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Nene Hilario led the league in FG% in 2010, but attempted just 40 percent of the shots Kobe Bryant did. Blake Griffin attempted 20 more free throws than Kevin Durant, but made 148 fewer than he did. Also, Dwight Howard’s FT% was just .003 percentage points higher than his FG% – and this was his best free throw-shooting season since he was a rookie. What does any of this mean? According to my cranky grandpa, “Nothing! Now get outta the way of the TV before you make me miss SVU!” According to Nihilists, “Nothing! Or as much as anything else in this existence! Now get outta the way of the TV before I miss the nothingness that is SVU!” According to Kierkegaard, “It means only as much as you let it. Now get outta the way of the TV in case I decide to place importance on watching SVU!” Eesh. When it comes to fantasy basketball percentages, placing accurate importance on them is tricky. Most owners don’t do it. The quickest way to drown yourself out of a league (H2H, Roto – it doesn’t matter) is to estimate inaccurately or ignore it altogether and hope it all works out in the end. It won’t.

The boys over at Give Me the Rock are wiling away the summer months with a batch of solid statistical examinations. They recently calculated Effective Percentages, a clever way of removing the relativity from player shooting percentages and putting every player on a level playing field.

At season’s end, perennial sharpshooter Steve Nash finished third with a .912 free throw shooting percentage last season. Houston’s Kevin Martin finished five spots behind him with an .888 free throw-shooting percentage. Even if you knew that Martin shot more free throws than Nash last season (he did), you might not have paid any attention to how many more he shot (420 more) and even if you knew that Martin shot more than 2.5 times more free throws than Nash, you might still have figured that because most leagues tally FT% not FTA or FTM that Nash is still the better option. What the Effective Percentages illustrate is the weight those additional free throws place on players like Martin. Martin may have shot at a slightly lower percentage of free throws throughout 2010 than Nash, but not so much lower as to negate the fact that he shot so many more. A ton more. Simply put, Martin was a larger influence on his fantasy teams’ final FT% than Nash was to his. And as their season-end free throw percentages were relatively close to begin with, Martin’s Effective Percentage (ePCT) is way higher (1.015) than Nash’s (.895). So while Nash’s ePCT is slightly lower than his actual FT% because he shot slightly fewer free throws each game than the average fantasy player, Martin shot WAY more (the league average was 3.8 FTA, based on the average taken from the top 120 fantasy players of 2010).

GMtR’s comprehensive list of last season’s ePCT’s for free throws, field goals and 3-pointers is here for your own perusal. But if you want to empower yourself, I’ve added the (moderately simple formula below). FAIR WARNING: you’re going to have to remember your Please Excuse My Dear Aunt Sally rule.

ePCT = Plg + (Ppl-Plg) * (SAp/SAlg) =

Let’s use Steve Nash’s free throw shooting as an example:

Plg = the average FT% among the top 120 fantasy players in 2010. In this case, it was 78.2.
Ppl = the player’s FT%. In Nash’s case, it was 91.2
SAp = the player’s FTA per game. In Nash’s case, it was 3.3 FTA per game.
SAlg = the average FTA among the top 120 fantasy players in 2010. In this case, it was 3.8.

Now, apply that shizz!

ePCT= 78.2 +(91.2-78.2) * (3.3/3.8)

Now, simplify that shizz! (Parenthesis first)

ePCT= 78.2 + 13 * 0.868

Calculate from left to right, then slide the decimal place to wherever you want to!

89.484 = .895 = Steve Nash’s FT ePCT.

Knowing a player’s various ePCTs won’t make you more handsome or more popular (it’ll likely have the opposite affect), but it will paint a clearer picture of what the players you’re targeting on draft day are likely to do to your team’s percentages, which is a particularly valuable weapon to have when you consider how many owners ignore these stats, quantify them poorly or leave them to chance.