Bayes Median·Bayes House, 2nd floor
20 Years Inside Officiating: A Referee Explores Its Economics & Incentives
- 20-year NCAA/HS Basketball & Football Referee (retired) | CFAR 2025 Alum | A rat, through and through
10.1/35 attending
Chance I’d attend
I'm giving a talk during LessOnline on my biggest learnings in my 20 year career in officiating (men’s basketball & football):
Inside a Referee's Mind: 20 Years of Officiating Lessons in 40 Minutes
The vibe of Manifest is economics & incentives and data & analytics - at both the individual and market levels.
Rough Shape of a Manifest Talk:
I.R.E.A.M. (Incentives Rule Everything Around Me): A key point from my primary talk: What set of incentives drive officials? In my that talk I only touch on a few things. Here I can explain different levels of incentives and go deep.
What is the pay scale up and down the officiating ladder?
ChatGPT estimates about ~65,000 high school football officials and ~75,000 high school basketball officials. How does that funnel down to the 70 NBA and 121 NFL professional officials?
We kinda treat officials like shit. 😅 Do we at least pay them well? (Outside of those ~200 unionized folks? Nope.) Hmm. Do many professions thrive, do they attract top talent, do they retain that talent - when practioners are poorly paid and poorly treated/regarded? Hmm.
What are the larger economics of sports officiating? How is it structured andor organized? (e.g. NFL model → “part-time” (though a misnomer); NBA → “full-time”)
To the surprise of observers, the NFL and the NFL Referee’s Association union negotiated a surprisingly quick deal this past April. But back in 2012 (and 2001) we had a labor stoppage. What was different this time around?
How do officials and their leagues measure accuracy? Are these good measures? Or merely the best we can do? How much is a pro official than a Division-I college official?
To what extent are officials held accountable for individual calls? “Big/critical” call? Systemic/crew errors? And given the impossible standard (perfection) and requisite human fallibility - should they be?
Gambling forced the professional leagues to publish officials names in advance of games. Gamblers know that officials are not a monolith and different officials produce different qualitative outcomes. Key thought: Is there something prediction markets can learn from this?