Upgrade Pro

How we predict your upgrade odds — and how often we're right.

Upgrade Pro turns live airline data — waitlists, fare buckets, seat maps — into a calibrated probability you'll clear the upgrade list. Here's exactly how it works, plus an honest monthly scorecard of our hits and misses.

WHAT YOU'LL SEE

Reading a search at a glance.

Every search opens with a five-day view. Each day breaks into morning, afternoon, and evening bars — height and color show the best upgrade odds in that window — with the day's headline number underneath. Tapping a bar filters the results to that day and time of day.

MONJun 22
34%Afternoon
TUEJun 23
41%Afternoon
WEDJun 24
52%Afternoon
BEST
THUJun 25
38%Afternoon
FRIJun 26
26%Afternoon

Below it, every flight is one row: schedule, aircraft, open premium seats against cabin size, fare, and the upgrade score — the model's calibrated probability with its honest range — plus one-tap booking on the airline's own site, saving to My flights, and an expandable factor analysis.

FlightScheduleAircraftSeatsPriceUpgrade score
UA 1525 10:24 AM → 6:05 PM
4h 41m · nonstop
Airbus A321neo 10 / 20 $486
57% Contender band 44–60%
Book on United ↗

10 of 20 premium seats open now (~6 expected by departure); you project around #3; modeled from typical elite demand on this route (no live waitlist yet) — a real contender — reasonable to book, unwise to count on.

Illustrative example with sample numbers — run a search to see live odds for your status.

OUR STORY

Built by a road warrior, for road warriors.

I spend a serious share of my life in seat 12C, hoping it turns into 2A. I also spent years building machine-learning models for a living.

So I got tired of folk wisdom and gate-agent tea-leaf reading, and built a calibrated model to tell me which of my own flights were actually worth booking. It changed how I book — sharing it felt obvious.

Upgrade Pro tells you the truth the way I wanted to hear it: a probability with honest error bars, not a marketing number.

THE FOUR BANDS

What a verdict actually promises.

Every prediction lands in one of four confidence bands, set by the model's calibrated estimate. The ranges below are the odds you can expect when you see each label on a flight.

Strong 65–100%

Book it expecting the upgrade. Still not a guarantee — roughly 1 in 4 will miss.

Contender 40–65%

Leans your way: reasonable to book, unwise to count on.

Underdog 15–40%

Possible, not probable — the odds are genuinely against you.

Long shot 0–15%

Don't count on it clearing. Book this flight for the schedule, not the seat.

0255075100%

The method, in four steps

01

We read what the gate agent sees

Live standby queues, fare-bucket inventory (J, C, D, PZ, PN), seat maps, and aircraft type — polled repeatedly as departure approaches. Where an airline blocks automated reads, we fall back to an estimated profile and label it plainly.

02

A calibrated model scores it

A Random Forest classifier, trained on 26,982 real-world standby passenger snapshots and isotonically calibrated, weighs your queue position, open seats, route competitiveness, timing, and route history. The model achieves 94.8% accuracy and 0.966 ROC-AUC in group-based cross-validation.

03

The band is the honest part

We never show a bare number. The band is the spread of the model's internal trees — wide when they disagree, tight when they agree. "Contender, 44–54%" is a real contender that leans your way: reasonable to book, unwise to count on.

04

We grade ourselves in public

Each month, every prediction is compared to the verified gate outcome and published below — including the calibration chart and historical Brier scores. When we're wrong, you'll see it here.

Where we're weakest — honestly
EARLY DAYS

This product is young, and it will say so.

Upgrade Pro is in its early stages. Coverage deepens airline by airline, the model retrains as every tracked flight becomes new training data, and the calibration above gets more trustworthy with each monthly audit. Expect rough edges, expect visible improvement — and when something is estimated rather than live, expect us to label it instead of dressing it up.

If something looks wrong, that feedback genuinely shapes what gets built next.