TravelHub Strictness Score Methodology 2026
The TravelHub Strictness Score estimates how consistently an airline enforces cabin baggage limits at the gate. It is designed as a behavioural metric for trip planning, not a legal interpretation of policy text. The goal is to help travellers understand likely enforcement risk before travel by combining published policy severity with observed real-world outcomes from approved traveller reports.
Why this score exists
Airline policy pages state rules but rarely describe how consistently those rules are applied in daily operations. Two carriers can publish similar dimensions while delivering very different gate experiences. This gap matters because trip decisions are often made near threshold: one small measurement difference can convert a low-cost fare into a high total cost when penalties apply.
The strictness score addresses this uncertainty. It converts mixed evidence into a practical planning signal. Higher scores suggest travellers should avoid borderline baggage and consider pre-purchased upgrades. Lower scores indicate reduced enforcement pressure, though never a guarantee.
Data sources
We use two evidence classes. First, policy data verified against official airline pages: size limits, weight rules, and gate fee structure. Second, reviewed traveller reports containing airline, airport, bag details, and outcome. Reports are checked for plausibility before approval. Obvious spam and contradictory submissions are excluded from calculations.
Initial seed datasets are explicitly marked and treated conservatively. As approved report volume grows, observed enforcement has greater weight in the composite rating.
Core calculation logic
Airport-level check rate is computed as checked outcomes divided by total approved outcomes for a given airline-airport pair. Airline-level strictness aggregates airport evidence with weighting by sample volume so larger datasets influence the composite more strongly than sparse points.
Policy severity contributes baseline structure, especially where report volume is still maturing. In practical terms, high fee severity and zero-tolerance policy language raise baseline risk even before large report samples are available.
Confidence levels
- Low confidence: fewer than 10 approved reports for the airline-airport pair.
- Medium confidence: 10 to 29 approved reports.
- High confidence: 30 or more approved reports.
Confidence levels are displayed alongside check rates where available. Low confidence values should be interpreted as directional indicators, while high confidence values are more stable for planning.
Update frequency and data lifecycle
Strictness recalculation runs weekly. New approved reports are incorporated in the next cycle. Policy records are reviewed on a rolling basis, and changes are reflected on airline pages with updated verification dates. This allows the score to track both policy shifts and operational behaviour changes over time.
How to interpret scores
A high score is a risk warning, not a certainty of failure. It means enforcement is consistently observed and travellers should treat limits as hard constraints. A mid score indicates mixed behaviour and stronger dependency on route and airport context. A low score means relatively lenient outcomes in current data, but travellers should still comply with published dimensions.
Where a score is policy-only, treat it as a conservative baseline until report density improves.
| Score | Band | Practical meaning |
|---|---|---|
| 0-3 | Rarely enforced | Gate agents rarely check. Oversized bags typically board. |
| 4-6 | Spot checks | Checks happen on full flights or with conspicuous bags. |
| 7-8 | Frequent enforcement | Expect sizer use on most flights. Budget for a fee. |
| 9-10 | Near-certain enforcement | Assume your bag will be checked. Non-compliance = paid hold. |
Unscheduled re-verification is triggered when a policy change is detected, when score delta exceeds 2 points in 30 days, or when a disputed report is resolved with validated evidence. Policy-only means the score is currently calculated from official policy alone because user report volume has not reached confidence thresholds yet. For a traveller booking today, that should be treated as a cautious estimate, not final observed behaviour.
Submitting reports and corrections
Traveller reports are critical to model quality. If you recently flew, submit an outcome through the report form. Reports with complete airport, airline, and bag details have highest utility. If you believe a score is inaccurate, a high-quality report is the fastest path to correction.
Limitations
The score reflects historical observations and cannot guarantee future outcomes. Enforcement can shift rapidly due to operational directives, route load, staffing, and seasonal pressure. Use the strictness score with verified dimensions and fare-specific allowances for best decisions.