We hear the expression “He’s a black hole on offense” often among fans and media types, but nobody so far has tried to quantify it. In layman’s terms, I’d say that a “black hole” is a player who shoots the ball almost every time he touches it. He rarely passes the ball to an open teammate, and shoots a low percentage to boot.

If we were to quantify it, we’d have to say that such a player would have a high Usage Rate (Usg%), a low Assist Ratio (Ast%), and a below-average True Shooting Percentage (TS%). But, what is considered a high Usg%, a low Ast% and a below-average TS%?

For Usg%, if the shots are distributed equally among the 5 players on the court, then the average Usg% would be 20%. To figure out Ast% and TS%, I divided all NBA players into 3 categories: Bigs, Wings and Point Guards. The Bigs include Power Forwards (PF) and Centers (C). The Wings include Shooting Guards (SG) and Small Forwards (SF). And Point Guards include all players that man the PG position in the NBA.

Once the 3 groups have been delineated, it became easy to calculate the average Ast% and TS% for each of the 3 groups:

       Ast%   TS%    Usg%
Big    8.05   0.553  20.0
Wing  13.01   0.541  20.0
PG    23.89   0.533  20.0

With this information at hand, we can now calculate the “Black Hole Index” using this formula:

100 * (1 – (AvgUsg% / Usg%) + (1 – (TS% / AvgTS%) + (1 – (Ast% / AvgAst))

The first portion of the formula calculates the percentage of possessions that the player uses above the average 20%. However, if a player’s Usg% is below 20%, then the player is not using more possessions than he should and is automatically disqualifed as a Black Hole.  In my spreadsheet, I set an IF condition that automatically filters out players with a Usg% of 20.5 or below, in order to remove players that are marginally over the average Usage Rate of 20.

The second portion calculates the TS% below the average TS% for the position. And the third portion calculates the Ast% below the average Ast% for the position.

So, who’s the black hole in the NBA? To classify the players, I decided to remove marginal players who don’t have enough FGAs to qualify. Consequently, I set the minimum FGA/G to 4.0 and the minimum Games Played to 20. 130 players qualified.

Top 10 in Black Hole Index (BHI):

Player          Pos    USG%     TS%   AST%    BHI
Rashad McCants  Wing   25.94   0.474  8.31   71.41
Gerald Green    Wing   26.65   0.513  7.89   69.38
Al Thornton     Wing   23.02   0.493  7.22   66.52
Rudy Gay        Wing   26.33   0.521  8.53   62.16
Josh Howard     Wing   26.15   0.526  8.70   59.37
Travis Outlaw   Wing   21.72   0.537  6.70   57.11
Michael Beasley Big    28.41   0.508  6.55   56.37
Leandro Barbosa PG     24.20   0.586 13.71   50.70
Corey Maggette  Wing   24.94   0.579  8.61   46.67
Marreese Speights Big  22.58   0.573  5.02   45.47

Few surprises on the list, like Speights and Beasley, but the names coming up on top are some of the most known “black holes” in the league. In fact, if it weren’t for the maximum criteria for games played, Monta Ellis would have topped the list with a BHI of 81.07.

Some of the other more known Black Holes:

Rk Player          Pos   USG%     TS%    AST%    BHI
29 Nate Robinson   PG    23.95    0.541  20.88   27.67
32 Kevin Martin    Wing  27.72    0.594  12.04   25.44
42 Eddie House     Wing  20.81    0.582  10.44   15.99
43 Ronald Murray   Wing  23.52    0.548  12.94   14.27
47 Danny Granger   Wing  29.10    0.580  15.55    4.53

I’m pretty sure the formula can be further adjusted and refined. But for the time being, the list above should help identify some of the biggest black holes in the league.

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