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If Elias Used WAR

Posted By Noah Isaacs On November 15, 2011 @ 11:30 am In Daily Graphings | 37 Comments

Yesterday, Buster Olney reported that Major League baseball and the Major League Baseball Players Association were nearing agreement on the new CBA. Olney notes that the new collective bargaining agreement will likely address free agent compensation by getting rid of compensation picks in the first round. As I noted last week, there are many fundamental problems with free agent compensation, as we currently know it. My focus last week was on how the system unintentionally provided incentives for rich teams to not just sign one type A free agent, but sign multiple. In addition to this unintended byproduct of the system, I briefly mentioned the archaic stats used to rank type A and B players. This led me to wonder what would happen if MLB instructed the Elias Sports Bureau to use more advanced metrics.

The rankings are based off of the past two seasons’ worth of statistics. With that in mind, I began thinking about what an idealized ranking system would look like. It didn’t take long to figure that Wins Above Replacement would be much better than the current equation used by the Bureau. Under the current system all players are divided into five different groups:

Groups Stats (From MLBtraderumors.com)
1B, OF and DH PA, AVG, OBP, HR, RBI
2B, 3B and SS PA, AVG, OBP, HR, RBI, Fielding%, TCs
C PA, AVG, OBP, HR, RBI, Fielding%, Assists
SP Total games (total starts + 0.5 * total relief appearances), IP, Wins, W-L Percentage, ERA, Strikeouts
RP Total games (total relief appearances + 2 * total starts), IP (weighted slightly less than other categories), Wins + Saves, IP/H ratio, K/BB, ERA

Once the players have been divided, they are ranked against their peers. The ranking works as follows: within each statistic, the player in question is ranked against his positional peers. If there are 30 players in a group, then the player the most HRs gets credited with 30 points, the player with the second most HRs would be credited with 29 points and so on until you reach the player with the fewest HRs, who will be credited with 1 point. All points are then scaled so that the max score for each stat is 100 (divide by the number of players in the given group and them multiply by 100). The scores for each stat are averaged to give the player his final score. If a player led his group in all stats, his final score would be 100. Once each player has been given a score, all the groups are aggregated. The top 20% of the aggregated list is deemed a type A player and 21%-40% is deemed a type B player.

Thanks to MLB Trade Rumors I was able to grab the rankings of all players for the 2010-11 seasons and take a look at their respective WARs. The first thing I did was divide the players into their respective groups. After the players were in the right groups I looked at the composition of each group. The average two-year WAR for type A Catchers was 6.2. The average type A player in Group 1 (1B, OF, and DH) had 8.1 Wins Above Replacement over the past two years. Similarly, Group 2 (2B, 3B and SS) had 8.1 Wins Above Replacement over the same time span. This seemed to be an interesting coincidence, but then I looked at Group 4 (SP). The average type A Starting Pitcher had 8.2 Wins Above Replacement over the last two years. It is surprising given their respective makeups, that groups 1, 2 and 4, would have nearly identical WAR. Finally, I looked at type A Relief Pitchers, and found that the averaged a measly 2-year WAR of 2.5. By looking at the average WAR for each group we can appreciate how type A players in certain groups are relatively valued. It seems as though all positions are valued approximately the same under the current system (catchers are slightly over valued) with the exception being relief pitchers. A type A relief pitcher nets the same compensation as any other position, but the value of the type A relief pitcher is on average a third of the value of other type A players (as measured by WAR). This overvaluation of Relief Pitchers is clearly an issue that needs to be addressed in the upcoming CBA.

Finally, I compared the current rankings as calculated by Elias and the idealized rankings using WAR where the top 20% of players according to WAR would be considered type A. The Venn Diagram below shows two sets and their intersection with each other. The red circle is the number of type A players according to the Elias ranking, and the blue circle is the number of type A players according to my WAR ranking. The intersection of the two groups, as seen in the purple shading, is the number of players that belonged to both sets, i.e. the number of type A players unchanged by the new ranking. At Bradley Woodrum’s behest, I’ve slapped in some festive Marios to make these impressive diagrams even more digestible.

 

If you look at the Venn diagrams above, you’ll see that a high percentage of the Elias type A players would continue to by type A players under the WAR ranking.  If you exclude RPs, then 92% of Elias type A players would be WAR type A players. This is a much higher number than I would have expected. That being said, you can see from the numbers that lie only in the blue areas that the Elias ranking misses a lot of good players – has a high type II error. Finally, the Relief Pitcher Venn diagram illustrates the huge incongruence of the WAR rankings and the Elias rankings. Of the 52 type A RPs, only one of them would be type A according to WAR. I think the WAR ranking would be a great improvement, but the Elias rankings was not as awful as I had initially thought.


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