Daniel Murphy Tops 2016 Baseball Most Undervalued
By Patrick Buzzard
The overall principles for this case study were very straightforward. The task was to pick any sport and any of the past three seasons and determine who was the most underrated player that season. For this study, I chose from the onset to focus on baseball and the 2016 season. At this time, it was a brand new dataset so I was interested in exploring it. I also chose baseball because data for it is widely available on sites such as fangraphs.com and baseball-reference.com.
I first went about it by going onto fangraphs.com and taking all players with over 300 plate appearances. I chose 300 because I determined that it was a good number to encapsulate players such as Jarod Dyson. As an occassional role player, the fact that he produced 3.1 Wins Above Replacement (WAR) in the 2016 was particularly surprising.
I then sorted my fangraphs table by including wRC+, Fld, BsR, OBP, SLG, and WAR. I felt these statistics conveyed the overall five tools of a baseball player. WAR is all encompassing, wRC+ conveys hitting ability, Fld conveys overall fielding ability and takes into account throwing, BsR tells of a player’s ability on the bases, OBP tells of a player’s ability to make it onto the bases, and SLG tells of power. This dataset looked like this when it was all said and done: i
Just thinking that these stats work though is not enough. After running a regression on the WAR of the players I found a .848 r squared and all the variables to have P-Values below .05 meaning everything was significant. The results of that regression can be seen below:
|Adjusted R Square||0.845049092|
|Coefficients||Standard Error||t Stat||P-value|
Now that I found that the variables were significant I calculated their z-score for each individual player. I then combined them and since it was a rather larger number, took a z-score of the total z-score to come up with a total value above mean statistic.
Since value in baseball ultimately comes from how much less you paying for a player based upon what they are worth I then took the difference between what each player was worth for the 2016 season and then subtracted their actual salary to create their surplus value. I then multiplied their surplus value by the total value z-score to measure how much a player utilized the surplus they were giving their team. The result of this calculation is illustrated in the table below:
This led to players like Mike Trout, Kris Bryant, and Mookie Betts coming away with crazy numbers. This is a problem because they aren’t undervalued. They are both MVP’s. They are just under cost control. So, I removed from my dataset all those making under $1 million or over $20 million because those players all have been seen for the value they are worth or are under cost control. Then I removed MVP’s and other players who are of All-Star quality and haven’t hit the market. The end result of this can be seen in the table below:
After accounting for these variables, I found Daniel Murphy to be the most undervalued player of the 2016 season. He produced a surplus value of $31.9 million based upon the $12.5 million average annual value of his backloaded contract. Multiplying his surplus value by the 2.07 z-score he produces results in a score of 66.065. While certainly not the highest it is more than two standard deviations above the median score.
Daniel Murphy was able to accomplish this by vastly overperforming expectations of him going into his contract with the Nationals. Prior to the 2016 season Murphy had never reached a .900 OPS, only breaking the pivotal .800 OPS barrier in two seasons, though both of were not full seasons for him. He’d also never reached more than 3.1 WAR in his entire career. This past season he was worth 5.5 WAR. His wOBA of .408 was 83 points higher than any other full season of his career, 27 points higher than his best previous offensive season, his 49 game rookie campaign.
It remains to be seen whether or not Murphy can keep this production up. He didn’t gain any more patience, keeping a similar K% to his previous seasons along with a similar OBP-AVG, meaning that his higher OBP was largely AVG fueled. His XBH and hits in general did go up though, so it could have been that he added more power to his swing.
This could be the beginning of a new Daniel Murphy that the Nationals were able to capitalize on, or it could be a one season fluke. Either way the Nationals were able to get the most value for what they spent on Daniel Murphy out of every player on a free-market contract.