How Much Did Everyone on Your Flight Pay?

Every traveler fears being the person on a flight who paid the most for their plane ticket.

Since you can't really ask every person how much their plane ticket cost, Hopper took a look at the range of prices that are quoted in search results. We looked at the minimum and maximum prices and a measure of variability. The flights with a higher percent variability are the ones where there is a higher mix of prices and a low percent indicates that prices are more constant. Higher variability also means there is more opportunity to get a better deal, but where you can also end up being the person who overpaid if you don't do your homework before buying.

We looked at past flights between Los Angeles and Las Vegas to show how the price distribution varied by flight and by airline (Figures 1 and 2). We also analyzed an additional 5 markets to see how price distribution varies by market (Figure 3). When looking at a specific flight between Los Angeles and Las Vegas, we found that prices can vary from under $200 to over $1,600 (all in coach). Most people could buy a ticket for under $600, those who scored a good deal paid under $400, and every once in a while someone with incredible luck scored a ticket for under $200.

The range in flight prices varied by airline, with Spirit and Virgin having the most uniform price distributions. Distribution of prices also varies significantly from market to market (Figure 3), so being educated about the best price to pay for a given market is very important if you don't want to be the flier with the most expensive ticket.

To avoid paying too much for your plane ticket:

• Be knowledgeable about what a good deal price is for your specific route. Distribution of prices varies significantly by market so it's important to be aware of how much you should be paying for your specific route. If you're not sure, check Hopper's When to Fly and Buy reports.

• Book your ticket early. In general, it's best to book about 30 days in advance.

• Monitor what prices other people are finding. Hopper Flight Explorer monitors and analyzes over 32 million real-time flight searches conducted by real people each day across the web. Each flight is labeled with a deal ranking so you'll know whether the flight is in the lowest-priced 10% of flights.

• Look at the price distribution for your specific trip. Hopper's Origin-Destination Technical Reports can show you how prices may vary on your specific route.

The flights with a higher percent variability are the ones where there is a higher mix of prices and a low percent indicates that prices are more constant. Higher variability also means there is more opportunity to get a better deal, but where you can also end up being the person who overpaid if you don't do your homework before buying.

Figure 1: Price distribution by flight

Figure 2: Price distribution by airline (4B is Perimeter Aviation, AA is American Airlines, VX is Virgin, NK is Spirit, DL is Delta, an UA is United)

Figure 3: Price distribution by market

5 airports where it's most important to compare ticket pricesDomestic destinations with the highest airfare price variability

• IAD - Washington (23.1%)

• ORD - Chicago (21.2%)

• MYR - Myrtle Beach (21.0%)

• OAK - Oakland (20.0%)

• LAX - Los Angeles (18.9%)

5 airports where it's least important to compare ticket pricesDomestic destinations with the lowest airfare price variability

• OGG - Kahului (8.3%)

• HNL - Honolulu (10.2%)

• MCO - Orlando (13%)

• PBI - West Palm Beach (13.8%)

• IND - Indianapolis (14%)

Data and MethodologyThe data presented in this analysis comes from Hopper's combined feed of Global Distribution Service (GDS) data sources which includes about 10 million queries and 1 billion trips per day. Demand is represented as the number of queries not actual ticket purchases, and is calibrated across all GDS sources for each market.

Charts in this report were generated using search and price data for early May. However, the charts found in the individual market reports are updated continuously to reflect current data.