Over the holiday season, I re-read (actually, re-summarized) the New Bill James Historical Abstract, which is still an indispensable resource over 13 years after its publication.
I certainly don’t need to go into who Bill James is. His annual Baseball Abstracts (1977-88) popularized and revolutionized in-depth statistical analysis of baseball, the way we think about the game today, and the way the game is operated.
Besides his annual Abstracts James published in 2003 The New Historical Baseball Abstract, where he took a look at the history of the game decade by decade, talking about how the game was played, where and by whom. This is one of my favorite baseball books; its bases are loaded with stories, statistics, and trivia and it’s just some kind of fun on every page. I pick it up often, and it’s the perfect remedy to a cold winter day.
The first part of the book, about 250 pages in my edition, looks at the game decade by decade, from the 1870s on, and each section starts with a quick listing of fun facts such as notable nicknames, (Death to Flying Things, Spinach, Ol’ Stubblebeard, The Grey Eagle, The Donara Greyhound), biggest and smallest players, most disappointing player (or over-hyped — the Clint Hurdle Award), attendance, births and deaths, most home runs, most wins, most strikeouts, best outfield arm, fastest player, best baseball book and so on. After this introductory section, James writes a number of brief articles looking at the issues and the players of that time period. These can be little biographical notes on a player of interest (Kirby Higbe, Gates Brown, Lyman Bostock) or more statistically oriented, such as his piece on why run production dropped so dramatically in the 1960s.
The second part of the book is also great, and a bit longer than the first section. Here James appraises the top players of the game, position by position, and gives his estimation as to who was the best. James begins this section with a brief overview of statistical methods for appraising baseball players and review different variations of formulas that have been carefully tailored to different time periods and different standards of record keeping. For example, did you know that the National League did not keep statistics on “caught stealing from 1926 to 1950? Well, they didn’t. You can’t look them up. And so the formula for evaluating players in that time period has been adjusted to account for that.
While casually skimming through the end of the player ranking section, I ran across an essay titled “Baseball 2015” which is on page 316-17 of the hardcover edition.
James made four predictions which I quote directly:
- That baseball will eventually solve or contain the problem of economics corroding competitive balance.
- That baseball will eventually gain control of the problem of the ever-lengthening games.
- That the hundred-year trend of using more and more pitchers will end, and complete games (for the first time ever) will soon become more common, rather than less.
- That the trend toward more strikeouts and more homers from the top of the order to the bottom will also end soon.
From here on out the words are mine.
As long as baseball has existed there have been cries about players’ salaries from players, owners, and fans. This chart shows pertinent payroll values (in millions of dollars) since 1985 and is from data at Baseball-Reference.com . The data runs through 2013 only to allow for salary bias due to revenue sharing.
I chose median (average) to offset the effects of either big-spending teams like the Yankees or the low-spending teams like the 2012 Indians. The important numbers are the two columns at the right; the first is the number of teams with payrolls more than one standard deviation, or (<-1SD) below the median payroll, or in 2013, payrolls below approximately $39.1 million, of which there were two. The last column is the number of teams with payrolls greater than one standard deviation (>+1SD) above the median, or payrolls above approximately $143.9 million, of which there were five.
Baseball salary data at B-R only goes back to 1985, and at the time of James’ writing (1999-2001), there was cause for legitimate concern. Baseball did appear to be separating into two camps, with 13 of the 30 teams 1 standard deviation removed from the median. This seems to have corrected itself in the intervening years, with 2013 having only 7 outlying teams.
There are probably two reasons for this: The first is improved revenue streams top-to-bottom throughout baseball. This does not mean all teams are equal in revenue–as long as teams negotiate local TV rights, advertising, and other income sources outside of a national TV contract, there will be disparities, but they will be smaller than in the past. The current local TV broadcast rights range from around $18 million for Miami and Pittsburgh to $150 million for the Texas Rangers. As large a spread as this may seem, in terms of bottom lines, the #1 team in revenue was the Yankees, with estimated revenue of $471 million. The bottom team were the Rays at $167 million. A revenue disparity of 3x is far different that the 25-50x that were common at the time of James’ writing.
The other team more than 1 SD below the 2013 median salary is the Marlins and no one knows what they’re doing, including their ownership. They made a disastrous attempt at buying success in 2012 that worked so well every player acquired–Mark Buehrle, Jose Reyes and Josh Johnson, as well as homegrown talent Hanley Ramirez was jettisoned by the start of 2013 and Ricky Nolasco was dealt a few months later. There’s a world of difference between unfair economic conditions and inept management, which is what the Marlins currently have. Their issues are not reflective of baseball economic realities but are completely self-induced. They have resources and are choosing not to use them on payroll.
The second reason for less payroll variability is the understanding that buying a championship is extremely difficult to do. It’s not impossible–solid arguments can be made that the 2009 Yankees purchased their World Series championship and the 2013 Dodgers were rudderless until big-money acquisitions like Adrian Gonzalez, Carl Crawford, Nolasco, Ramirez and Zack Greinke came together and began playing like a team. The fact that something can happen is far different from that it will happen.
To explain, the teams with the most wins in 2013, the Red Sox and Cardinals, had the 3rd and 9th-highest payrolls. In 2012 the Nationals had the most wins with the 15th-highest payroll. The difference is the disparity in payrolls appears to be diminishing, and in many cases low payrolls are made by choice and not out of necessity or lack of resources. In other words, outspending the league helps, but it’s far from a guarantee.
Big contracts like the ones given to Albert Pujols, Josh Hamilton, Prince Fielder and Robinson Cano get all the publicity, but success lies in the support players who complement these signings. The problem Bill James identified is essentially solving itself as teams realize how difficult it is to purchase victories and instead try to develop it. Can teams increase the odds of winning by spending more money? Of course, but the teams of the future are spending more money on talent recognition, development, and scouting and less on free agency (relatively speaking) because free agency pays for past performance. As this realization takes hold, the payroll disparities will lessen–they won’t disappear as long as one team is willing to spend freely, but payroll choices will be driven by logic instead of blind hope. The third-lowest payroll in 2013 belonged to…the Chicago Cubs? It wasn’t for lack of money, but from an understanding that they were nowhere near contention and spending money on players for a team at least a year away from contention doesn’t make sense. It’s the same reason the A’s and Rays have been successful with lower payrolls. Free agency is a really difficult way to build a team, so teams that don’t invest heavily there aren’t at a huge disadvantage.
Like just about everything he researches, Bill James was right on the money in identifying this important issue in the game. Issues come and issues go, with the only constant being they will generally correct themselves if given the chance. In the case of economic disparities, teams found new revenue streams and simply resisted the urge to spend with the big-market teams and found they could still have success, which has led big market teams to the realization that spending efficiently is better than spending big.
It’s a fantastic read, not because of it’s author’s name-brand but because of the in-depth coverage of the history of the game. It comes highly recommended.
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