A Video Charter’s Guide To The Final Four | Stat Geek Idol

The following is the third (Final Four) post I wrote for TeamRankings' Stat Geek Idol. For more information on the competition click here.

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.

Video Charting The Swing Offense Of The Wisconsin Badgers | Stat Geek Idol

The following is the second (Sweet 16) post I wrote for TeamRankings' Stat Geek Idol. For more information on the competition click here.

The Wisconsin Badgers, led by Coach Bo Ryan, are a familiar topic of discussion for stat geeks.

The foundation of advanced statistics in basketball is tempo free. That is, numbers that are not influenced by the pace a team plays at. The Badgers are of course known for their slow pace. Without looking at Wisconsin on a per possession basis, you cannot compare them to teams that play faster.

To analyze Bo Ryan’s Swing Offense I watched each Wisconsin possession versus Vanderbilt in the Round of 32 in slow motion and charted categories such as: number of passes, shot location, defender proximity, number of dribbles the shooter takes, time of possession, and more.

Getting to Know Hoop Vision (Video Charting Overview)

Video Analysis is a technique we will be instituting at Hoop Vision. Video Charting can show different aspects about individual teams. It can show tendencies of how a team functions. For example, how often a team passes and where there shots are coming from. By looking at what happens when a team has success on a possession and what happens on a possession a team does not have success we can make conclusions. However, sample size can play a big role in the charting. The more plays that are charted the more reliable the data is. 82games charted touches/dribbles, rebounds, floor locations, and passes in bulk for the NBA. Great conclusions can be made conceptually for offensive efficiency based on the data.

Despite the clear troubles of sample size, we think charting can give a unique perspective of a game. There are many things we can do with the charting and we will probably be learning as we go. The chart below is the first 10 possessions for Utah St. versus Texas A&M in the NCAA Tourney. With our luck, we picked 10 miserable possessions from a normally efficient team (can't emphasize sample size enough).

Charts with information like this one above will be featured in game recaps. Throughout the year, we will look to provide in depth analysis on keys to success in basketball in general and on a team specific level. Game charting will be one of many ways that we hope to make Hoop Vision unique and insightful.