Stadiums track everything. Tickets, fans, sponsors, on-field performance, but one problem has quietly resisted innovation for decades: lines.

This week, Jake and Tyler sat down with Sam Porta, founder of Queues, to break down how he went from hacking together queue data at Georgia Tech to helping the Atlanta Braves cut wait times, increase throughput, and uncover hidden inefficiencies using computer vision.

From the true cost of bad data to what “occupancy as a service” could mean for every major venue, this episode digs into why lines still exist — and what it will take to finally fix them.

⏱️ Timestamps

00:00 — Intro: Why Sports Still Struggle With Lines
00:46 — How Qs Started at Georgia Tech
02:35 — Why Google Popular Times Doesn’t Work for Queues
04:13 — Building the First Crowdsourced System
05:06 — Winning Georgia Tech’s InVenture Prize & Hitting COVID
06:41 — Why Sam Didn’t Quit When Lines Disappeared
09:23 — AI, Computer Vision, and the Missing Data Problem
10:57 — The ROI of Queue Data in Airports & Stadiums
12:04 — Who Should Pay for Faster Lines?
13:54 — Disney’s Long-Held Lead in Queue Tech
15:33 — Moving from Dining Halls to Stadiums
17:43 — How the Braves Found Qs
19:30 — From Manual Reporting to Full Computer Vision
22:46 — Testing Qs Across Cafes, Arenas, Waffle House & More
23:31 — Building the First Real Hardware Version
24:12 — How Qs Sensors Count Without Storing Video
25:54 — How Queue Tracking Actually Works
26:18 — Breaking Down the Braves Clubhouse Case Study
29:24 — What Happened When They Eliminated a 25-Minute Line
31:08 — Privacy, PII & Why Qs Doesn’t Store Images
33:07 — Will Stadiums Want More Data on Individual Fans?
36:10 — How Fans Will Eventually See Live Queue Times
37:39 — Occupancy as a Service: How Qs Makes Money
39:44 — Beyond Sports: Airports, Retail & Drive-Thrus
41:43 — The Consulting Layer Hidden in Queue Data
43:35 — Tech Sam Thinks Is Missing in Sports
45:01 — Defensibility: What Stops Competitors?
47:27 — Closing Thoughts & Next Episode Tease
48:05 — Should Everything Be Maximally Convenient?
49:37 — Why People Choose the Longest Line
50:50 — Is Queue Data Part of a Bigger Fan Surveillance Trend?
53:43 — Privacy, Stadium Data & the Slippery Slope
57:34 — Do Speed Cameras Make Cities Safer?
59:29 — Final Thoughts