What makes one person a champion and the other one not?
Schwarzenegger:
"It's drive. It's the will. There are certain people that grow up with a tremendous hunger and it's usually kids that have struggled when they were young. When you grow up comfortable and in peace and happiness, all those things will produce a very balanced person and a good person, but it will not create the will and determination and hunger that you need to be the best in the world."
4.03.2010
Garnett
A note in Bruce Jenkins' San Francisco Chronicle column today tells me all I need to know about Kevin Garnett's character:
All season, Garnett has insisted that Paul Pierce be the last Celtic to take the floor during pregame introductions. And when he's asked to participate in a postgame news conference, Garnett invariably brings a teammate with him.
All season, Garnett has insisted that Paul Pierce be the last Celtic to take the floor during pregame introductions. And when he's asked to participate in a postgame news conference, Garnett invariably brings a teammate with him.
3.21.2010
Game Theory by Malcolm Gladwell
The first player picked in the 1996 National Basketball Association draft was a slender, six-foot guard from Georgetown University named Allen Iverson. Iverson was thrilling. He was lightning quick, and could stop and start on a dime. He would charge toward the basket, twist and turn and writhe through the arms and legs of much taller and heavier men, and somehow find a way to score. In his first season with the Philadelphia 76ers, Iverson was voted the N.B.A.’s Rookie of the Year. In every year since 2000, he has been named to the N.B.A.’s All-Star team. In the 2000-01 season, he finished first in the league in scoring and steals, led his team to the second-best record in the league, and was named, by the country’s sportswriters and broadcasters, basketball’s Most Valuable Player. He is currently in the midst of a four-year, seventy-seven-million-dollar contract. Almost everyone who knows basketball and who watches Iverson play thinks that he’s one of the best players in the game.
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. Suppose that we wanted to measure something in the real world, like the relative skill of New York City’s heart surgeons. One obvious way would be to compare the mortality rates of the patients on whom they operate—except that substandard care isn’t necessarily fatal, so a more accurate measure might be how quickly patients get better or how few complications they have after surgery. But recovery time is a function as well of how a patient is treated in the intensive-care unit, which reflects the capabilities not just of the doctor but of the nurses in the I.C.U. So now we have to adjust for nurse quality in our assessment of surgeon quality. We’d also better adjust for how sick the patients were in the first place, and since well-regarded surgeons often treat the most difficult cases, the best surgeons might well have the poorest patient recovery rates. In order to measure something you thought was fairly straightforward, you really have to take into account a series of things that aren’t so straightforward.
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. Or he might be the equivalent of an average surgeon with a first-rate I.C.U.: maybe his success reflects the fact that everyone else on his team excels at getting rebounds and forcing the other team to turn over the ball. Nor does the number of points that Iverson scores tell us anything about his tendency to do other things that contribute to winning and losing games; it doesn’t tell us how often he makes a mistake and loses the ball to the other team, or commits a foul, or blocks a shot, or rebounds the ball. Figuring whether one basketball player is better than another is a challenge similar to figuring out whether one heart surgeon is better than another: you have to find a way to interpret someone’s individual statistics in the context of the team that they’re on and the task that they are performing.
In “The Wages of Wins” , the economists David J. Berri 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, Iverson’s finest season was in 2004-05, when he was worth ten wins, which made him the thirty-sixth-best player in the league. In the season in which he won the Most Valuable Player award, he was the ninety-first-best player in the league. In his worst season (2003-04), he was the two-hundred-and-twenty-seventh-best player in the league. On average, for his career, he has ranked a hundred and sixteenth. In some years, Iverson has not even been the best player on his own team. Looking at the findings that Berri, present is enough to make one wonder what exactly basketball experts—coaches, managers, sportswriters—know about basketball.
Basketball experts clearly appreciate basketball. They understand the gestalt of the game, in the way that someone who has spent a lifetime thinking about and watching, say, modern dance develops an understanding of that art form. They’re able to teach and coach and motivate; to make judgments and predictions about a player’s character and resolve and stage of development. But the argument of “The Wages of Wins” is that this kind of expertise has real limitations when it comes to making precise evaluations of individual performance, whether you’re interested in the consistency of football quarterbacks or in testing claims that N.B.A. stars “turn it on” during playoffs. The baseball legend Ty Cobb, the authors point out, had a lifetime batting average of .366, almost thirty points higher than the former San Diego Padres outfielder Tony Gwynn, who had a lifetime batting average of .338:
So Cobb hit safely 37 percent of the time while Gwynn hit safely on 34 percent of his at bats. If all you did was watch these players, could you say who was a better hitter? Can one really tell the difference between 37 percent and 34 percent just staring at the players play? To see the problem with the non-numbers approach to player evaluation, consider that out of every 100 at bats, Cobb got three more hits than Gwynn. That’s it, three hits.
Michael Lewis made a similar argument in his 2003 best-seller, “Moneyball,” about how the so-called sabermetricians have changed the evaluation of talent in baseball. Baseball is sufficiently transparent, though, that the size of the discrepancies between intuitive and statistically aided judgment tends to be relatively modest. If you mistakenly thought that Gwynn was better than Cobb, you were still backing a terrific hitter. But “The Wages of Wins” suggests that when you move into more complex situations, like basketball, the limitations of “seeing” become enormous. Jermaine O’Neal, a center for the Indiana Pacers, finished third in the Most Valuable Player voting in 2004. His Win Score that year put him forty-fourth in the league. In 2004-05, the forward Antoine Walker made as much money as the point guard Jason Kidd, even though Walker produced 0.6 wins for Atlanta and Boston and Kidd produced nearly twenty wins for New Jersey.
Most egregious is the story of a young guard for the Chicago Bulls named Ben Gordon. Last season, Gordon finished second in the Rookie of the Year voting and was named the league’s top “sixth man”—that is, the best non-starter—because he averaged an impressive 15.1 points per game in limited playing time. But Gordon rebounds less than he should, turns over the ball frequently, and makes such a low percentage of his shots that, of the N.B.A.’s top thirty-three scorers—that is, players who score at least one point for every two minutes on the floor—Gordon’s Win Score ranked him dead last.
The problem for basketball experts is that, in a situation with many variables, it’s difficult to know how much weight to assign to each variable. Buying a house is agonizing because we look at the size, the location, the back yard, the proximity to local schools, the price, and so on, and we’re unsure which of those things matters most. Assessing heart-attack risk is a notoriously difficult task for similar reasons. A doctor can analyze a dozen different factors. But how much weight should be given to a patient’s cholesterol level relative to his blood pressure? In the face of such complexity, people construct their own arbitrary algorithms—they assume that every factor is of equal importance, or randomly elevate one or two factors for the sake of simplifying matters—and we make mistakes because those arbitrary algorithms are, well, arbitrary.
Berri argues that the arbitrary algorithms of basketball experts elevate the number of points a player scores above all other considerations. In one clever piece of research, they analyze the relationship between the statistics of rookies and the number of votes they receive in the All-Rookie Team balloting. 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. At home, attendance is primarily a function of games won. Basketball’s decision-makers, it seems, are simply irrational.
It’s hard not to wonder, after reading “The Wages of Wins,” about the other instances in which we defer to the evaluations of experts. Boards of directors vote to pay C.E.O.s tens of millions of dollars, ostensibly because they believe—on the basis of what they have learned over the years by watching other C.E.O.s—that they are worth it. But so what? We see Allen Iverson, over and over again, charge toward the basket, twisting and turning and writhing through a thicket of arms and legs of much taller and heavier men—and all we learn is to appreciate twisting and turning and writhing. 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.”
A couple of extra points about my piece in this week’s New Yorker on “Wages of Wins.”
I’ve noticed, in reading reactions to the book around the blogosphere, a certain residual skepticism, particularly among hard-core basketball fans. Someone wrote in to point out, for instance, that Shawn Marion’s Win Score this past season was higher than Steve Nash’s, when common sense would suggest that the team would suffer far more from the loss of Nash than Marion. I think that's right. Nash is more ultimately more valuable to the Suns than anyone else.
Basketball is tricky. No statistical formula can adequately measure the series of intangible factors that are so critical to a team’s success: a player’s impact on his teammates, for example, or attitude, or willingness to play hurt, or grace under pressure or—most important of all—how well a player plays defense. Nash’s particular, largely unquantifiable; genius is that he manages to make everyone around him much better. As Bill Simmons (world’s greatest sportswriter) points out in his column today, Tim Thomas was traded to the Suns this season after nine years of disappointment, and all of a sudden he played like a star. Is that a conincidence? I don't think so.
Similarly, the Wages of Wins algorithm tells us that over the course of his career Ray Allen has been “worth” nearly as much to the teams he has played for as Kobe Bryant. Does that mean Allen is as good as Bryant? Of course not. Bryant is one of the greatest on-the-ball defenders of his generation and Allen is, well (let’s be nice here) not. Perhaps the best part of Kobe's game doesn't—and probably can't—show up in any kind of statistical analysis.
But the Wages of Wins guys aren’t arguing that their formulas are the only and best way to rate players. They are making a more sophisticated—and limited—claim: for those aspects of basketball performance that are quantifiable (steals, turnovers, rebounds, shots made and missed, free throws etc) are the existing statistical measures we use to rate players any good? And if not, is there a better way to quantify the quantifiable?
To the first question, “Wages of Wins” argues—convincingly—no. For instance, they show that the correlation between a team’s payroll and a team’s performance, in the NBA, is surprisingly weak. What that tells us is that the people charged with evaluating and rewarding ability and performance in the NBA do a lousy job. In particular, they argue, traditional talent evaluation over-rates the importance of points scored, and under-rates the importance of turnovers, rebounds and scoring percentage. Wages of Wins also obliterates the so-called NBA Efficiency rating, which is the official algorithm used by the league and many basketball experts to rank the statistical performance of players. The Efficiency rating, they argue, makes the same error. It dramatically over-rewards players who take lots and lots of shots.
Okay: part two. Is the Wages of Wins algorithm an improvement over the things like the NBA Efficiency system? To make the case for their system, the authors “fit” their algorithm to the real world. For the 2003-04 season, they add up the number of wins predicted by their algorithm for every player on every team, and compare that number to the team’s actual win total. Their average error? 1.67 wins. In other words, if you give them the statistics for every player on a given team, they can tell you how many wins that team got that season, with a margin of error under two wins. That’s pretty good. I think the real value of the Wages of Wins system is that it gives us a tool to see those instances where our intuitive ratings of players may be particularly inaccurate.
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. Suppose that we wanted to measure something in the real world, like the relative skill of New York City’s heart surgeons. One obvious way would be to compare the mortality rates of the patients on whom they operate—except that substandard care isn’t necessarily fatal, so a more accurate measure might be how quickly patients get better or how few complications they have after surgery. But recovery time is a function as well of how a patient is treated in the intensive-care unit, which reflects the capabilities not just of the doctor but of the nurses in the I.C.U. So now we have to adjust for nurse quality in our assessment of surgeon quality. We’d also better adjust for how sick the patients were in the first place, and since well-regarded surgeons often treat the most difficult cases, the best surgeons might well have the poorest patient recovery rates. In order to measure something you thought was fairly straightforward, you really have to take into account a series of things that aren’t so straightforward.
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. Or he might be the equivalent of an average surgeon with a first-rate I.C.U.: maybe his success reflects the fact that everyone else on his team excels at getting rebounds and forcing the other team to turn over the ball. Nor does the number of points that Iverson scores tell us anything about his tendency to do other things that contribute to winning and losing games; it doesn’t tell us how often he makes a mistake and loses the ball to the other team, or commits a foul, or blocks a shot, or rebounds the ball. Figuring whether one basketball player is better than another is a challenge similar to figuring out whether one heart surgeon is better than another: you have to find a way to interpret someone’s individual statistics in the context of the team that they’re on and the task that they are performing.
In “The Wages of Wins” , the economists David J. Berri 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, Iverson’s finest season was in 2004-05, when he was worth ten wins, which made him the thirty-sixth-best player in the league. In the season in which he won the Most Valuable Player award, he was the ninety-first-best player in the league. In his worst season (2003-04), he was the two-hundred-and-twenty-seventh-best player in the league. On average, for his career, he has ranked a hundred and sixteenth. In some years, Iverson has not even been the best player on his own team. Looking at the findings that Berri, present is enough to make one wonder what exactly basketball experts—coaches, managers, sportswriters—know about basketball.
Basketball experts clearly appreciate basketball. They understand the gestalt of the game, in the way that someone who has spent a lifetime thinking about and watching, say, modern dance develops an understanding of that art form. They’re able to teach and coach and motivate; to make judgments and predictions about a player’s character and resolve and stage of development. But the argument of “The Wages of Wins” is that this kind of expertise has real limitations when it comes to making precise evaluations of individual performance, whether you’re interested in the consistency of football quarterbacks or in testing claims that N.B.A. stars “turn it on” during playoffs. The baseball legend Ty Cobb, the authors point out, had a lifetime batting average of .366, almost thirty points higher than the former San Diego Padres outfielder Tony Gwynn, who had a lifetime batting average of .338:
So Cobb hit safely 37 percent of the time while Gwynn hit safely on 34 percent of his at bats. If all you did was watch these players, could you say who was a better hitter? Can one really tell the difference between 37 percent and 34 percent just staring at the players play? To see the problem with the non-numbers approach to player evaluation, consider that out of every 100 at bats, Cobb got three more hits than Gwynn. That’s it, three hits.
Michael Lewis made a similar argument in his 2003 best-seller, “Moneyball,” about how the so-called sabermetricians have changed the evaluation of talent in baseball. Baseball is sufficiently transparent, though, that the size of the discrepancies between intuitive and statistically aided judgment tends to be relatively modest. If you mistakenly thought that Gwynn was better than Cobb, you were still backing a terrific hitter. But “The Wages of Wins” suggests that when you move into more complex situations, like basketball, the limitations of “seeing” become enormous. Jermaine O’Neal, a center for the Indiana Pacers, finished third in the Most Valuable Player voting in 2004. His Win Score that year put him forty-fourth in the league. In 2004-05, the forward Antoine Walker made as much money as the point guard Jason Kidd, even though Walker produced 0.6 wins for Atlanta and Boston and Kidd produced nearly twenty wins for New Jersey.
Most egregious is the story of a young guard for the Chicago Bulls named Ben Gordon. Last season, Gordon finished second in the Rookie of the Year voting and was named the league’s top “sixth man”—that is, the best non-starter—because he averaged an impressive 15.1 points per game in limited playing time. But Gordon rebounds less than he should, turns over the ball frequently, and makes such a low percentage of his shots that, of the N.B.A.’s top thirty-three scorers—that is, players who score at least one point for every two minutes on the floor—Gordon’s Win Score ranked him dead last.
The problem for basketball experts is that, in a situation with many variables, it’s difficult to know how much weight to assign to each variable. Buying a house is agonizing because we look at the size, the location, the back yard, the proximity to local schools, the price, and so on, and we’re unsure which of those things matters most. Assessing heart-attack risk is a notoriously difficult task for similar reasons. A doctor can analyze a dozen different factors. But how much weight should be given to a patient’s cholesterol level relative to his blood pressure? In the face of such complexity, people construct their own arbitrary algorithms—they assume that every factor is of equal importance, or randomly elevate one or two factors for the sake of simplifying matters—and we make mistakes because those arbitrary algorithms are, well, arbitrary.
Berri argues that the arbitrary algorithms of basketball experts elevate the number of points a player scores above all other considerations. In one clever piece of research, they analyze the relationship between the statistics of rookies and the number of votes they receive in the All-Rookie Team balloting. 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. At home, attendance is primarily a function of games won. Basketball’s decision-makers, it seems, are simply irrational.
It’s hard not to wonder, after reading “The Wages of Wins,” about the other instances in which we defer to the evaluations of experts. Boards of directors vote to pay C.E.O.s tens of millions of dollars, ostensibly because they believe—on the basis of what they have learned over the years by watching other C.E.O.s—that they are worth it. But so what? We see Allen Iverson, over and over again, charge toward the basket, twisting and turning and writhing through a thicket of arms and legs of much taller and heavier men—and all we learn is to appreciate twisting and turning and writhing. 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.”
A couple of extra points about my piece in this week’s New Yorker on “Wages of Wins.”
I’ve noticed, in reading reactions to the book around the blogosphere, a certain residual skepticism, particularly among hard-core basketball fans. Someone wrote in to point out, for instance, that Shawn Marion’s Win Score this past season was higher than Steve Nash’s, when common sense would suggest that the team would suffer far more from the loss of Nash than Marion. I think that's right. Nash is more ultimately more valuable to the Suns than anyone else.
Basketball is tricky. No statistical formula can adequately measure the series of intangible factors that are so critical to a team’s success: a player’s impact on his teammates, for example, or attitude, or willingness to play hurt, or grace under pressure or—most important of all—how well a player plays defense. Nash’s particular, largely unquantifiable; genius is that he manages to make everyone around him much better. As Bill Simmons (world’s greatest sportswriter) points out in his column today, Tim Thomas was traded to the Suns this season after nine years of disappointment, and all of a sudden he played like a star. Is that a conincidence? I don't think so.
Similarly, the Wages of Wins algorithm tells us that over the course of his career Ray Allen has been “worth” nearly as much to the teams he has played for as Kobe Bryant. Does that mean Allen is as good as Bryant? Of course not. Bryant is one of the greatest on-the-ball defenders of his generation and Allen is, well (let’s be nice here) not. Perhaps the best part of Kobe's game doesn't—and probably can't—show up in any kind of statistical analysis.
But the Wages of Wins guys aren’t arguing that their formulas are the only and best way to rate players. They are making a more sophisticated—and limited—claim: for those aspects of basketball performance that are quantifiable (steals, turnovers, rebounds, shots made and missed, free throws etc) are the existing statistical measures we use to rate players any good? And if not, is there a better way to quantify the quantifiable?
To the first question, “Wages of Wins” argues—convincingly—no. For instance, they show that the correlation between a team’s payroll and a team’s performance, in the NBA, is surprisingly weak. What that tells us is that the people charged with evaluating and rewarding ability and performance in the NBA do a lousy job. In particular, they argue, traditional talent evaluation over-rates the importance of points scored, and under-rates the importance of turnovers, rebounds and scoring percentage. Wages of Wins also obliterates the so-called NBA Efficiency rating, which is the official algorithm used by the league and many basketball experts to rank the statistical performance of players. The Efficiency rating, they argue, makes the same error. It dramatically over-rewards players who take lots and lots of shots.
Okay: part two. Is the Wages of Wins algorithm an improvement over the things like the NBA Efficiency system? To make the case for their system, the authors “fit” their algorithm to the real world. For the 2003-04 season, they add up the number of wins predicted by their algorithm for every player on every team, and compare that number to the team’s actual win total. Their average error? 1.67 wins. In other words, if you give them the statistics for every player on a given team, they can tell you how many wins that team got that season, with a margin of error under two wins. That’s pretty good. I think the real value of the Wages of Wins system is that it gives us a tool to see those instances where our intuitive ratings of players may be particularly inaccurate.
3.02.2010
Interview with Author of Blink: Malcolm Gladwell
Malcolm Gladwell is a staff writer for the New Yorker
"Blink," his latest book, is subtitled, "The Power of Thinking Without Thinking," which is at No. 2 on the New York Times bestseller list.
Gladwell is a master at linking sociological and psychological studies with the everyday and mundane, and has an uncanny ability to make connections between new ideas and old, seemingly insolvable problems.
JM: Early on in "Blink," you ask, "When should we trust our instincts, and when should we be wary of them?" That's a great question, and seems at the heart of what happens on the football field. You've got intense, detailed preparation leading up to the game, and lots of fast analysis between plays (by the coaches and players), and then the "instinctive" moves that happen once the ball is snapped. Let's say the Eagles call you up and ask you to spend a day with the team explaining the lessons of "Blink," and how they could be used in the Super Bowl. Would you take them up on the offer? If so, what would you say? Who would you spend the most time with? What would you want to talk about first?
Malcolm Gladwell: I'd tell Andy Reid the story from "Blink" about Millennium Challenge, which was the $500 million war game the Pentagon conducted in 2001. It was an elaborate dress rehearsal for the Iraq War, with one side "playing" the U.S. and another team playing Iraq -- and Iraq won. The chapter is all about how that happened, and it focuses on a retired Marine Corps General named Paul Van Riper, who was playing Saddam Hussein
Van Riper won by speeding up the game. The team playing the U.S. had all kinds of computer programs and decision-making systems, and experts on every conceivable problem. But when the war started, Van Riper hit them with so many unexpected plays so quickly that he forced them out of that kind of conscious, deliberate decision-making mode -- and forced them to rely on their instincts. And they weren't prepared for that. Van Riper, in a sense, went to the "no-huddle" against his much more formidable opponent. And his experience shows that being good at deliberate, conscious decision-making doesn't make you good at instinctive decisions.
That's why I've always been so surprised that more NFL teams don't use the no-huddle. It's not just that it forces your opponent to keep a specific defense on the field. It's that it shifts the game cognitively: it forces coaches and defensive captains to think and react entirely in the instinctive "blink" mode -- and when teams aren't prepared for that kind of fast-paced thinking crazy things happen, like Iraq beating the U.S. Andy Reid has to know that Belichick has an edge when he can calmly and deliberately plot his next move. But does he still have an advantage when he and his players have to make decisions on the spur of the moment? I'd tell Andy Reid to go no-huddle at random, unpredictable points during the game -- to throw Belichick out of his comfort zone.
JM: Well, you've told the story, you've given no-huddle advice, and you've still got 45 minutes on the clock. In walks Donovan McNabb. In walks defensive coordinator Jim Johnson. Reid says if you don't give them some good advice, he's going to put on tights right then and there. So you're going to talk. What do you tell those two?
MG: Oh God. That's putting me in a spot. I guess I would only say that I hope McNabb has stopped watching film at this point. I'm not sure anything he learns consciously at this point about the Pats is going to make much difference on Sunday.
JM: You write about how, in auditions for symphony orchestras, both conscious and unconscious biases are strongly at work, and that the simple placement of a screen -- not being able to see whether the person auditioning was a man or a woman -- made a world of difference. Women, in particular, found themselves getting lots of jobs they otherwise would not have been offered. This reminded me of "Moneyball" arguments. On one side, you've got lots of people who believe that you can tell a whole lot about a player by not looking at him, by looking at selected stats. And on another, you've got the scouts, who believe, in short, that seeing is believing. Both seem to me to be examples of "thin slicing." The numbers guys can look at a stat line and say, "Worth it." The scouts can see a player in action and say, "He's got it." These sides seem to be opposed, but they could also be complementary. How can "Blink" help us understand this, and maybe reconcile the two views?
MG: You are right to bring up "Moneyball," because reading Michael Lewis' book was a real inspiration for me. I think about it this way. What people in the classical music world discovered was that when they couldn't see the person auditioning, they made very different and much better hiring decisions than when they could see the auditioner. With a screen up, for instance, they began to hire women for the first time, which suggests that before that their judgment had been impaired by all kinds of biases they were unaware of. What they saw with their eyes had interfered with what they heard with their ears. Billy Beane makes the same argument about scouting prospects: that sometimes what you see -- whether a player is short or tall, thin or heavy -- corrupts your assessment of what really matters, which is whether a guy can hit. So Beane does, essentially, a version of what orchestras do: he put a screen. He doesn't let what he sees with his eyes corrupt his statistical appreciation of a player's ability.
But this doesn't mean that all instinctive judgments about players are useless, because the question of whether a guy can hit is only one of a number of questions that a scout has to answer. GMs also want to know: is the guy lazy or a hard worker? Is he coachable? Does he have good habits? Will he be a good clubhouse presence? How strong is his competitive desire? What separates Roger Clemens or Barry Bonds from any of the other top players drafted alongside them is not talent, at the end of the day. It's desire and competitiveness -- and to predict that you very much need a seasoned scout who can look at a player and have an instinctive sense of what he'll be like years down the road. I always thought that the critics of "Moneyball" misinterpreted what Lewis was saying. He wasn't saying that all instinctive scouting judgments are flawed. He was saying that there are some questions -- like predicting hitting ability -- that are better answered statistically, and that the task of a successful GM is to understand the difference between what can and can't be answered that way. That's my argument in Blink as well.
JM: The "Warren Harding error," which you devote a chapter to, seems to apply often in sports.
MG: The Warren Harding Error is in honor of our best-looking president ever -- a man so handsome and distinguished and with such a barrel chest and broad shoulders and commanding voice that people would just look at him and be convinced that that he would make a wonderful leader. Unfortunately, Harding turned out to be our stupidest and most incompetent president ever. (And there is some stiff competition for that title). The Warren Harding Error is what happens when our first impressions are so powerful that they cloud our better judgment.
I always think about this when I hear basketball people talking about how high a player can jump. People fall in love with leaping ability, because when you see someone soar so far above the rim its an almost emotional experience. It's like looking at Warren Harding. But, of course, what does leaping ability really tell you about a player? Not much. Most rebounds are taken below the rim, and the key to getting your shot off is really how quick your release is and how you shoot, not how high you jump.
JM: What do you think are the most egregious examples of this, in recent memory?
MG: Who suffers the most from the Warren Harding Error? Well, I'm an embittered New Yorker so I'd say Isiah Thomas. He's brought together a group of marvelous athletes -- Crawford, Thomas, Marbury -- all of whom look the part of basketball players, without being able to actually play the game with any great skill or discipline.
JM: Talk a little about tennis coach Vic Braden, the subject of one of your anecdotes. He says, "We haven't found a single (tennis) player who is consistent in knowing and explaining exactly what he does."
MG: Braden's experience is really interesting. He would ask, say, a world-class tennis player to describe precisely how they would hit a topspin forehand, and they would invariably say that they rolled their wrist at the moment of impact with the ball. And then he'd do a digital analysis of videotape of them actually hitting a topspin forehand and find out that at the moment of impact with the ball their wrist was rock solid. They didn't roll it at all. The expertise of a world-class tennis player, in other words, is instinctive, which means that the knowledge behind their actions is buried in the corners of their brain. They hit a ball unconsciously.
JM: Is that why, quite often, great players don't make such great coaches?
MG: Yes, that's precisely why top athletes so often make bad coaches or general managers. They often don't really know why they were as good as they were. They can't describe it, which means that they can't teach it and they quickly become frustrated at their inability to lift others up to their own level. Mediocre players -- or non-athletes -- tend to make better coaches because their knowledge isn't unconscious. It's the same thing with writing. I know very little about science. But I think I write about science more clearly than many scientists, because I have to go over every step, carefully and deliberately.
JM: Nobody in pro football is known more for studying tape than Peyton Manning. If you were to sit down with Peyton while he's studying film, what would you be most interested in? What would you want to know?
MG: Manning reminds me of Tom Hoving, who I write about in "Blink"; he has spent a lifetime studying and handling and thinking about ancient Greek art. One day, the curator of the Getty Museum in Los Angeles showed him a statute they had just bought for $10 million, and Hoving took one look at it and blurted out: "It's fake." In that first split second, the statue struck him as wrong. And sure enough, Hoving was right. It was a fake. When we spend a lifetime studying something that closely, what we are doing is educating our unconscious. We're developing and training our instincts, so that we can glance at a unusual situation and instantly know what it means. That's what Manning is doing by studying so much film. He's educating his on-field instincts.
What I'd love to do is to put eye-tracking goggles on him. Cognitive psychologists use these a lot: they are special glasses that track exactly what your eyes are focusing on at any given moment -- to an incredible level of detail. When you read the word "moment" in my previous sentence, for instance, did you start at the 't' and work backwards, or zero in on the middle "m" or just look at the first 'm' and then skip to the last 't'? The answer would tell me how you "read" a sentence.
JM: When you used the term "momentary autism," in "Blink," I immediately thought of Brett Favre's pass during the first-round playoff game, when he tossed the ball when he was about four yards past the line of scrimmage. He ran off the field and it appeared he was smiling or laughing, as if he couldn't believe what he'd just done. Was that a moment of momentary autism, do you think?
MG: That's an interesting question. I use "momentary autism" to describe those moments when otherwise normal people become autistic -- that is, like people suffering from that disorder, they lose the ability to mind-read, to make sense of the intentions of others. An autistic person can follow the literal meaning of words, for instance, but cannot interpret gestures. They can understand flirting, in other words, only if one party says to another "I'm flirting with you."
I think all of us become momentarily autistic when we're under extreme physiological stress. For instance, when our heart rate gets above 145, our ability to make sophisticated judgments and to engage in this kind of mind-reading begins to erode very rapidly. I'm guessing Joe Montana's heart rate barely got above 100 in any of his fourth-quarter comebacks. Whenever I see Favre do something inexplicably stupid late in the game -- and I feel like he does that a surprising amount -- I'd love to know what his heart rate is at that moment. Is he just a little too excitable for his own good?
JM: Perhaps momentary autism was the wrong phrase to use in Favre's case, but it does seem like something shut down in his mind when that happened. What can Brett -- or other QBs who need to think on their feet and not panic -- do to keep such things from happening? If Ben Roethlisberger had done that, we'd be calling it a "rookie mistake."
MG: I talked for a long time when I was doing "Blink" with a fascinating guy named Gavin deBecker, who runs one of the top personal security agencies in Los Angeles.
Basically, if you're a movie star or a billionaire or the Sultan of Brunei, he provides you with your bodyguard. DeBecker talked a lot about how rigorously he trains his people. If the quality of our coordination and instinctive reactions breaks down when our heart rate gets above 145, he wants to expose his people to stressful situations over and over and over again until they can face them at 130, 110 or 90.
So he fires bullets at people, and does these utterly terrifying exercises involving angry pit bulls. The first and second and third and fourth time you run through one of deBecker's training sessions you basically lose control of your bowels and take off like a scalded cat. By the fifth time, essential bodily functions start to return. By the 10th time, you can function as a normal human being.
This, by the way, is why police officers will tell you that you must practice dialing 911 at least once a week. Because if you don't, when a burglar is actually in the next room, believe it or not you won't be able to dial 911: you'll forget the number, or you'll have lost so many motor skills under the stress of the moment that your fingers won't be able to pick out the buttons on the phone.
So I'd run quarterbacks who don't do well under pressure through deBecker's gauntlet -- or any other kind of similar exercise so they have a sense of what REAL life-threatening stress feels like. I'd run them through a live-fire exercise at Quantico. I'd have them spend the offseason working with a trauma team in south-central L.A. It is only through repeated exposures to genuine stress that our body learns how to function effectively under that kind of pressure. I think its time we realized that a quarterback needs the same kind of exhaustive preparation for combat that we give bodyguards and soldiers.
JM: You provide some compelling examples of how too much data can undermine decision-making. Can you talk a little about how this might apply to sports? Is there a point, during Super Bowl prep, for example, when the info spigot should be turned off?
MG: Oh, absolutely. I think that the worst thing about the Super Bowl is the two-week layoff. I think teams get over-coached in the second week. In "Blink," I talk about how we can turn ER doctors from terrible decision-makers when it comes to diagnosing chest pain into great decision makers simply by limiting the amount of information they are given about a patient. Load them down with every conceivable piece of data, and they have real difficulty distinguishing patients with heartburn from patients who are experiencing a real heart attack. Limit them to three or four crucial pieces of data, though, and they do a great job. How can that not be true of football players as well? It's quite possible right now that Tom Brady or Donovan McNabb simply know too much about each other.
JM: One of my pet peeves, especially in basketball, is the frequency of timeouts that are called near the end of games. My thought is, "Let 'em play!" It seems that two bad things could be going on when this happens: 1) a loss of spontaneity on the part of the players, and 2) a message sent from coach to players that says, unconsciously, of course, that he doesn't trust that they know what to do. Your thoughts?
MG: I agree, which is why I argued above for the no-huddle. We know the Pats are a beautifully coached team when Belichick has time to think. But are they still the best team in the NFL when Belichick has no time to think, and the players have to rely on their instincts?
"Blink," his latest book, is subtitled, "The Power of Thinking Without Thinking," which is at No. 2 on the New York Times bestseller list.
Gladwell is a master at linking sociological and psychological studies with the everyday and mundane, and has an uncanny ability to make connections between new ideas and old, seemingly insolvable problems.
JM: Early on in "Blink," you ask, "When should we trust our instincts, and when should we be wary of them?" That's a great question, and seems at the heart of what happens on the football field. You've got intense, detailed preparation leading up to the game, and lots of fast analysis between plays (by the coaches and players), and then the "instinctive" moves that happen once the ball is snapped. Let's say the Eagles call you up and ask you to spend a day with the team explaining the lessons of "Blink," and how they could be used in the Super Bowl. Would you take them up on the offer? If so, what would you say? Who would you spend the most time with? What would you want to talk about first?
Malcolm Gladwell: I'd tell Andy Reid the story from "Blink" about Millennium Challenge, which was the $500 million war game the Pentagon conducted in 2001. It was an elaborate dress rehearsal for the Iraq War, with one side "playing" the U.S. and another team playing Iraq -- and Iraq won. The chapter is all about how that happened, and it focuses on a retired Marine Corps General named Paul Van Riper, who was playing Saddam Hussein
Van Riper won by speeding up the game. The team playing the U.S. had all kinds of computer programs and decision-making systems, and experts on every conceivable problem. But when the war started, Van Riper hit them with so many unexpected plays so quickly that he forced them out of that kind of conscious, deliberate decision-making mode -- and forced them to rely on their instincts. And they weren't prepared for that. Van Riper, in a sense, went to the "no-huddle" against his much more formidable opponent. And his experience shows that being good at deliberate, conscious decision-making doesn't make you good at instinctive decisions.
That's why I've always been so surprised that more NFL teams don't use the no-huddle. It's not just that it forces your opponent to keep a specific defense on the field. It's that it shifts the game cognitively: it forces coaches and defensive captains to think and react entirely in the instinctive "blink" mode -- and when teams aren't prepared for that kind of fast-paced thinking crazy things happen, like Iraq beating the U.S. Andy Reid has to know that Belichick has an edge when he can calmly and deliberately plot his next move. But does he still have an advantage when he and his players have to make decisions on the spur of the moment? I'd tell Andy Reid to go no-huddle at random, unpredictable points during the game -- to throw Belichick out of his comfort zone.
JM: Well, you've told the story, you've given no-huddle advice, and you've still got 45 minutes on the clock. In walks Donovan McNabb. In walks defensive coordinator Jim Johnson. Reid says if you don't give them some good advice, he's going to put on tights right then and there. So you're going to talk. What do you tell those two?
MG: Oh God. That's putting me in a spot. I guess I would only say that I hope McNabb has stopped watching film at this point. I'm not sure anything he learns consciously at this point about the Pats is going to make much difference on Sunday.
JM: You write about how, in auditions for symphony orchestras, both conscious and unconscious biases are strongly at work, and that the simple placement of a screen -- not being able to see whether the person auditioning was a man or a woman -- made a world of difference. Women, in particular, found themselves getting lots of jobs they otherwise would not have been offered. This reminded me of "Moneyball" arguments. On one side, you've got lots of people who believe that you can tell a whole lot about a player by not looking at him, by looking at selected stats. And on another, you've got the scouts, who believe, in short, that seeing is believing. Both seem to me to be examples of "thin slicing." The numbers guys can look at a stat line and say, "Worth it." The scouts can see a player in action and say, "He's got it." These sides seem to be opposed, but they could also be complementary. How can "Blink" help us understand this, and maybe reconcile the two views?
MG: You are right to bring up "Moneyball," because reading Michael Lewis' book was a real inspiration for me. I think about it this way. What people in the classical music world discovered was that when they couldn't see the person auditioning, they made very different and much better hiring decisions than when they could see the auditioner. With a screen up, for instance, they began to hire women for the first time, which suggests that before that their judgment had been impaired by all kinds of biases they were unaware of. What they saw with their eyes had interfered with what they heard with their ears. Billy Beane makes the same argument about scouting prospects: that sometimes what you see -- whether a player is short or tall, thin or heavy -- corrupts your assessment of what really matters, which is whether a guy can hit. So Beane does, essentially, a version of what orchestras do: he put a screen. He doesn't let what he sees with his eyes corrupt his statistical appreciation of a player's ability.
But this doesn't mean that all instinctive judgments about players are useless, because the question of whether a guy can hit is only one of a number of questions that a scout has to answer. GMs also want to know: is the guy lazy or a hard worker? Is he coachable? Does he have good habits? Will he be a good clubhouse presence? How strong is his competitive desire? What separates Roger Clemens or Barry Bonds from any of the other top players drafted alongside them is not talent, at the end of the day. It's desire and competitiveness -- and to predict that you very much need a seasoned scout who can look at a player and have an instinctive sense of what he'll be like years down the road. I always thought that the critics of "Moneyball" misinterpreted what Lewis was saying. He wasn't saying that all instinctive scouting judgments are flawed. He was saying that there are some questions -- like predicting hitting ability -- that are better answered statistically, and that the task of a successful GM is to understand the difference between what can and can't be answered that way. That's my argument in Blink as well.
JM: The "Warren Harding error," which you devote a chapter to, seems to apply often in sports.
MG: The Warren Harding Error is in honor of our best-looking president ever -- a man so handsome and distinguished and with such a barrel chest and broad shoulders and commanding voice that people would just look at him and be convinced that that he would make a wonderful leader. Unfortunately, Harding turned out to be our stupidest and most incompetent president ever. (And there is some stiff competition for that title). The Warren Harding Error is what happens when our first impressions are so powerful that they cloud our better judgment.
I always think about this when I hear basketball people talking about how high a player can jump. People fall in love with leaping ability, because when you see someone soar so far above the rim its an almost emotional experience. It's like looking at Warren Harding. But, of course, what does leaping ability really tell you about a player? Not much. Most rebounds are taken below the rim, and the key to getting your shot off is really how quick your release is and how you shoot, not how high you jump.
JM: What do you think are the most egregious examples of this, in recent memory?
MG: Who suffers the most from the Warren Harding Error? Well, I'm an embittered New Yorker so I'd say Isiah Thomas. He's brought together a group of marvelous athletes -- Crawford, Thomas, Marbury -- all of whom look the part of basketball players, without being able to actually play the game with any great skill or discipline.
JM: Talk a little about tennis coach Vic Braden, the subject of one of your anecdotes. He says, "We haven't found a single (tennis) player who is consistent in knowing and explaining exactly what he does."
MG: Braden's experience is really interesting. He would ask, say, a world-class tennis player to describe precisely how they would hit a topspin forehand, and they would invariably say that they rolled their wrist at the moment of impact with the ball. And then he'd do a digital analysis of videotape of them actually hitting a topspin forehand and find out that at the moment of impact with the ball their wrist was rock solid. They didn't roll it at all. The expertise of a world-class tennis player, in other words, is instinctive, which means that the knowledge behind their actions is buried in the corners of their brain. They hit a ball unconsciously.
JM: Is that why, quite often, great players don't make such great coaches?
MG: Yes, that's precisely why top athletes so often make bad coaches or general managers. They often don't really know why they were as good as they were. They can't describe it, which means that they can't teach it and they quickly become frustrated at their inability to lift others up to their own level. Mediocre players -- or non-athletes -- tend to make better coaches because their knowledge isn't unconscious. It's the same thing with writing. I know very little about science. But I think I write about science more clearly than many scientists, because I have to go over every step, carefully and deliberately.
JM: Nobody in pro football is known more for studying tape than Peyton Manning. If you were to sit down with Peyton while he's studying film, what would you be most interested in? What would you want to know?
MG: Manning reminds me of Tom Hoving, who I write about in "Blink"; he has spent a lifetime studying and handling and thinking about ancient Greek art. One day, the curator of the Getty Museum in Los Angeles showed him a statute they had just bought for $10 million, and Hoving took one look at it and blurted out: "It's fake." In that first split second, the statue struck him as wrong. And sure enough, Hoving was right. It was a fake. When we spend a lifetime studying something that closely, what we are doing is educating our unconscious. We're developing and training our instincts, so that we can glance at a unusual situation and instantly know what it means. That's what Manning is doing by studying so much film. He's educating his on-field instincts.
What I'd love to do is to put eye-tracking goggles on him. Cognitive psychologists use these a lot: they are special glasses that track exactly what your eyes are focusing on at any given moment -- to an incredible level of detail. When you read the word "moment" in my previous sentence, for instance, did you start at the 't' and work backwards, or zero in on the middle "m" or just look at the first 'm' and then skip to the last 't'? The answer would tell me how you "read" a sentence.
JM: When you used the term "momentary autism," in "Blink," I immediately thought of Brett Favre's pass during the first-round playoff game, when he tossed the ball when he was about four yards past the line of scrimmage. He ran off the field and it appeared he was smiling or laughing, as if he couldn't believe what he'd just done. Was that a moment of momentary autism, do you think?
MG: That's an interesting question. I use "momentary autism" to describe those moments when otherwise normal people become autistic -- that is, like people suffering from that disorder, they lose the ability to mind-read, to make sense of the intentions of others. An autistic person can follow the literal meaning of words, for instance, but cannot interpret gestures. They can understand flirting, in other words, only if one party says to another "I'm flirting with you."
I think all of us become momentarily autistic when we're under extreme physiological stress. For instance, when our heart rate gets above 145, our ability to make sophisticated judgments and to engage in this kind of mind-reading begins to erode very rapidly. I'm guessing Joe Montana's heart rate barely got above 100 in any of his fourth-quarter comebacks. Whenever I see Favre do something inexplicably stupid late in the game -- and I feel like he does that a surprising amount -- I'd love to know what his heart rate is at that moment. Is he just a little too excitable for his own good?
JM: Perhaps momentary autism was the wrong phrase to use in Favre's case, but it does seem like something shut down in his mind when that happened. What can Brett -- or other QBs who need to think on their feet and not panic -- do to keep such things from happening? If Ben Roethlisberger had done that, we'd be calling it a "rookie mistake."
MG: I talked for a long time when I was doing "Blink" with a fascinating guy named Gavin deBecker, who runs one of the top personal security agencies in Los Angeles.
Basically, if you're a movie star or a billionaire or the Sultan of Brunei, he provides you with your bodyguard. DeBecker talked a lot about how rigorously he trains his people. If the quality of our coordination and instinctive reactions breaks down when our heart rate gets above 145, he wants to expose his people to stressful situations over and over and over again until they can face them at 130, 110 or 90.
So he fires bullets at people, and does these utterly terrifying exercises involving angry pit bulls. The first and second and third and fourth time you run through one of deBecker's training sessions you basically lose control of your bowels and take off like a scalded cat. By the fifth time, essential bodily functions start to return. By the 10th time, you can function as a normal human being.
This, by the way, is why police officers will tell you that you must practice dialing 911 at least once a week. Because if you don't, when a burglar is actually in the next room, believe it or not you won't be able to dial 911: you'll forget the number, or you'll have lost so many motor skills under the stress of the moment that your fingers won't be able to pick out the buttons on the phone.
So I'd run quarterbacks who don't do well under pressure through deBecker's gauntlet -- or any other kind of similar exercise so they have a sense of what REAL life-threatening stress feels like. I'd run them through a live-fire exercise at Quantico. I'd have them spend the offseason working with a trauma team in south-central L.A. It is only through repeated exposures to genuine stress that our body learns how to function effectively under that kind of pressure. I think its time we realized that a quarterback needs the same kind of exhaustive preparation for combat that we give bodyguards and soldiers.
JM: You provide some compelling examples of how too much data can undermine decision-making. Can you talk a little about how this might apply to sports? Is there a point, during Super Bowl prep, for example, when the info spigot should be turned off?
MG: Oh, absolutely. I think that the worst thing about the Super Bowl is the two-week layoff. I think teams get over-coached in the second week. In "Blink," I talk about how we can turn ER doctors from terrible decision-makers when it comes to diagnosing chest pain into great decision makers simply by limiting the amount of information they are given about a patient. Load them down with every conceivable piece of data, and they have real difficulty distinguishing patients with heartburn from patients who are experiencing a real heart attack. Limit them to three or four crucial pieces of data, though, and they do a great job. How can that not be true of football players as well? It's quite possible right now that Tom Brady or Donovan McNabb simply know too much about each other.
JM: One of my pet peeves, especially in basketball, is the frequency of timeouts that are called near the end of games. My thought is, "Let 'em play!" It seems that two bad things could be going on when this happens: 1) a loss of spontaneity on the part of the players, and 2) a message sent from coach to players that says, unconsciously, of course, that he doesn't trust that they know what to do. Your thoughts?
MG: I agree, which is why I argued above for the no-huddle. We know the Pats are a beautifully coached team when Belichick has time to think. But are they still the best team in the NFL when Belichick has no time to think, and the players have to rely on their instincts?
3.01.2010
Ray Allen Shooting Videos
http://www.youtube.com/watch?v=6IPuD8bGdts&feature=related
http://www.youtube.com/watch?v=HOGNWTvLvgE&feature=related
http://www.youtube.com/watch?v=HOGNWTvLvgE&feature=related
100 game-like shots in 20 minutes
The public laments young basketball players’ lack of fundamentals. People see a skill deficiency, especially in ball and player movement and shooting ability, but few understand its roots. Experts pass blame and make excuses, but few criticize players’ daily practice habits. To develop players with better fundamentals, we must teach players how to practice.
Basketball Shooting: The Problem
Player 1 walks into an empty gym, turns on the lights and puts down her ball. She stretches, jogs and does some light plyometric/footwork drills. Player 2 enters the gym, jogs to get loose and does the same warm-up, while P1 does the Mikan Drill. When P2 completes a light warm-up, P1 and P2 start basic shooting drills; passing, closing out to the shooter and rebounding one’s own shot. They start with mid-range jump shots, no further than the free throw line. Player 3 arrives, gets loose and joins a three-person shooting drill. When Player 4 arrives, P1 and P2 work together and P3 and P4 work together. P1 and P2 finally extend the range on their jumpers.
In another gym, P1 enters the gym dribbling and throws a three-pointer at the rim. He walks after the rebound, dribbles back to the three-point line and throws another shot at the basket. P2 enters and P1 shows off an “And1 move.” P2 takes a three-pointer, and then they play one-on-one, dribbling and dribbling and dribbling before shooting. As more players enter, they attempt half court shots, throw balls off the wall and practice double-pump 360-lay-ups.
Gym 1 was the middle school where my Swedish professional team practiced. The second example took place at a local high school and involved high school freshman, junior varsity and varsity players. Before one blames the kids, I attended a WNBA game with the Sacramento Monarchs playing the Indiana Fever and witnesses the exact same approach as example 2, as one player literally shot from the tunnel on her way onto the court and then started bombing errant threes, while other poor shooters never bothered to step inside the key to work on their shooting mechanics.
Shooting: The Proper Approach
Rather than jacking wild shots, great shooters start close to the basket and make a habit of making shots. Anyone can be a shooter; coaches want makers. Young players should shoot 90% of their shots in their range; a player’s range extends to the point where he can no longer shoot without a breakdown in his mechanics. The other 10% of shots should be attempted from just beyond one’s range, as the goal is to extend one’s range. If a player’s range is 15 feet, he shoots some shots from 16-17 feet to work on the extra leg drive needed to extend his range. When he gets comfortable from that distance, he extends again. Even with high school varsity players, we go entire workouts without shooting a three-pointer, as the players train out to 17-feet where they make 75% of their shots, gain confidence and reinforce good habits, rather than developing bad habits.
Shooting: The Workout
Once a player learns the correct shooting mechanics, he needs repetitions in game-like drills. The following is a workout based on the drills and motion of successful NBA shooters.
Dirk Nowitzki Drill
As a warm-up start in the middle of the key; slowly bend into a deep squat with ball in shooting position and explode up into a jump shot. Nowitzki does this drill to increase flexibility (full squat), and it doubles as a good form shooting drill and warm-up. Make five shots and take a step back; shoot until the free throw line. Make 25 shots total.
Rip Hamilton Series
Start on the wing and curl toward the elbow. Each drill in the series starts the same. (1) Curl for a jump shot; (2) Curl and run through the catch, take one dribble and shoot the jump shot; (3) Catch, shot fake, crossover step 1-2 and shoot; (4) stop, flare and shoot; (5) stop, flare, one dribble to the baseline and shoot; (6) run through the catch, dribble and spin for a lay-up or short shot. Make five in each drill and make a free throw in between.
Sue Bird Pull-ups
Speed dribble the length of the floor and pull up at the elbow. Make five.
Seven Spot Shooting
Shoot catch-and-shoot three-pointers (or in the player’s range) from seven spots: baseline, wing, guard-spot, top of the key, guard-spot, wing and baseline. Make five from each spot.
This workout trains a player’s shooting ability, footwork and conditioning; players make 100 game shots (one dribble pull-up, curls, flares, stand-still and full speed pull-ups) plus free throws and form shooting. If the player has a coach to rebound and pass, the workout takes about 20 minutes. This 20-minute workout is more effective than the hours that many players piss away throwing errant shots at the basket to prove they can make three-pointers or show-off some other shot. University of Arizona Head Coach Mike Dunlap says, “Being the best at anything is a bitch.” Becoming a great shooter requires a commitment to excellence and a dedication to developing good, solid mechanics and training game-like shots religiously.
Basketball Shooting: The Problem
Player 1 walks into an empty gym, turns on the lights and puts down her ball. She stretches, jogs and does some light plyometric/footwork drills. Player 2 enters the gym, jogs to get loose and does the same warm-up, while P1 does the Mikan Drill. When P2 completes a light warm-up, P1 and P2 start basic shooting drills; passing, closing out to the shooter and rebounding one’s own shot. They start with mid-range jump shots, no further than the free throw line. Player 3 arrives, gets loose and joins a three-person shooting drill. When Player 4 arrives, P1 and P2 work together and P3 and P4 work together. P1 and P2 finally extend the range on their jumpers.
In another gym, P1 enters the gym dribbling and throws a three-pointer at the rim. He walks after the rebound, dribbles back to the three-point line and throws another shot at the basket. P2 enters and P1 shows off an “And1 move.” P2 takes a three-pointer, and then they play one-on-one, dribbling and dribbling and dribbling before shooting. As more players enter, they attempt half court shots, throw balls off the wall and practice double-pump 360-lay-ups.
Gym 1 was the middle school where my Swedish professional team practiced. The second example took place at a local high school and involved high school freshman, junior varsity and varsity players. Before one blames the kids, I attended a WNBA game with the Sacramento Monarchs playing the Indiana Fever and witnesses the exact same approach as example 2, as one player literally shot from the tunnel on her way onto the court and then started bombing errant threes, while other poor shooters never bothered to step inside the key to work on their shooting mechanics.
Shooting: The Proper Approach
Rather than jacking wild shots, great shooters start close to the basket and make a habit of making shots. Anyone can be a shooter; coaches want makers. Young players should shoot 90% of their shots in their range; a player’s range extends to the point where he can no longer shoot without a breakdown in his mechanics. The other 10% of shots should be attempted from just beyond one’s range, as the goal is to extend one’s range. If a player’s range is 15 feet, he shoots some shots from 16-17 feet to work on the extra leg drive needed to extend his range. When he gets comfortable from that distance, he extends again. Even with high school varsity players, we go entire workouts without shooting a three-pointer, as the players train out to 17-feet where they make 75% of their shots, gain confidence and reinforce good habits, rather than developing bad habits.
Shooting: The Workout
Once a player learns the correct shooting mechanics, he needs repetitions in game-like drills. The following is a workout based on the drills and motion of successful NBA shooters.
Dirk Nowitzki Drill
As a warm-up start in the middle of the key; slowly bend into a deep squat with ball in shooting position and explode up into a jump shot. Nowitzki does this drill to increase flexibility (full squat), and it doubles as a good form shooting drill and warm-up. Make five shots and take a step back; shoot until the free throw line. Make 25 shots total.
Rip Hamilton Series
Start on the wing and curl toward the elbow. Each drill in the series starts the same. (1) Curl for a jump shot; (2) Curl and run through the catch, take one dribble and shoot the jump shot; (3) Catch, shot fake, crossover step 1-2 and shoot; (4) stop, flare and shoot; (5) stop, flare, one dribble to the baseline and shoot; (6) run through the catch, dribble and spin for a lay-up or short shot. Make five in each drill and make a free throw in between.
Sue Bird Pull-ups
Speed dribble the length of the floor and pull up at the elbow. Make five.
Seven Spot Shooting
Shoot catch-and-shoot three-pointers (or in the player’s range) from seven spots: baseline, wing, guard-spot, top of the key, guard-spot, wing and baseline. Make five from each spot.
This workout trains a player’s shooting ability, footwork and conditioning; players make 100 game shots (one dribble pull-up, curls, flares, stand-still and full speed pull-ups) plus free throws and form shooting. If the player has a coach to rebound and pass, the workout takes about 20 minutes. This 20-minute workout is more effective than the hours that many players piss away throwing errant shots at the basket to prove they can make three-pointers or show-off some other shot. University of Arizona Head Coach Mike Dunlap says, “Being the best at anything is a bitch.” Becoming a great shooter requires a commitment to excellence and a dedication to developing good, solid mechanics and training game-like shots religiously.
2.28.2010
JJ REDICK - SHOOTING DRILLS
http://www.youtube.com/watch?v=UhlYBXBf7WA&feature=related
http://www.youtube.com/watch?v=GDAzECm6bCA&feature=related
http://www.youtube.com/watch?v=VCyUIq1OjJM&feature=related
CLICK ON THE LINK BELOW TO WATCH: JJ REDICK - THE JOURNEY
http://www.youtube.com/watch?v=L10rnXuz18o&feature=related
http://www.youtube.com/watch?v=GDAzECm6bCA&feature=related
http://www.youtube.com/watch?v=VCyUIq1OjJM&feature=related
CLICK ON THE LINK BELOW TO WATCH: JJ REDICK - THE JOURNEY
http://www.youtube.com/watch?v=L10rnXuz18o&feature=related
PISTOL PETE
The greatest scorer in college basketball history.
Clink on the link below to watch the 4min video on him.
http://www.youtube.com/watch?v=swHmiNyzHPM&feature=related
Clink on the link below to watch the 4min video on him.
http://www.youtube.com/watch?v=swHmiNyzHPM&feature=related
LARRY BIRD - #1 SHOOTER IN COLLEGE BBALL
Bird is widely considered the best shooter in college basketball history.
In this Video Bird describes a shooter as a player that can shoot from 15-18 feet and make 60-70 shots in a row while working out.
Click on the link below to watch the 4min video...
http://www.youtube.com/watch?v=_1Qn4JjJ_vc
In this Video Bird describes a shooter as a player that can shoot from 15-18 feet and make 60-70 shots in a row while working out.
Click on the link below to watch the 4min video...
http://www.youtube.com/watch?v=_1Qn4JjJ_vc
Evidence That Little Touches Do Mean A Lot
By BENEDICT CAREY
Published: February 22, 2010
Psychologists have long studied the grunts and winks of nonverbal communication, the vocal tones and facial expressions that carry emotion. A warm tone of voice, a hostile stare — both have the same meaning in Terre Haute or Timbuktu, and are among dozens of signals that form a universal human vocabulary.
YOU FEEL ME...
A quick hug, fist pound, high five or belly bump can communicate a wide range of emotions, sometimes more accurately than words.
In recent years some researchers have begun to focus on a different, often more subtle kind of wordless communication: physical contact. Momentary touches, they say — whether an exuberant high five, a warm hand on the shoulder, or a creepy touch to the arm — can communicate an even wider range of emotion than gestures or expressions, and sometimes do so more quickly and accurately than words.
“It is the first language we learn,” said Dacher Keltner, a professor of psychology at the University of California, Berkeley, and the author of “Born to Be Good: The Science of a Meaningful Life” (Norton, 2009), and remains, he said, “our richest means of emotional expression” throughout life.
The evidence that such messages can lead to clear, almost immediate changes in how people think and behave is accumulating fast. Students who received a supportive touch on the back or arm from a teacher were nearly twice as likely to volunteer in class as those who did not, studies have found. A sympathetic touch from a doctor leaves people with the impression that the visit lasted twice as long, compared with estimates from people who were untouched. Research by Tiffany Field of the Touch Research Institute in Miami has found that a massage from a loved one can not only ease pain but also soothe depression and strengthen a relationship.
In a series of experiments led by Matthew Hertenstein, a psychologist at DePauw University in Indiana, volunteers tried to communicate a list of emotions by touching a blindfolded stranger. The participants were able to communicate eight distinct emotions, from gratitude to disgust to love, some with about 70 percent accuracy.
“We used to think that touch only served to intensify communicated emotions,” Dr. Hertenstein said. Now it turns out to be “a much more differentiated signaling system than we had imagined.”
To see whether a rich vocabulary of supportive touch is in fact related to performance, scientists at Berkeley recently analyzed interactions in one of the most physically expressive arenas on earth: professional basketball. Michael W. Kraus led a research team that coded every bump, hug and high five in a single game played by each team in the National Basketball Association early last season.
In a paper due out this year in the journal Emotion, Mr. Kraus and his co-authors, Cassy Huang and Dr. Keltner, report that with a few exceptions, good teams tended to be touchier than bad ones. The most touch-bonded teams were the Boston Celtics and the Los Angeles Lakers, currently two of the league’s top teams; at the bottom were the mediocre Sacramento Kings and Charlotte Bobcats.
The same was true, more or less, for players. The touchiest player was Kevin Garnett, the Celtics’ star big man, followed by star forwards Chris Bosh of the Toronto Raptors and Carlos Boozer of the Utah Jazz. “Within 600 milliseconds of shooting a free throw, Garnett has reached out and touched four guys,” Dr. Keltner said.
To correct for the possibility that the better teams touch more often simply because they are winning, the researchers rated performance based not on points or victories but on a sophisticated measure of how efficiently players and teams managed the ball — their ratio of assists to giveaways, for example. And even after the high expectations surrounding the more talented teams were taken into account, the correlation persisted. Players who made contact with teammates most consistently and longest tended to rate highest on measures of performance, and the teams with those players seemed to get the most out of their talent.
The study fell short of showing that touch caused the better performance, Dr. Kraus acknowledged. “We still have to test this in a controlled lab environment,” he said.
If a high five or an equivalent can in fact enhance performance, on the field or in the office that may be because it reduces stress. A warm touch seems to set off the release of oxytocin, a hormone that helps create a sensation of trust, and to reduce levels of the stress hormone cortisol.
In the brain, prefrontal areas, which help regulate emotion, can relax, freeing them for another of their primary purposes: problem solving. In effect, the body interprets a supportive touch, as “I’ll share the load.”
“We think that humans build relationships precisely for this reason, to distribute problem solving across brains,” said James A. Coan, a psychologist at the University of Virginia. “We are wired to literally share the processing load, and this is the signal we’re getting when we receive support through touch.”
Published: February 22, 2010
Psychologists have long studied the grunts and winks of nonverbal communication, the vocal tones and facial expressions that carry emotion. A warm tone of voice, a hostile stare — both have the same meaning in Terre Haute or Timbuktu, and are among dozens of signals that form a universal human vocabulary.
YOU FEEL ME...
A quick hug, fist pound, high five or belly bump can communicate a wide range of emotions, sometimes more accurately than words.
In recent years some researchers have begun to focus on a different, often more subtle kind of wordless communication: physical contact. Momentary touches, they say — whether an exuberant high five, a warm hand on the shoulder, or a creepy touch to the arm — can communicate an even wider range of emotion than gestures or expressions, and sometimes do so more quickly and accurately than words.
“It is the first language we learn,” said Dacher Keltner, a professor of psychology at the University of California, Berkeley, and the author of “Born to Be Good: The Science of a Meaningful Life” (Norton, 2009), and remains, he said, “our richest means of emotional expression” throughout life.
The evidence that such messages can lead to clear, almost immediate changes in how people think and behave is accumulating fast. Students who received a supportive touch on the back or arm from a teacher were nearly twice as likely to volunteer in class as those who did not, studies have found. A sympathetic touch from a doctor leaves people with the impression that the visit lasted twice as long, compared with estimates from people who were untouched. Research by Tiffany Field of the Touch Research Institute in Miami has found that a massage from a loved one can not only ease pain but also soothe depression and strengthen a relationship.
In a series of experiments led by Matthew Hertenstein, a psychologist at DePauw University in Indiana, volunteers tried to communicate a list of emotions by touching a blindfolded stranger. The participants were able to communicate eight distinct emotions, from gratitude to disgust to love, some with about 70 percent accuracy.
“We used to think that touch only served to intensify communicated emotions,” Dr. Hertenstein said. Now it turns out to be “a much more differentiated signaling system than we had imagined.”
To see whether a rich vocabulary of supportive touch is in fact related to performance, scientists at Berkeley recently analyzed interactions in one of the most physically expressive arenas on earth: professional basketball. Michael W. Kraus led a research team that coded every bump, hug and high five in a single game played by each team in the National Basketball Association early last season.
In a paper due out this year in the journal Emotion, Mr. Kraus and his co-authors, Cassy Huang and Dr. Keltner, report that with a few exceptions, good teams tended to be touchier than bad ones. The most touch-bonded teams were the Boston Celtics and the Los Angeles Lakers, currently two of the league’s top teams; at the bottom were the mediocre Sacramento Kings and Charlotte Bobcats.
The same was true, more or less, for players. The touchiest player was Kevin Garnett, the Celtics’ star big man, followed by star forwards Chris Bosh of the Toronto Raptors and Carlos Boozer of the Utah Jazz. “Within 600 milliseconds of shooting a free throw, Garnett has reached out and touched four guys,” Dr. Keltner said.
To correct for the possibility that the better teams touch more often simply because they are winning, the researchers rated performance based not on points or victories but on a sophisticated measure of how efficiently players and teams managed the ball — their ratio of assists to giveaways, for example. And even after the high expectations surrounding the more talented teams were taken into account, the correlation persisted. Players who made contact with teammates most consistently and longest tended to rate highest on measures of performance, and the teams with those players seemed to get the most out of their talent.
The study fell short of showing that touch caused the better performance, Dr. Kraus acknowledged. “We still have to test this in a controlled lab environment,” he said.
If a high five or an equivalent can in fact enhance performance, on the field or in the office that may be because it reduces stress. A warm touch seems to set off the release of oxytocin, a hormone that helps create a sensation of trust, and to reduce levels of the stress hormone cortisol.
In the brain, prefrontal areas, which help regulate emotion, can relax, freeing them for another of their primary purposes: problem solving. In effect, the body interprets a supportive touch, as “I’ll share the load.”
“We think that humans build relationships precisely for this reason, to distribute problem solving across brains,” said James A. Coan, a psychologist at the University of Virginia. “We are wired to literally share the processing load, and this is the signal we’re getting when we receive support through touch.”
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