Risk _____ to Win _____ : Resources
Resources to accompany my 2024 AVCA convention presentation
Click below to view the page with video of the presentation itself as well as a link to the slides.
I don’t remember where I got the land statement but I think the quotation that follows it is the most important part. The map of native territories comes from Native Land Digital and it’s a fascinating resource for learning about indigenous peoples.
The Ellsberg Paradox has multiple formulations. I adapted the “two urn” version into a volleyball situation to make it more interesting and relatable. There is a related paradox (the Allais Paradox) that also highlights how people handle decisions under uncertainty, risk, and certainty.
The differences between gambles that show differences in attitudes towards risk rely on the concept of expected value from probability and expected utility from economics.
I did not invent GAZE (General Assessment Zero Evidence). It came from the original hosts of the 538 podcast Hot Takedown, somewhere back in 2015 or 2016.
The data for the SA/SE and K/AE plots came from Evollve.net and includes NCAA data for Division I teams for each season 2019-2024. I made the plots themselves using Tableau.
The reception average/FBSO plots were made by Chad Gordon and can be found here. I highly recommend Chad’s blog as an introduction to expected value. You can also read my Number Theory series with him by clicking the link below.
The relationship between aces and service errors in my data set is such that each additional 1 percentage point increase in aces is correlated to a 0.67 percentage point increase in service errors. The r-squared value for the relationship is 0.14.
The relationship between kills and attack errors in my data set is such that each additional 1 percentage point increase in kills is correlated to a 0.34 percentage point decrease in attack errors. The r-squared value for the relationship is 0.38.
The exercise of quantifying the relationships is basically what Bayesian statisticians would refer to as establishing your priors. In Bayesian statistics, priors express a degree of belief that an event will occur. Priors are then updated as evidence either supports or negates the prior. If you want to dig into Bayesian and Frequentist views of the world, I suggest reading Cassie Kozyrkov.
The reception average box plot I used to describe variance in performance comes from proprietary data and was made in Tableau. I encourage you to learn what regression to the mean really is.
Peter Krawietz was one of Jurgen Klopp’s top assistants at Borussia Dortmund and Liverpool. Both coaches have since left Liverpool.
To learn about omission/commission bias, I recommend reading Annie Duke’s Substack post about it.
The stacked bar chart I used to discuss points and errors comes from proprietary data and was made in Tableau. In my data set, teams are net-positive 11.6 points in sets they won but only net-positive 6.6 points in sets they lost. While teams make 1-3 more errors in sets they lose, they are scoring 4-6 fewer points in losing efforts. That suggests that scoring points has nearly twice as strong an effect on set outcomes.
The picture of beach volleyball practice came from Alex Luna. You can read our collaboration for Drills in Depth at the link below.
The heat maps I used to discuss diversification and the bar charts I used to discuss optionality came from Volley Metrics scout files for all 2024 Big 12 matches. I made all four plots in Tableau.
You can read about Bounded Rationality here. The idea is important to many books you may have read by or about Daniel Kahneman and Amos Tversky.
The “In the Arena” picture comes from Kelly O’Connor and was taken during the Nebraska-Omaha stadium match. You can read our collaboration for One Player at a Time at the link below.
I wrote a little bit about HAPER during the Fall 2024 season. It stands for Home-Away Point-Error Ratios. You can read more at the links below. The table comes from a Data Volley worksheet I use.
The Team Benchmarks table also comes from Data Volley. You may notice that there are three different versions of PSR (Point Scoring Ratio) on the sheet. There are different ways that people classify earned points and unforced errors. PSR is the number of earned points divided by the number of unforced errors a player/team makes. The plain PSR counts stuff blocks as an earned point for the blocker. PSR+B counts stuff blocks as earned points for the blocker and as an unforced error for the attacker. PSR+b counts stuff blocks as half an earned point for the blocker and half an unforced error for the attacker. I like PSR+b but there’s not a right or wrong way to do it.
The team huddle picture on the “Risk Is Inevitable” slide comes from Maddie Beal. You can read our Drills in Depth collaboration at the link below.
If you have further questions, you can always email me or comment here.