First, we asked the amateur stat geeks of the world to submit us up to four pages of insightful, unique analysis about college hoops. (Here’s the invite.) We staked a $2,000 cash prize for the entry that exhibited the best combination of a compelling topic, rigorous analysis, and refined, persuasive presentation. The entries we received came from people of all backgrounds, from students to professors to professionals.
Then, we whittled the number of submissions down to five finalists, which we sent to an esteemed judging panel stocked with consumers and practitioners of basketball analytics. In the end, eight judges read every finalist’s entry, and weighed in with their rankings and feedback: Mark Cuban, Dean Oliver, Ken Pomeroy, John Gasaway, Ben Alamar, Toby Moskowitz, John Stasko, and Jeff Haley. For judge bios, see the original post.
Now, the judges have spoken, and we are happy to crown our champion of Stat Geek Idol 2: Jordan Sperber.
This post is one of the five finalists in our second Stat Geek Idol contest. It was conceived of and written by Stephen Shea.
In 2006-07, the champion Florida Gators employed a balanced offensive attack, with five players averaging between 10.3 and 13.3 points per game. In contrast, the 2010-11 UConn Huskies relied heavily on the shots of Kemba Walker. The amount of balance in an offense can vary greatly between teams, and the game has seen champions at both ends of the spectrum. We quantify offensive balance (OB). We observe a surprisingly high correlation between OB and rank among the AP’s top 25 teams.
Teams have the ability to measure or quantify nearly every aspect of a basketball game in today’s game. With the use of Synergy Sports, they can easily pin down how they succeed on offense against man and zone defenses, how strong they are on the pick and roll, how their offense performs in transition and countless other scenarios. Many teams chart other aspects of the game themselves, including deflections, most famously done by Louisville and Indiana and recently profiled in this NPR article.
Let me start with an obvious statement: In basketball, players who attempt more shots score more points on average. Other individual stats are also associated with more points, such as rebounds and blocks. Similarly, some statistics, like turnovers, are associated with fewer points scored. In this way, we can compute an expected number of points a player should score based on their other statistics such as shots attempted, rebounds, turnovers, etc. Then we can compare the expected number of points a player should have scored to the actual number of points scored and evaluate players based on their tendency to be above or below their expected number of points. I’m going to call this player efficiency.
This post is one of the five finalists in our second Stat Geek Idol contest. It was conceived of and written by Ryan Silvis.
In 1978, a then promising young coach at Army, Mike Krzyzewski, interviewed for the vacant Northwestern coaching job. Northwestern offered the position to a different coach and Coach K went back to Army only to be hired by Duke in 1980. Since, Coach K has led Duke to 29 NCAA Tournaments, while Northwestern is still looking for their first. Northwestern is again looking for a new coach and hopefully Athletic Director Jim Phillips is on the Stat Geek Idol judging panel, because I will tell him who he should hire.
There are 347 teams in Division I college basketball. The nature of the sport allows for all different kinds of styles of play. Every team has varying player personnel and coaching philosophy. College basketball analysts are given the tough task of forecasting the end result of games featuring contradicting styles. It seems undeniable that, in some cases, certain teams can be bad matchups for other teams. Still, quite frequently analysts just say what sounds good. To illustrate this point, let’s look at a first round matchup from this year’s NCAA tournament:
After a very successful inaugural year, TeamRankings’ Stat Geek Idol competition is back!
Last March, Jeff Haley captured the crown with his analysis of play-by-play data showing the impacts of pace, drawing rave reviews for his work from SGI final round judges including Mark Cuban, Dean Oliver, Ken Pomeroy, and Jeff Ma.
Who’s going to impress the judges and bring home the greenbacks this year? If you’re an armchair stat geek, this is your big chance to get your work noticed by some of the biggest names in basketball analytics and media!
Since last year’s contest was so successful, we’re doubling the prize for the 2013 winner to two grand. We were inspired by last year’s response and want to raise the bar even higher.
- Mark Cuban, Owner, Dallas Mavericks – Shark #1, Shark Tank
- Dean Oliver, Director of Production Analytics, ESPN – Author, Basketball On Paper
- Ken Pomeroy, Owner, KenPom.com – College basketball team consultant
- Jeff Ma, Founder, TenXer & Citizen Sports – Former member, MIT Blackjack team
- Ben Alamar, Professor, Menlo College – Author, Sports Analytics: A Guide for Coaches, Managers, and Other Decision Makers
- Luke Winn, Senior college basketball writer, Sports Illustrated
- John Gasaway, College basketball analyst, ESPN Insider
- John Stasko, Professor & Associate Chair, Georgia Tech – Faculty, CS 4801 SA, Sports Analytics
- Tobias Moskowitz, Professor, University of Chicago – Author, Scorecasting: The Hidden Influences Behind How Sports Are Played and Games Are Won
- Jeff Haley, Founder, Hoop-Math.com - Stat Geek Idol champion 2012
And now at last we can crown a winner! One industrious geek is about to be $1,000 richer …
This is a Final Four submission in our inaugural Stat Geek Idol contest. It was conceived of and written by Jordan Sperber of Hoop Vision (@HoopVision68). For more from Jordan check out his previous round posts.
Sweet 16 entry: Video Charting Wisconsin’s Swing Offense
Round of 64 entry: Quantity Over Quality: Getting More Whacks At The Piñata
Last week, I attempted to quantify Wisconsin’s Swing Offense through the use of video charting. With the Final Four, I set out on a similar goal for Louisville, Ohio State, Kentucky, and Kansas.
To analyze each offense I watched each offensive possession from the Elite Eight of the Final Four teams in slow motion and charted categories such as: number of passes, shot location, defender proximity, number of dribbles the shooter takes, time of possession, number of players crashing the boards, and more. When it was all said and done, I was about 3% closer to becoming a video charting expert.
This is a Final Four submission in our inaugural Stat Geek Idol contest. It was conceived of and written by Nathan Walker of the basketball distribution (@bbstats). For more from Nathan check out his posts from previous rounds.
Sweet 16 entry: Coaches Love Blocks: How Statistics Determine Player Minutes
Round of 64 entry: Not All Points Are Created Equally
Last week, the North Carolina Tar Heels suffered a crushing loss to the Kansas Jayhawks in the Sweet 16. Following the loss of ultimate-pass-machine Kendall Marshall to a wrist injury in their second NCAA tourney game, the Heels looked shaky against Ohio. It took a strong overtime performance by UNC to finish off the Bobcats. Any casual observer could tell you that the Tar Heels struggled to adjust to backup point guard Stillman White; after all, Marshall had barely touched the bench all season, at 33 minutes per game.
After the Ohio game, forward John Henson was quoted saying,
“We didn’t have our starting point guard, so it was a little tough out there.”
And the Tar Heels had to adjust much more, since their 2nd-string point guard Dexter Strickland suffered a torn ACL late January. But intuition and statistics agree that there is a reason adjusting to a point guard loss is tough for any team: your #1 passer plays the large majority of all possible minutes.
Let’s back up for a second.