The SportsCrew | The True Meaning of the term "WAR" (Wins Above Replacement)
Everything you need to know about "WAR" and why the analytics community loves it so much
Baseball, MLB, Wins Above Replacement
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MLB: “WAR!” This is What It’s Good For!

MLB: “WAR!” This is What It’s Good For!

Wins Above Replacement (WAR) is an endeavor by the saber metric baseball community to encapsulate a player’s total contributions to their team in one statistic. WAR offers a conjecture to answer the question, “If this player got injured and their team had to replace them with a freely available minor leaguer or a player from their bench, how much value would the team be losing?” This value is formulated in a wins format, so we could say that Player X is worth +5.7 wins to their team while Player Y is only worth +2.9 wins, which means it is highly likely that Player X has been more valuable than Player Y. You should always use more than one metric at a time when evaluating players, but WAR is an all-encompassing measure and provides a useful reference point for comparing players.  war

WAR is not meant to be an unequivocal indicator of a player’s contribution, but rather an estimate of their value to date. Given the inadequacies of some of the available data and the assumptions made to calculate other components, WAR works best as an approximation. A 6 WAR player might be worth between 5.0 and 7.0 WAR, but it is pretty safe to say they are at least an All-Star level player and potentially an MVP.

While WAR is not as complicated as some people may think, it does take quite a bit of information to calculate and understand. Below we will show a synopsis of how WAR is calculated for position players and for pitchers.

Position Players- To calculate WAR for position players you want to take their Batting Runs, Base Running Runs, and Fielding Runs above average and then add in a positional adjustment, a small adjustment for their league, and then compute in replacement runs so that we are comparing their performance to replacement level rather than the average player. After that, you simply take that sum and divide it by the runs per win value of that season to find WAR. The simple equation looks something like this:

WAR = (Batting Runs + Base Running Runs +Fielding Runs + Positional Adjustment + League Adjustment +Replacement Runs) / (Runs Per Win)war2

Pitchers- The rubric for calculating WAR in terms of pitchers is more sophisticated than position players. While position player WAR is based on Batting Runs and Fielding Runs, pitching WAR uses Fielding Independent Pitching or FIP (with infield fly balls), adjusted for park, and prorated to how many innings the pitcher threw. FIP is translated into runs, converted to represent value above replacement level, and is then reformed from runs to wins.screen-shot-2017-01-11-at-1-16-33-pm

Why do we use WAR?

WAR is trying to answer the long-standing question: How valuable is each player to his team? Baseball is the agglomeration of many different parts and players can help their teams win through hitting, base running, defensive play, or pitching. Sizing up two players offensively is useful, but it discounts the potential contribution a player can make by saving runs on defense. WAR is a simple attempt to combine a player’s total contribution into a single value.

The goal of WAR is to provide a holistic metric of player value that allows for comparisons across team, league, year, and era. While there will likely be improvements to the process by which we calculate the inputs of WAR, the basic idea is something fans and analysts have desired for decades. WAR estimates a player’s total value and allows us to make comparisons among players with vastly different skill sets. Who is better, a slugging first baseman or a superlative defensive shortstop? WAR gives you a method for answering that question. Using a function on the FanGraphs website, I was able to generate a graph illustrating MVP players over the last 15 years that compares their WAR to one another.chart

Using WAR properly

Using WAR properly is difficult because it requires you to think more abstractly than some other aspects of life. The exact number is not as important as the basic range, but this is not just true of WAR. This is the case with all statistics in all parts of the game.

Perhaps one of the most controversial aspects of sabermetrics is the way in which WAR is used. Given the nature of the calculation and potential measurement errors, WAR should be used as a guide for separating groups of players and not as a precise estimate. For example, a player that has been worth 5.8 WAR and a player that has been worth 6.2 WAR over the course of a season cannot be distinguished from one another using WAR. It is simply too close for this particular tool to tell them apart. WAR can tell you that these two players are likely about equal in value, but you need to dig deeper to separate them.war4

However, a 6.4 WAR player and a 4.1 WAR player are different enough that you can have a high level of confidence that the first player has been more valuable to their team over the given season.

For position players, the largest point of contention comes in measuring defense and estimating the positional adjustment. Our measures of both are more uncertain than our measures of offense, so players who get a good amount of their value through their defensive ratings likely have more uncertainty around their WAR value than players who have defensive value closer to average. This does not mean that WAR is wrong or biased, but rather that it is not yet capable of perfect accuracy and should be used as such.

For pitchers, the biggest open question is how much credit a pitcher should receive for the result of a ball in play. When using FIP, it is assuming average results on batted balls. We know that there is some skill involved in suppressing hits on balls in play, but we have no idea exactly how much. Therefore, WAR will sell short players with certain FIP-beating skills and oversell those pitchers whose results fall short of their FIP for reasons within their control. At this point, we don’t have a good way of assigning credit more accurately for balls in play.


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