This report is produced by Aviate Alabama using a proprietary six-year longitudinal flight log database covering aircraft movements at general aviation airports across the United States. All findings are derived through custom-built predictive models incorporating linear regression, seasonal decomposition, operator classification, and N-number attribution analysis.
Data is collected, normalized, and validated against FAA registration records and publicly available ADS-B transponder data. Movement predictions carry statistically defined confidence intervals and are benchmarked against observed historical frequencies at the subject airport.
Each report leverages a layered modeling approach:
Linear regression models trained on rolling 90-day, 180-day, and annual windows to establish baseline movement rates
Seasonal decomposition algorithms that isolate day-of-week, month, and holiday-period patterns from secular trends
Operator-class segmentation distinguishing fractional operators, charter fleets, Part 91 corporate flight departments, and private owners
Confidence interval scoring for movement predictions expressed as a percentage probability of at least one event occurring within a defined window
Anomaly flagging when current observed rates deviate significantly from modeled historical norms
Our reports are purpose-built for professionals who need more than a raw flight log — they need interpreted, predictive intelligence they can act on. Our subscriber base spans nine distinct professional categories:
Know exactly when and where rare airframes will appear — before anyone else does.
Identify demand patterns, understand competitor positioning, and optimize fleet deployment by market.
Quantify real-world fleet utilization, validate route capability claims, and pinpoint high-value sales territories.
Assess operator health and aircraft utilization rates to inform collateral valuations and default risk models.
Supplement actuarial models with granular movement frequency, operator profiles, and route-risk exposure data.
Track aircraft associated with portfolio companies, investment targets, or beneficial owners discreetly.
Establish verifiable movement histories, operator patterns, and asset location timelines for litigation or due diligence.
Monitor principal aircraft movements to anticipate arrivals, departures, and exposure windows.
Surface aviation activity as a leading indicator of executive attention, deal activity, and business health for target companies.
A lender financing a fleet acquisition uses utilization frequency data from our reports to validate the operator's claimed flight hours, stress-test residual value assumptions, and identify whether the subject aircraft is genuinely income-producing or parked.
A protective intelligence team receives a 7-day movement prediction ahead of a principal's scheduled arrival, enabling advance site preparation, ground transportation staging, and counterintelligence evaluation of co-located aircraft.
A charter operator uses quarterly airport-level movement reports to identify underserved origin markets where demand for Ultra Long Range aircraft is rising faster than competing operators have recognized — and positions assets ahead of the demand curve.
An investment team cross-references aircraft movements associated with a target company's leadership against known business travel patterns, flagging anomalous activity — site visits, supplier meetings, regulatory appearances — that may signal unreported operational events ahead of a transaction.
