KEYNOTE: Reintroducing an old Bill James formula, applying historic/modern significance

I don’t recall the date I had begun walking to the library by myself but it probably once I turned 13. The walk was long 4 blocks which eventually would cover 20 minutes time, walking at my mom’s pace, as we would go up either the main street in our neighborhood in Southern Brooklyn, or we’d be curious and go up one of the nearby side streets to admire the housing and elements. I share in my mom’s everlasting sense of wonder and curiousness.  Enough so, that I did immediately graduate to one whole half of one floor of branch 44. Everywhere else in the library there were the adult books, the grown-up books, the mysterious microfilm, and the wooden racks that held the spines of the daily newspapers near the front.  We split time between that one and branch 56, near the subway, and a longer haul, always taking the scenic route, often combined with a shopping trip. Mom was always about ensuring there was enough food at home, even if there already was enough for a couple of weeks.
I seemed to recall gravititating to a few particular sections, with no real guidance as to which subject to lean to. The sports-related material were in the 740s of the Dewey Decimal System. Here I borrowed a good deal of books. One of these was an inspiring read about the Triple Crown horse racing winners. Another that comes to mind was a book on New Games, something of a hippie invention, but one that introduced such concepts as Earthball.

I had begun following baseball since about 1980, passively taking interest in the sport around 1976, hearing so much about the signing of one Reggie Jackson to the Yankees, and hearing next to nothing but about losing from the Mets side of things.  Dad seemed to be more of a Yankees fan, but I imagine he still cared about the Dodgers, as he was in his own teens attending games at Ebbetts Field. I never asked him about the 1950s rivalries between them, the Yankees and Giants.  I grew my interest in baseball through not only watching with my dad the Yankees AND Mets games, but the NBC Game Of The Week, a staple for decades at 1pm Saturday for pre-game, 115pm for first pitch. The 2 big names I had latched onto for heroes were Reggie, and Pete Rose. Maybe it was the constant exposure from TV (Reggievision, anyone?), or the way Dad pointed out the true hustle that was Charlie Hustle. While my folks did what they could to keep up with the neighbors (I don’t think we actually had Jones in the 6-story co-op we lived in), I was enrolled for one spring in the local Little League. I recall wearing #14 for Pete, and was something of a free swinger. I was OK, tho over the years I figured out how to swing late and develop more of a sense of patience. What did I know about tagging up, or coaching my teammates? I didn’t. But I did have fun, and I think the coaches understood.

So 1984 comes around, and I don’t stick around for Little League (the folks balked at having to pay for multiple seasons and probably wanted me on a short leash as it was).  As I check out other subjects like astronomy, astrology, some reference books, I find a new book among the sports. It’s The 1983 Bill James Baseball Abstract. Hello…..

This page from 2004 documents much of the innards of this publication.
Everything there is true. I learned about the wonders of Runs Created, The Favorite Toy, ballpark bias, The Pythagorean Method, a de facto Hall of Fame (and Museum) and thoroughly original analysis to explain what were on our baseball cards and TV sets. Sports radio was still some years away, as were the idea of pushbutton knowledge.  I was still yet to explore Elias’s masterwork publication in the annual Baseball Analyst.
I recall the library having to raise money to stay open more hours, and I was overjoyed to find that this book was for sale. And so I did purchase it..probably not more than one dollar.  My appreciation for the game grew and multiplied.

It’s in recalling this book that I introduce a formula that was introduced right alongside the Runs Created stat. I have not seen any further printing of the formula but as I use it, it’s become an absolute staple in my search for ideal players, whether to follow in fantasy, or replay league or otherwise for mindless historical comparatives. The latest such comparative was done in my previous post.

But now we turn to this formula: Percentage of Offensive Value.   James explains the stat to mean that a player uses more of his value when he bunts and sacrifices, and less so when swinging for the fences. From what I recall, he wrote nary a paragraph on the subject, with a small diagram explaining the difference. I believe he was properly giving more positive weight to the players who bothered to move the runners over in classic small-ball instead of playing solely for power or something derivative of Earl Weaver’s three-run-HR model (no SBs, no bunts, just get on base, and get them home)

The formula itself:
% = H(squared) /AB / RC
I don’t quite get why squaring a number should have the desired effect tho it might have something to do with the amount of standard deviations.
RC is Runs Created, calculated as RC = {(H+BB) x (TB)} / (AB + TB)} This is the original version, while its many spawns have included SB and sacrifice numbers.  The version I’m using is lifted from http://www.baseball-reference.com I’m pretty sure they stick to the old formula, but they don’t spell out exactly which version.

This formula, after dividing by the number of AB, spells out exactly how many runs the player would create if he had nothing but singles and BBs. When divided by the actual number of runs created, we’ll get a %, very typically between 25 and 75%, with numbers outside that range in extreme cases.  The higher the number, the greater amount of singles and walks and potential sacrifices were used in creating runs, while a lower amount suggested a power hitter is at work.

My own appropriation of %OV takes this standard and sets a balancing point of 50%. This mark introduces my concept of the Zen batter (a nod here to the Tao Of Baseball). Players within the 45-55% area are relatively balanced, being adept to hit for average and power alike, taking a few chances but also the ability to take one for the team, as it were.   Players below 40% and above 60% gathered real identities;  you can see the power and sacrifice qualities inherent in a ballplayer.   Ballparks I imagine will have some effects but these players generally don’t change stripes much at all.

Let’s go back to our 2 spreadsheets:
2012 MLB players:

Historical sample:

That last column with %OV is what we’re focusing on. Compare this percentage to the FF number and you’ll eventually uncover a different kind of matrix, one that represents more of the sense of a complete ballplayer.  Here are the 4 quadrants of the matrix:

Higher Fear Factor number (say, converted # in the 400s) with a lower %OV (below 45%)
In the historical sample, here are such players: Babe Ruth, Lou Gehrig, Aaron, Mays, Griffey, et al.

Higher Fear Factor number with a more balanced %OV: (IDEAL) Billy Williams, Moises Alou, Chuck Klein, Vladimir Guerrero, George Brett.

Higher Fear Factor number with a higher %OV (above 55%): (few examples, but 2012 players include Manny Machado, Brandon Phillips, Yunieksy Betancourt, Juan Rivera, Giancarlo Stanton)

Lower Fear Factor number with lower %OV (rare types: Rickey Henderson, Mike Cameron)

Lower Fear Factor number with a central %OV: Jose Guillen,

Lower Fear Factor number with higher %OV: Billy Hamilton, Hughie Jennings, Willie Keeler, David Eckstein, Lou Brock, Rod Carew.

Comparing Ruth to Gehrig again: Both have more of a true power number (surprise, but it’s Gehrig whose numbers are more centralized).

Willie, Mickey, Duke again:
Mays (418.772, .418)
Mantle (365.015, .353)
Snider (400.221, .423)
All three are strongly power oriented, Mantle more so than the others. At the same time, Mays is the most ‘dangerous’, with that FF number, while Mantle is more average at 365)

In the final post I’ll explore the concept of the ultimate batter based on the further comparison of these two stats.

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