Baseball Prospectus is looking for a Public Data Services Director. Read the description here.

There are two ways to build a winning baseball team. One way is to have a few players who are extraordinarily good. Alternatively, you can have few players who are extraordinarily bad. Conversely, there are two reasons that baseball clubs fail. They can have an absence of good players-or an abundance of bad ones.

This distinction might seem at once too basic and too esoteric. Nevertheless, it is something that can get lost in our obsession with replacement level, which begins to assign value at a relatively low threshold, and seems to divide players into good, “gooder”, and “goodest.” If you take two teams whose offenses are both 180 runs better than replacement, for example, that doesn’t tell you very much about how those teams are composed. You might have one team who has two stars with VORPs around 90, and a bunch of zero-value scrubs (in VORP) rounding out the roster, and another team that has no star talent at all, but gets a 20 VORP contribution out of each of its nine regulars.

Suppose instead that we divide our accounting into above-average and below-average talent. For example, looking at this year’s Yankees:

Hitter            PA    VAA    VBA
Derek Jeter      230  +18.6     ---
Bobby Abreu      227    ---   -13.6
Alex Rodriguez   223  +22.6     ---
Robinson Cano    201    ---    -8.1
Jorge Posada     181  +22.6     ---
Johnny Damon     180    ---    -1.4
Jason Giambi     174   +3.3     ---
Hideki Matsui    157   +4.1     ---
Melky Cabrera    147    ---   -10.6
D. Mientkiewicz  135    ---    -7.6
Josh Phelps       59    ---    -0.2
Wil Nieves        31    ---    -5.9
Other Hitters     35   +1.6    -3.4
Hitters               +72.8   -50.9

Pitcher          IP     VAA     VBA
Andy Pettitte   71.2  +12.7     ---
Chien-ming Wang 48     +3.2     ---
Mike Mussina    35.1    ---    -4.4
Kei Igawa       30.2    ---   -11.3
Luis Vizcaino   26      ---    -8.4
Scott Proctor   25.1   +2.3     ---
Darrell Rasner  24.2    ---    -1.3
Brian Bruney    23     +9.2     ---
Mike Myers      23     +4.1    ---
Matt DeSalvo    21.2    ---    -1.6
Kyle Farnsworth 20.1    ---    -1.4
Sean Henn       17.1    ---    -2.0
Mariano Rivera  16.2    ---    -2.3
Carl Pavano     11.1    ---    -1.1
Philip Hughes   10.2   +1.7     ---
Tyler Clippard  10     +1.2     ---
Other Pitchers  25.1   +1.3    -9.7
Pitchers              +19.9   -27.7

Total                 +92.7   -78.6

The terms “VAA” and “VBA” will not be familiar to you, but you will probably have no trouble figuring out what they mean. “VAA” means Value Above Average, which is literally just a player’s VORP using league average rather than replacement level as the baseline. If a player is below average, his VAA isn’t negative; it is simply zero. “VBA” stands for Value Below Average, which is exactly the opposite.

If you look at the Yankees, you’ll find that both their VAA and VBA are fairly high; they’ve had a lot of really outstanding performances (Alex Rodriguez, Jorge Posada), and a lot of really terrible performances (Kei Igawa, Bobby Abreu). If you sum VAA and VBA, you should get a number which is fairly close to a team’s run differential. In this case, the Yankees’ total is 14.1, which is a good match for their actual plus-19 run differential.

For contrast, let’s take a look at the Brewers:

Hitter            PA     VAA     VBA
Prince Fielder   228   +13.1     ---
J.J. Hardy       226   +16.2     ---
Rickie Weeks     199    +0.7     ---
Bill Hall        197     ---    -0.9
Johnny Estrada   169    +3.4     ---
Geoff Jenkins    150    +8.0     ---
Kevin Mench      120     ---    -4.7
Tony Graffanino  120     ---   -11.2
Craig Counsell   117     ---    -3.3
Corey Hart       108     ---    -0.1
Tony Gwynn        76    +2.7     ---
Gabe Gross        67    +2.1     ---
Damian Miller     54     ---    -3.0
Other Hitters    138    +2.3    -4.0
Hitters                +48.4   -27.2

Pitcher          IP      VAA     VBA
Jeff Suppan      73     +4.3     ---
F. Cordero       21     +9.5     ---
Ben Sheets       68.1   +3.3     ---
C. Villanueva    33.1   +4.6     ---
Claudio Vargas   49.1   +0.6     ---
Chris Capuano    59.1    ---    -1.2
Matt Wise        20.2   +3.3     ---
Derrick Turnbow  22.1   +2.2     ---
Chris Spurling   16.2   +2.3     ---
Brian Shouse     12.1   +1.2     ---
Greg Aquino       7.2    ---    -2.2
Dave Bush        61.2    ---   -12.3
Elmer Dessens    15      ---    -8.4
Pitchers               +31.5   -24.0

Total                  +79.9   -51.2

The Brewers have had a handful of All-Star caliber performances this year, notably from Prince Fielder, J.J. Hardy, and Francisco Cordero. They are more noteworthy, however, for their absence of poor performances. Whereas the Yankees have seven players who have cost them five or more runs below average this year, the Brewers have only three. Thus, the Brewers rate as the better team, even though they have somewhat less star talent:

             VAA     VBA       Net
Yankees    +108.7   -94.2     +14.5
Brewers     +79.9   -51.2     +28.7

We can run this calculation, of course, for every team in the league, which is exactly what we’re going to do right now:

Value Above Average

That chart is quite an eyesore-I’m definitely not channeling Edward Tufte-but let me try and explain what’s going on. We have VAA on the horizontal axis and VBA on the vertical axis. The very best teams, who have both a high VAA and a low VBA, will be in the top right-hand side of the plot, and the very worst teams in the bottom left. As for that tic-tac-toe board in the middle and all those extra letters and numbers-actually, this works better if we rotate the chart at a 45 degree angle:

Run Differential

The meanings of the axes have now changed. The horizontal axis now represents run differential, with the better teams toward the right, while the vertical access now represents what I’m calling “sharpness”. A team is “sharp” if, like the Yankees, it has a large degree of variance in its talent base-some very good players, but also some very poor players. A team is “flat” if, like the Brewers, its value is distributed fairly evenly across its roster. Sharper teams appear toward the bottom of the graph, and flatter teams toward the top, which is slightly counterintuitive, but jibes better with our first version of the chart. Teams that are neither sharp nor flat are what we might call “natural” (I’m borrowing from music terminology), which means that have a normal assortment of stronger and weaker players.

This will probably give you a hint and what that tic-tac-toe board means. We’ve divided the chart into nine regions, with each region labeled according to its sharpness and the run differential of the team in question. In particular, the nine regions are as follows:

  • 1F: Strong, Flat teams. These are clubs which have very few weak spots, but perhaps only an average amount of star-level talent. Examples: Brewers, Diamondbacks.
  • 1N: Strong, Natural teams. Plain ol’ good baseball teams, with their share of strong spots and not too many weak spots. Examples: Mets, Tigers.
  • 1S: Strong, Sharp teams. Perhaps the most interesting category, these teams have plenty of star talent but also a handful of grave weaknesses. Examples: Angels, Twins.
  • 2F: Average, Flat teams. These are .500 clubs with well-rounded rosters but few All-Stars. Example: Orioles; the Giants are the only other club in this region, but that’s a bit strange considering that they have Barry Bonds.
  • 2N: Average, Natural teams. Average in every way, shape and form, these teams have the usual array of strengths and weaknesses. Examples: Mariners, Blue Jays.
  • 2S: Average, Sharp teams. Teams with plenty of star-level talent, but which have holes in the lineup that preclude them contending for a title. Examples: Yankees, Marlins.
  • 3F: Poor, Flat teams. These clubs have no glaring weaknesses, but their distinct lack of star talent renders them below average. Examples: Reds, Astros.
  • 3N: Poor, Natural teams. Standard-issue bad baseball clubs. Examples: Royals, Nationals.
  • 3S: Poor, Sharp teams. Finally, we have those teams that are sort of half-full with star talent, but three-quarters empty of the average talent they need to build a winning baseball team. Example: Devil Rays.

So, you’re probably asking, is it better to be sharp or be flat? And is it better to be natural than either of the above? There are intuitive arguments either way. On the one hand, it’s generally much cheaper to exchange replacement-level talent with average talent than it is to replace average talent with superstar talent, particularly if you have extra financial or scouting resources at your disposal. There’s little chance that the Yankees will still be employing Doug Mientkiewicz, for example, if they’ve limped back into the race by the trade deadline, and their marginal gains are going to be very high once they replace him. On the other hand, sharp teams do not do a very good job of diversifying themselves, and may be more vulnerable to injuries or other kinds of attrition problems. The Cardinals, who were an extremely “sharp” team heading into this season, are a good example of this; then Chris Carpenter gets hurt, Jim Edmonds and Scott Rolen start showing their age, and what you’re left with is a team that… well, falls flat.

It’s almost like you have two of Bill James’ seminal concepts at loggerheads. The Talent Pyramid would tend to suggest that sharp teams have an easier job of improving themselves, while the Plexiglass Principle might favor flat ones. My hunch is that that the argument for sharpness prevails; in fact, I’m almost certain that being sharp is better than being flat, though I don’t know if it’s better than being natural. But I haven’t run the numbers yet, and that’s going to need to wait until next week.

Thank you for reading

This is a free article. If you enjoyed it, consider subscribing to Baseball Prospectus. Subscriptions support ongoing public baseball research and analysis in an increasingly proprietary environment.

Subscribe now
You need to be logged in to comment. Login or Subscribe