A lot has changed with the index, but we’ve almost come full circle since the book was published. The inclusion of win shares was controversial at the time because wins above replacement had leapfrogged Bill James contribution and that hasn’t really changed in terms of popularity. However, James recently criticized WAR because it is based on runs scored and allowed instead of the number of games a team actually wins or loses. For most fans, their eyes gloss over when hearing this kind of talk, but for the mathematicians out there this is a huge deal.
Teams usually finish within five games one way or another of their “expected wins”, but occasionally there are wider ranges in play. This happened last season in the American League when the Yankees finished nearly ten games worse than they were expected to. So, some of the positive run differential may not have been as valuable as WAR would make it out to be. In short, WAR did not account for the clutch element. In terms of a career these things usually even themselves out. From season to season there could be significant variance. The goal of the index is not to come down one way or another, but to gather a collection of the top sabermetric minds in the industry. So, we include what most people know as bWAR, fWAR, and win shares. For those new to this, bWAR stands for the WAR configured by baseball-reference.com, and fWAR stands for the WAR configured by Fangraphs.
James configured his win shares to be three times the number of wins a team earned in a season. So, a 100 win team would have 300 total win shares. Even with that multiplier, win share totals end up being considerably higher than WAR totals. Part of this is based on the fact that win shares always begin at zero whereas players can have negative WAR totals. James would later develop loss shares, but we aren’t going to confuse the process further. Instead, we will divide the win share totals by five in order to scale win shares similarly to the two WAR formulas.
Admittedly, we are creating a bit of a Frankenstein monster in terms of math. This is usually what happens when a liberal arts guy starts crunching numbers. However, the goal is not to determine who the best catcher was or pinpoint exactly who is where. The goal is to measure a player’s fitness for the Hall of Fame. We do this by determining what the industry standard is for guys that are already in. Occasionally, we find outliers (or players that shouldn’t be in), but most of the time we are simply using what the BBWAA has already done to determine what they should do in the future.
We will try to define things as we go, but if you want a more in-depth overview of why we are doing what we are doing you can take a look at the home article that describes the process. In short, there are ten catchers in the Hall of Fame that were voted in by the BBWAA. We are ignoring the Veterans Committee selections because they are rife with so much bias that it ends up muddying the waters beyond recognition. We will start with career value and then break that down first. Then, we will move onto peak value and go from there. In a book format we would look at offense, fielding, and other considerations all at once. At the website we can look at those things individually.
Career Value
WS/5 | bWAR | fWAR | Total | |
Johnny Bench | 71.2 | 75.0 | 74.8 | 221.0 |
Yogi Berra | 75.0 | 59.5 | 63.7 | 198.2 |
Roy Campanella | 41.0 | 34.2 | 38.2 | 113.4 |
Gary Carter | 67.4 | 69.9 | 69.4 | 206.7 |
Mickey Cochrane | 55.0 | 52.1 | 50.6 | 157.7 |
Bill Dickey | 62.8 | 55.8 | 56.1 | 174.7 |
Carlton Fisk | 73.6 | 68.3 | 68.3 | 210.2 |
Gabby Hartnett | 65.0 | 53.9 | 53.7 | 172.6 |
Mike Piazza | 64.8 | 59.4 | 63.7 | 187.9 |
Ivan Rodriguez | 67.6 | 68.4 | 68.9 | 204.9 |
There are two major differences between the index and most other rating systems. First, it combines a career and peak value element. The idea is that career value can sometimes be misleading on its own. Some players are solid players for a very long time but are rarely ever great. You don’t want a Hall of Fame of stat compilers. Using these kinds of formulas does limit that to a certain extent. A player could be replacement level for a considerable time and add nothing to their career value. However, usually players offer some minimal value even when they are merely average.
The second major difference is that there are no hard and fast rules as to what is Hall of Fame worthy and what isn’t. It’s more about the players’ proximity to each other. When we see separation we begin to take notice. Roy Campanella is obviously separated from his peers, but there are clear extenuating circumstances there that we will get to in another article. The rest all fall above 150 combined wins. The beauty is that you don’t have to know what that means in order to offer sound analysis.
Mickey Cochrane is also lagging behind the others in career value because his career was cut short due to injuries. However, his peak value might mitigate those differences and some and he might close the gap. So, we will look at their peak values. In this case, we take the top ten year stretch for each player. Campanella only played for ten seasons, so his peak value will be the same.
Peak Value
WS/5 | bWAR | fWAR | Total | |
Johnny Bench | 54.6 | 59.9 | 60.4 | 174.9 |
Yogi Berra | 55.2 | 47.2 | 50.8 | 153.2 |
Roy Campanella | 41.0 | 34.2 | 38.2 | 113.4 |
Gary Carter | 52.4 | 60.8 | 59.0 | 172.2 |
Mickey Cochrane | 49.6 | 47.0 | 45.4 | 142.0 |
Bill Dickey | 46.0 | 42.4 | 42.7 | 131.1 |
Carlton Fisk | 38.0 | 41.9 | 40.2 | 120.1 |
Gabby Hartnett | 41.0 | 35.8 | 35.2 | 112.0 |
Mike Piazza | 54.6 | 54.0 | 59.1 | 167.7 |
Ivan Rodriguez | 43.0 | 51.8 | 50.2 | 145.0 |
Bill James once described good statistics as having the qualities of language. While that kind of description is compelling, I’ve always likened it to either a painting or photograph. Good numbers paint a more accurate picture of a player. When you compare career and peak values you get a sense as to what a player must have been like during his prime. Someone like a Carter, Piazza, or Bench was truly dominant throughout the decade. Players like Hartnett not so much.
What is interesting is that all three statistical sources begin from the same premise. They are comparing players with a replacement level player. In other words, we don’t compare them with the average because even an average player has value. We compare them with the triple AAA equivalent. However, what that looks like varies differently depending on the source. What specific value specific events have also varies slightly. This is particularly true when we evaluate the fielding side of things. We will focus on fielding in a subsequent article. The purpose of this article is to give us a baseline for catchers where we can jump off on as many tangents as we deem fit.
The Hall of Fame Index
Career | Peak | Total | |
Johnny Bench | 221.0 | 174.9 | 395.9 |
Yogi Berra | 198.2 | 153.2 | 351.4 |
Roy Campanella | 113.4 | 113.4 | 226.8 |
Gary Carter | 206.7 | 172.2 | 378.9 |
Mickey Cochrane | 157.7 | 142.0 | 299.7 |
Bill Dickey | 174.7 | 131.1 | 305.8 |
Carlton Fisk | 210.2 | 120.1 | 330.3 |
Gabby Hartnett | 172.6 | 112.0 | 284.6 |
Mike Piazza | 187.9 | 167.7 | 355.6 |
Ivan Rodriguez | 204.9 | 145.0 | 349.9 |
It’s at this point where I must remind the crowd of my usual disclaimers. First, the index is not meant to identify the greatest player at a particular position or in history. There are a number of problems with it that we will get to later when we cover individual categories like fielding. So, if people want to use it to justify that Bench is the greatest catcher of all-time be my guest, but that isn’t my intent. Secondly, there are no hard and fast cutoffs of who should be in and who should be out. It seems silly to set 300 as a line of demarcation and suggest that Cochrane doesn’t belong in. At the end of the day, we are talking fractions of a win even in the case of Hartnett. Remember, we have three different systems that are divided into career and peak value. The differences are magnified.
Additionally, identifying outliers is not the same thing necessarily as identifying mistakes. Roy Campanella is not a mistake by any stretch. He is a player with extenuating circumstances that override the statistical exercise. As an outlier, we place him aside and consider the rest. When a player gets north of Hartnett then he becomes a viable candidate. That doesn’t mean he definitely deserves to be in. It means that he should be a very compelling candidate. We will get those examples as well in other articles. Still, we will always use this article as a reference point for every other catcher we consider from here on out.