In the following 2012 season, NBA teams shot an average of 18.4 three-point shots per game, which had risen by four shots per game since the 2001-02 season. Just five years later, this number rose by 8.6 attempts per game, to an average of 27 attempts in 2017. But what caused this increase?
Tag: sports analytics
Most people’s ideas about analytics in sport are probably based on the book and film Moneyball, about Billy Beane, manager of the Oakland Athletics baseball team in 2002, and his efforts to find a way to build a winning team without overspending. His analytical approach set the foundation for the
I recently paddled in a boat race, and was wondering how I did compared to all the other paddlers. And being a Graph Guy, I decided I should find a cool way to graph the data ... Here's some background information ... There's a great organization called Bridge II Sports
This past weekend, I was a volunteer helping with an Ironman 70.3 race. I was really impressed & inspired by the athletes ... I was also excited about the quantity and variety of data generated by this type of race (compared to a regular marathon). And as a 'graph guy' I
Billy Beane attained fame in baseball and analytics circles long before Brad Pitt portrayed him in the 2011 film Moneyball. In fact, Beane was making quite the name for himself prior to Michael Lewis’s 2004 book of the same name. It’s no overstatement to claim that, as general manager (GM)
Opening Day is here! Every game experience at the ball park is memorable for my family. I'm excited to smell the fresh popcorn and peanuts. I love holding cold drinks in hopes of catching a foul ball with my cup. I’m anxious to see my team’s new prospects in action
Here in the US, it's the nationwide men's college basketball tournament season! Therefore let's use some data from the previous years' tournaments to sharpen our analytics & visualization skills... But before we get started, I must mention (brag?) that my alma mater, NC State University, won this tournament in 1983.
The second round of the 2017 NCAA Men’s Basketball Tournament was an interesting one. Eight-seeded Wisconsin took out the reigning champion Wildcats, despite pundit predictions that Villanova could go all the way again. South Carolina, 24-10 in the SEC during the regular season, upset perennial favorite Duke by seven points.
My high school basketball coach started preparing us for the tournaments in the season’s first practice. He talked about the “long haul” of tournament basketball, and geared our strategies toward a successful run at the end of the season. I thought about the “long haul” when considering my brackets for
The NC Scholastic Chess Championship is coming up this weekend, and my buddy Michael Thomas asked if I might could create a few graphs to help analyze the event data. How could I pass up an opportunity like that?!?! Read along, and find out what graphs I created, and the
“Here comes Chicago. 17 seconds, 17 seconds from Game 7 or from Championship number 6. Jordan open. Chicago with the lead”. These words from a TV commentary describe Michael Jordan 's crucial shot in game 6 of the NBA Finals 1997/98 between the Chicago Bulls and Utah Jazz, which probably
If you are involved in Analytics, you already know that there are some key areas to be aware of in order to achieve results. Over the last year and a half I’ve found that some of those things make Sports a really intriguing and exciting, not to say the ultimate
Who cares about sports and data? Not just athletes, coaches and fans. It turns out that many companies outside of sporting organisations are also associated with the sports industry. For example, financial services organisations are actively involved in sports sponsorships. Retailers sell fan merchandise. Telcos build social engagement strategies around
.@philsimon chimes in on new data-gathering methods and what they mean for analytics.
When you read people’s stories of winning Olympic medals, they often fall into cliché. It's hard not to. In my experience, the nerves, the expectations, the emotions are all heightened beyond what I've ever experienced, so it becomes necessary to use all the hyperbole at your disposal. That said, winning
Machine learning applications for NBA coaches and players might seem like an odd choice for me to write about. Let us get something out of the way: I don’t know much about basketball. Or baseball. Or even soccer, much to the chagrin of my friends back home in Europe. However,
The summer games have all the elements of a great story—power, drama, intrigue, and the key moment when one team rises above the rest and is dressed in gold. I guess I can’t help but love the games -- and as a professional communicator, I can’t resist a great story.
As American football teams prepare to select new team members later today, fans and pundits can only guess how the draft will turn out. Will your favorite professional team make good picks? And will your favorite college players go to good teams? With high stakes and billions of possible outcomes,
With more and more data available these days, and computers that can analyze that data, it's becoming feasible to look for fraud in events such as the Boston Marathon. So put on your detective hat, and follow along as I show you how to use SAS to be a data sleuth!
Last week Robert Allison showed how to download NBA data into SAS and create graphs such as the location where Stephen Curry took shots in the 2015-16 season to date. The graph at left shows the kind of graphs that Robert created. I've reversed the colors from Robert's version, so
People have always been fascinated by sports statistics, and with the recent popularity of fantasy sports there is an increased demand for custom analyses of the sports data. With those folks in mind, I have created a simple example that SAS programmers can use as a starting point for analyzing NBA
There’s been quite a lot of chatter lately about my Boston Red Sox and their recent shift ‘away’ from using analytics or ‘sabermetrics,’ as data science is often referred to in baseball (Jeff Passan, one of my favorite baseball writers, chimes in here – Forbes also commented that the Sox are
April 7, 2003 will go down in the history books for me. The streets of Syracuse, New York, were abuzz. I was a junior television major, and our men’s basketball team had just won its first NCAA basketball title. Our three-seed Orangemen had bested #2 Kansas in New Orleans, but the
As February is coming to a close, many of us in the US, and perhaps around the world, are ready for March Madness. It’s the time of year when colleges competing in the NCAA basketball tournament become the center of attention. Who will be part of the tournament has even
Eating donuts, burning calories, and raising money for a good cause -- that's what the annual Krispy Kreme Challenge is all about. If this intrigues you, read on to find out more... But first, here's a picture of me eating a donut, preparing for a race. I bet you didn't
Shocking headlines to start the new year: Paul DePodesta is leaving the New York Mets and Major League Baseball (MLB) to take a top office position at the Cleveland Browns of the National Football League (NFL). Not so shocked? You don’t care? Who’s Paul De Podesta? Well for those of
It is said that everything is big in Texas, and that includes big data. During my recent trip to Austin I had the privilege of being a judge in the final round of the Texata Big Data World Championship, a fantastic example of big data competitions. It felt fitting that
~ Coauthored by Varsha Chawla and Dale Rierson ~ Here at SAS, we take our sports seriously. With our corporate headquarters in a city surrounded by major universities and with offices all over the world, it’s no wonder that sports data often becomes the forefront of our demos and projects.
With the 2015 World Series currently underway, there couldn't be a more exciting time to discuss how analytics is transforming the game of baseball. It comes as no surprise to say that managers and front office executives, not to mention the players, are continuously looking for a competitive advantage over their opponents.
As a longtime fan of the New York Mets and a longtime employee of SAS, I'm particularly excited about the start of the World Series. In 2014, the Mets and SAS formed a partnership to use SAS analytics to help the organization build stronger relationships with its fan base. While the vast majority of the credit