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title: When Data Science Makes Us Sad: The Story of an...
description: Airlines intentionally oversell flights using probability and expected value calculations. Using a worked example of 304 tickets sold for a 300-seat flight...
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# When Data Science Makes Us Sad: The Story of an Overbooked Flight

**[Towards Data Science](https://daily.dev/sources/tds)** · 8 min read · 0 upvotes · 0 comments

## Summary

Airlines intentionally oversell flights using probability and expected value calculations. Using a worked example of 304 tickets sold for a 300-seat flight with a 95% show-up rate, the post walks through binomial distribution to calculate the overbooking probability (~0.014%), the expected number of bumped passengers, and the financial trade-off: $8M in extra revenue vs. under $5K in compensation costs across 10,000 flights. The post also covers the non-mathematical risks like viral PR incidents and how reverse-auction voucher systems help airlines avoid them.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://towardsdatascience.com/when-data-science-makes-us-sad-the-story-of-an-overbooked-flight>

## Questions this post answers

### How do airlines use probability to decide how many extra tickets to overbook on a flight?

Airlines model passenger show-up behavior with a binomial distribution, treating each ticket holder as an independent trial with a fixed probability of showing up (e.g., 95%). For a flight with 300 seats selling 304 tickets, the probability of overbooking (301+ passengers showing up) comes out to about 0.014%, or roughly a 1-in-7,200 chance, letting airlines weigh the tiny compensation risk against guaranteed extra ticket revenue.

_daily.dev surfaces practical probability and statistics breakdowns for anyone modeling real-world business risk._

### What is the expected value of the number of overbooked passengers when an airline sells 4 extra tickets on a 300-seat flight?

The expected value is about 0.000166 overbooked passengers per flight, calculated by weighting each possible overbooking outcome (1, 2, 3, or 4 extra passengers) by its binomial probability. Scaled across 10,000 flights, this averages to about 1.66 total bumped passengers, a tiny number compared to the 40,000 extra tickets sold over the same set of flights.

_Developers modeling risk and rare-event probabilities can find similar worked examples curated on daily.dev._

### How much extra revenue can an airline earn from overbooking flights compared to the compensation costs?

Selling 4 extra tickets on each of 10,000 flights at an average $200 fare generates $8,000,000 in additional revenue, while expected compensation costs for the roughly 1.66 bumped passengers across those flights total under $5,000, since US Department of Transportation rules cap bumping compensation at $2,150 per passenger. This makes overbooking financially favorable despite the reputational risk of a viral bumping incident.

_daily.dev collects data-driven case studies like this for readers weighing quantitative trade-offs in their own work._

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---

Tags: [#data-science](https://daily.dev/tags/data-science), [#statistics](https://daily.dev/tags/statistics)

[View this post on daily.dev](https://daily.dev/posts/when-data-science-makes-us-sad-the-story-of-an-overbooked-flight-te80fcvme)

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