQ | 2.9 | +5000 | New | 1.53% |
Andrew McCutchen | Phillies | 120 | 2.6 | +6600 | New | 1.16% |
wRC+ is one of the best metrics we have in evaluating the impact a player has on their team. We have provided the formula for this stat below, but the idea behind it is to normalize how many runs a player creates for their team adjusting for external factors like ballpark or era. A wRC+ of 100 indicates a league average player, meaning a batter with a wRC+ of 150 is 50% better than the league average at doing the most important thing he can for his team – creating runs.
(((wRAA per PA + league runs per PA) + (league runs per PA - ballpark factor x league runs per PA) / league wRC per plate appearance, excluding pitchers)) x 100
WAR is something of a catch-all statistic that evaluates how many wins a player is worth to their team compared to a replacement player. WAR basically says, if this player did not play for this team in this season and their backup was at best and average player, how many wins would that team be expected to lose? What is great about WAR is that it also factors in a player’s fielding contributions, not just their hitting statistics.
WAR is a bit more complicated for pitchers since they have less control over how the team around them will perform in the field, but using a metric called Fielding Independent Pitching (FIP) helps give a better idea of how to fairly compare pitchers to league averages.
(Batting Runs + Base Running Runs +Fielding Runs + Positional Adjustment + League Adjustment +Replacement Runs) / (Runs Per Win)
[[([(League “FIP” – “FIP”) / Pitcher Specific Runs Per Win] + Replacement Level) * (IP/9)] * Leverage Multiplier for Relievers] + League Correction