It won’t have escaped your attention that a sporting event has just kicked off in Russia; 32 teams and 732 players will be watched by billions of fans before one team earns the right to be crowned world champions. We now know the groups, and the roadmap to the final
Tag: sports analytics
Ever since the Moneyball book & movie came out, athletes have been scrambling to use data and analytics to gain a competitive advantage. One of my favorite sports is boat racing - the ones you paddle. Follow along as I lead you through some maps and graphs I created for
Sports clubs have a lot of data, from a wide range of sources. For the players themselves, there is physical data, about their condition, there is medical information, and there is performance data — goals scored or saved, time on the pitch, that kind of thing. Clubs also have plenty
American readers may know that the ongoing 2018 international soccer/football tournament is a big deal in other countries. But it's hard to grasp just how ubiquitous and important it is when there's no other event like it in the United States. The best way I can describe it is if the
Ballpark Chasers A cross-country trip is pretty much an all-American experience, and so is baseball. Traveling around the country to see all 30 Major League Baseball (MLB) stadiums is not a new idea; there's even a social network between so-called "Ballpark Chasers" where people communicate and share their journeys. Even
What do the New York Mets, the Orlando Magic and the Boston Bruins all have in common? They all use SAS analytics to gain deeper insights into athlete recruitment, retention, performance, safety and more. And after seeing the success teams like these have had using analytics, collegiate sports are turning
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?
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
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.
Regular readers will now be familiar with my recent musings about why and how Sports should embrace and engage with Analytics. While sports are an inspiration already, I’ve been struck by the parallels in objectives, challenges and outcomes with various manufacturing processes. Lately we have been thinking about the impact of
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!
If you don’t believe Analytics and Sports go together you may want to stop reading here. Or you may want to start with validating my previous reasoning on "Why Sports should embrace analytics". If you find you are past the “Why?” you may instead think that the title above doesn’t
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
With the wide spread Moneyball success story you may think this question is already answered. I for one used to think so. However, after I’ve enthusiastically tried to use the Oakland A’s success story as a metaphor and inspiration for applying analytics, with mixed success, I think it’s worth elaborating
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