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Basketball Statistician's Digest:
Game Theory: When it comes to athletic prowess, don’t believe your eyes.
From The New Yorker By Malcolm Gladwell
Download source here: ' Game Theory ~ When it comes to athletic prowess, don’t believe your eyes. '
"... But how do we know that we’re watching a great player? That’s an easier question to answer when it comes to, say, golf or tennis, where players compete against one another, under similar circumstances, week after week. Nobody would dispute that Roger Federer is the world’s best tennis player.
Baseball is a little more complicated, since it’s a team sport. Still, because the game consists of a sequence of discrete, ritualized encounters between pitcher and hitter, it lends itself to statistical rankings and analysis. Most tasks that professionals perform, though, are surprisingly hard to evaluate. ..."
"... Basketball presents many of the same kinds of problems. The fact that Allen Iverson has been one of the league’s most prolific scorers over the past decade, for instance, could mean that he is a brilliant player.
It could mean that he’s selfish and takes shots rather than passing the ball to his teammates. It could mean that he plays for a team that races up and down the court and plays so quickly that he has the opportunity to take many more shots than he would on a team that plays more deliberately. ..."

"... In “The Wages of Wins” (Stanford; $29.95), the economists David J. Berri, Martin B. Schmidt, and Stacey L. Brook set out to solve the Iverson problem.
Weighing the relative value of fouls, rebounds, shots taken, turnovers, and the like, they’ve created an algorithm that, they argue, comes closer than any previous statistical measure to capturing the true value of a basketball player.
The algorithm yields what they call a Win Score, because it expresses a player’s worth as the number of wins that his contributions bring to his team. According to their analysis,..."
"... If a rookie increases his scoring by ten per cent—regardless of how efficiently he scores those points—the number of votes he’ll get will increase by twenty-three per cent. If he increases his rebounds by ten per cent, the number of votes he’ll get will increase by six per cent.
Every other factor, like turnovers, steals, assists, blocked shots, and personal fouls—factors that can have a significant influence on the outcome of a game—seemed to bear no statistical relationship to judgments of merit at all. It’s not even the case that high scorers help their team by drawing more fans. As the authors point out, that’s only true on the road. ..."
"... We become dance critics, blind to Iverson’s dismal shooting percentage and his excessive turnovers, blind to the reality that the Philadelphia 76ers would be better off without him.
“One can play basketball,” the authors conclude. “One can watch basketball. One can both play and watch basketball for a thousand years. If you do not systematically track what the players do, and then uncover the statistical relationship between these actions and wins, you will never know why teams win and why they lose.” ..."
Read more in The New Yorker
To read Today's 'Press Clippings' in Spanish, click this week above on the 'Español' tab or afterwards click here: ' Propuesta de un instrumento para valorar el desempeño defensivo de los jugadores de baloncesto ' por César Juan Puente Garzón
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tags: basketball ~ statistician's digest ~ basketball analysis ~ Malcolm Gladwell
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