Amateur Statistics For Professional Athletes Part 2
Do numbers lie? Or do we need to just find the right ones?
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See the first part of this series here! Will this be an Empire Strikes Back sequel or a Cars 2 sequel? Please let me know in the comments.
“Who’s a Player You Think Has Really Stood Out So Far?”
Take your mind back a couple of weeks. The WUL championship hasn’t happened yet, and everything is still to play for between the league’s two best teams. How would you pick a winner if you had to choose? Based on who played better in their semifinals? Their early-season head-to-head matchup? Feelings and emotions? No. The only answer is cold hard facts: statistics and math. So let’s crunch some numbers.
Below is part of a table I made using data from my favorite place on the internet: the WUL Stats Hub, as well as a couple of calculations I did myself. I’ve cut out a fair amount of data, so if you want to see the whole data set I’m working with and more, click here. This edited version primarily covers some per-game stats and team efficiencies. A couple of things stood out when considering a championship matchup between San Diego and Seattle.
Like when only looking at Game Score, much of the top end of the data loves San Diego. Throughout the 2023 WUL Regular Season, the San Diego Super Bloom was statistically dominant. They were efficient on both sides of the disc and would not hesitate to punish any mistakes made by their opponents. However, one of the takeaways from the Game Score data was that the impressive regular season performance often came off the back of dominant individual play.
Looking at Seattle in that same team data doesn’t indicate much separation between the two teams. The Seattle Tempest didn’t quite boast the same high-scoring offense that the Super Bloom did but have a rock-solid team defense. They were the most efficient defensive team in the league, generated the most blocks per game, and were only 0.3 points off the league-best mark for points allowed per game. The Tempest and Super Bloom were the two best teams in the league, but it wasn’t clear how to separate them before the game.
“The Best Player We Have…Is Team Ball”
So obviously, the game has already happened, and Seattle ended up winning a rather low-scoring, high-wind affair 13-11. I spent some time crunching numbers and figuring out what happened to the San Diego offense and what Seattle did so effectively to stymie their opponents. Most importantly, I wanted to see if any missed trends could have explained or illustrated a clear difference between the two teams that would have led to this result. And a bit to my surprise, I did find something exciting that demonstrated a clear distinction between the two teams:
Above is a box plot representing the number of points played by each individual during the WUL Championship Game. As you can see, there is a stark difference between the subbing patterns each team applied when a championship was on the line. Seattle played the ultimate (lol, sorry for the pun) team game, with all 21 players playing between seven and eleven points. San Diego rode their heavy hitters, with a much larger data spread ranging from a player who played one point to someone playing 21, just shy of the 24 total completed points. This was such a significant difference in team strategy and philosophy that I wanted to look at their subbing trends during the regular season to see if these philosophies held.
And what do you know, the pattern holds. Across the 2023 WUL season, Seattle maintained the subbing practices of an elite club team, with balance across the top and bottom of their roster. Only twice did someone play five or fewer points in a single game for the Tempest. Meanwhile, only a few times did a Tempest player hit 15 points played in a game, which denoted just the 75% mark of the Super Bloom’s points played data. This subbing spread is reminiscent of a college team riding their top few players while sprinkling their depth pieces as needed.
Looking at the Game Score data for the Post-Season backs this up too. Kaela Helton was the only Super Bloom Player who managed to put a Game Score above 5.0, with a 7.083. Meanwhile, despite the challenging conditions and every player playing at least eight points less than Helton’s 19, five Tempest players clocked in with Game Scores above 5.0. Hana Kawai led with a team and game-high 10.0. Check out the complete game-by-game Game Score Data for the Post-Season here.
Let’s be honest. In a one-game situation with the season on the line, we can’t just make statements about how teams should sub. We don’t know the team chemistry or strategies that went into how those decisions are made. However, we know that it was a real grind of a game of Ultimate between two excellent teams. The points were long, and the weather often worked to extend them. And while the Super Bloom often chose to keep their top players out there repeatedly, the Tempest felt comfortable rotating through their entire roster to ensure they had fresh legs for every point. And that very well may have been the difference between the two teams. The one thing we learned is that you can’t take the team ball out of Seattle.
About The Breakside
The goal of this newsletter is to tackle what I see as a gap in the present coverag
e of Ultimate as a sport. I hope that this newsletter will provide an outlet for important, yet overlooked people and stories to receive the coverage and perspectives they deserve.
About the Author
My name is Noam Gumerman (he/him), and I am a recent grad of Brandeis University in Waltham, MA, and future grad student at Davenport Univerrsity in Grand Rapids, MI. I am from Chapel Hill, NC, and have just finished studying Journalism and American Studies for my undergraduate degree. I captained Brandeis TRON for two and a half years. I will be starting a masters program at Davenport University on an athletic scholarship for Ultimate this fall. My claim to fame within the Ultimate community is running the @being_ulti account during the week of the 2022 WUCC tournament. Contact me for discussions, feedback, story suggestions and more on Twitter at @noamgum, or via email at ngumerman@brandeis.edu.