Methodology

OffPeakTrip's core feature is predicting how crowded an attraction will be on a given future date. Rather than relying on a single data source, we combine multiple dimensions through a weighted algorithm to produce a 0-100 crowd score.

Each attraction's crowd score is calculated from four weighted factors:

Category Adjustments

Different attraction types respond differently to holidays and weekends:

• Theme parks see the biggest holiday surge (×1.20) and weekend boost (×1.15)
• Landmarks have notable holiday effects (×1.15) but normal weekends
• Nature spots are actually less crowded on holidays (×0.75) as tourists concentrate in cities
• Museums see slight holiday increases (×1.10) but slightly lower weekends (×0.90)

Weather Adjustment

When weather is severe (factor < 0.4, e.g. heavy rain or extreme heat), outdoor attractions receive a 30% score reduction. Indoor attractions are unaffected.

Non-linear Compression

The final score uses 0.8 power compression (base^0.8) to prevent all popular attractions from saturating at 100 during holidays. This provides better differentiation in the 60-90 range.

Each level corresponds to a different queuing expectation: "Quiet" means almost no queuing, "Crowded" means long queues throughout the day. These descriptions are calibrated against real visitor feedback.

Our predictions are estimates based on historical patterns, not exact counts. Known limitations include:

• International cities lack migration data — a default value of 0.5 is used
• Weather forecast accuracy decreases beyond 5 days
• Unexpected events (temporary closures, special events) cannot be predicted
• The "crowded experience" varies by venue size and visitor flow design

We continuously refine our algorithm and welcome user feedback to improve prediction accuracy.

Related: About Us · Data Sources