Team sports
and statistics are no strangers, take sabermetrics, that revolutionized game
analysis for baseball, while making it more fun to watch. The story might sound
familiar if you have seen Moneyball, where Brad Pitt took on the role of Billy
Beane, who pumped up the game of the Oakland A’s.
Compared to
baseball, though, basketball is much more dynamic, and ball movement becomes a
key variable in success. Passing is one of the fundamentals of hoops, and in
the upper ranks of the sport, turnovers — often the result of wayward passes —
contribute to ticks in the win-loss column. Fast, agile passing can make or break
a team. That’s why sabermetrics might not tell the entire story about what
happens on the court. Researchers at Arizona State University, led by life
science professor and basketball fan Jennifer Fewell and math professor Dieter
Armbruster found an ideal model to explain the results of the 2010 NBA playoffs
by simply keeping their eye on the ball. Their work opens the door to an
entirely new line of sports analysis, from game-tape breakdown to highlight
reels and augmented-reality visualizations.
Their
method - not surprisingly – was network analysis, which turns teammates into
nodes and exchanges — passes — into paths. From there, they created a flowchart
of sorts that showed ball movement, mapping game progression pass by pass:
Every time one player sent the ball to another, the flowchart lines
accumulated, creating larger and larger and arrows. Using data from the 2010
playoffs, Fewell and Armbruster’s team mapped the ball movement of every play.
Using the most frequent transactions — the inbound pass to shot-on-basket —
they analyzed the typical paths the ball took around the court.
Network
analysis of the Chicago Bulls, showing the majority of ball interaction
remained with the point guard. Image:
Network
analysis of the Los Angeles Lakers shows the team is far more likely to
distribute the ball among more players, using the “triangle offense.”
For most
teams, the inbound pass went primarily to the point guard, generally a team’s
best ball handler. But point guard-centric, such as the Bulls, didn’t fare well
in the 2010 playoffs, the researchers told Wired. On the other hand, the Los
Angeles Lakers — which won the 2010 NBA championship — distributed the ball
more evenly than their rivals, embracing what Phil Jackson calls the “triangle
offense,” a technique pioneered by Hall of Fame coach Sam Barry. The basic idea
is simple: Maintain balanced court spacing so any player can pass to another at
any point.In their
model, Fewell and Armbruster found a mathematical explanation for why the
triangle offense works — the point guard was no longer the only player feeding
passes to fellow players; his teammates were just as likely to take on that
role. With more potential passers, there are more potential paths for the
opposition to defend.
To quantify
their results, published in the journal PLOS ONE, the researchers derived the
entropy, or measure of system disorder, for each team during each game. In six
of the eight first rounds, winners had higher team entropy, and therefore more
randomness, than losers. Though the sample size of teams in the NBA playoffs
may be small, the data suggest a possible relationship between quick, unpredictable
ball movement and success in games.
While fans
direct cheers that fill sports arenas toward athletic giants such as LeBron
James or Kobe Bryant, bright statisticians still sit in the shadows. But when
these mathematical stars begin helping LeBron improve his game, it’s certain
they’ll hear more and more of the applause.
Hungry for more? Read the full article on Wired.
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