• That proper statistical evaluation is essential to understanding how baseball games are won and lost
• That the stats that are available today are superior to the ones available in the 1950s for this purpose
• That there is no one perfect stat to evaluate players
The closest we have to a perfect stat is WAR, which attempts to put all of a player’s contributions into one number to indicate how much value he created towards team success. Just to be clear, WAR is not perfect. But it is extremely reliable, which makes it extremely useful.
As you might recall from your math classes, correlation is the measure of the relation between two or more variables. Correlation ranges from (-1) to +1, where positive 1 means perfect correlation, which we rarely find. Generally, a correlation of 0 means that the two variables have no correlation, a positive number less than 0.5 implies a weak correlation and a value of 0.8 or greater means there is a strong correlation.
Jordan Tuwiner over at OriolesNation did the heavy lifting for the 2011 season, comparing fWAR to actual team Wins. He writes, “I compiled a ton of WAR data in an excel sheet and determined that the correlation between WAR and actual wins for the 2011 season to be 0.88.”
Tuwiner had done a similar study in 2009 and found that the correlation was 0.83 that season. He attributes the higher correlation last year due to the inclusion of a baserunning metric into the fWAR calculation last year that previously was not there.
There are still improvements to be made to the calculation, most notably in catchers’ defense. But even as fWAR stands now, we can use it to understand the vast majority of what goes into a winning player and a winning team.
WAR measures Wins Above Replacement, so you may be curious as to how many Wins a team comprised totally of replacement-level players would achieve. Tuwiner ran the numbers for MLB last season and concluded that in 2011 such a team would produce 42.2 Wins.
With that as our backdrop, I copied the Fans projections over at FanGraphs for the eight starting position players and the expected five starters in the rotation. Here is the wisdom of the crowd in fWAR form:
If we add the two totals from above to our 42.2 replacement number, we get 78.5 Wins. Now, it’s important to remember that these are projections, not actual numbers. Anyone can go over to FanGraphs and make a projection and I have no doubt that some of these are optimistic. My completely non-scientific way to handle this was not to include anyone else except for the team’s main players. Not included was Justin Turner’s 1.1 fWAR prediction or Frank Francisco’s 0.7 projection and anyone else who would play a game for the 2012 squad.
While recognizing the flaws inherent in this approach, I submit this as another reason why it’s foolish to project 100 losses for the 2012 Mets.
Finally, let’s look back and see how fWAR did in projecting the actual record of the Mets in 2011.
When you added up the fWAR from the players on the 2011 Mets, you came up with 23.5 in hitting and 8.8 in pitching for 32.3 total fWAR. Add in the 42.2 replacement level and you get 74.5 Wins. On the field, the Mets won 77 games. So we have 2.5 Wins that are unaccounted for by fWAR. Perhaps this is managerial impact or clubhouse chemistry or any other intangible. But this is the upper limit of how much those things mattered to the Mets last year.
Now, 2.5 Wins is hardly an insignificant thing, especially for a club that finishes a game or two out of the playoffs. But 97 percent of the Mets’ wins in 2011 can be accounted for in the statistical record of the players. And that’s why we acknowledge that intangibles exist but place very little importance on them.