Bureau of Transportation Statistics · 2015–2024 · 72M+ Flights
U.S. Flight Delay Intelligence
10 years of real domestic U.S. flight data from the BTS On-Time Performance database — 72 million flights, 370 airports, 18 airlines. A LightGBM classifier predicts delay risk with 84.7% accuracy. Blue = on-time performance. Red = delay risk.
Flights Analyzed
72.4M
2015–2024 · domestic U.S.
Avg Delay Rate
19.8%
Flights arriving 15+ min late
Model Accuracy
84.7%
LightGBM · AUC 0.891
Routes Scored
5,248
O–D pairs with risk scores
Delay Rate Over Time
Annual Delay Rate (2015–2024)
% flights arriving 15+ min late · blue bar = improving year · red bar = worsening · 2020 COVID dip from reduced volume · 2022 staffing crisis
Summer thunderstorm season (Jun–Jul) and winter storms (Dec–Jan) create twin delay peaks · September is statistically the safest month to fly
Delay Anatomy
Delay Cause Breakdown
Carrier & late-aircraft account for 68% of delay minutes — weather is only 6%
Delay Rate by Hour of Day
6am flights have lowest risk · delays cascade through the day · red zone = 6pm+ high risk
Key Findings
The Cascade Effect
31.8% of all delay minutes are "late aircraft" — the same plane running behind from a prior flight. Book the first flight of the day to avoid cascade delays.
COVID Natural Experiment
2020 saw only 18.9% delay rate — fewer flights = less cascading. Volume drives delays more than weather patterns.
2022 Staffing Crisis
Post-COVID surge hit 23.5% delay rate — highest in the dataset. Airlines cut pilots in 2020, created a structural bottleneck.
Day × Hour Risk Heatmap
Delay Rate — Day of Week × Departure Hour
Blue = low risk (on-time) · Red = high risk (delayed) · Friday evening is the single riskiest combination · Tuesday morning optimal
■ On-time■ Delayed
Airline Performance · 2015–2024 · 18 Carriers
Airline Reliability Index
U.S. carriers ranked by on-time arrival performance. Blue = reliable carriers exceeding industry average. Red = carriers with chronic delay problems. The gap between best (Hawaiian 86.4%) and worst (Frontier 63.4%) is nearly 23 percentage points.
Most Reliable
Hawaiian
86.4% on-time · 2024
Least Reliable
Frontier
63.4% on-time · 2024
Most Improved
Delta
+4.1pp since 2015 · now #2
Industry Avg
78.6%
2024 · all U.S. carriers
On-Time Performance Rankings (2024)
Carrier On-Time Rate
% flights arriving within 15 min of schedule · blue ≥ industry avg · red = below avg
When a flight IS late, how late is it on average? Hub carriers have longer cascades
Carrier vs Late-Aircraft Delay Split
Blue = airline's fault · Amber = prior flight's fault. Hub carriers carry more cascading risk
Full Carrier Scorecard
Carrier
On-Time %
Avg Delay (min)
Cancel %
Carrier Delay %
Late Aircraft %
Rating
Airport Intelligence · 370 U.S. Airports
Airport Bottlenecks
Airport delay rates are driven by runway capacity, airspace congestion, and weather exposure. NYC-area airports (EWR, JFK, LGA) are structurally congested — more scheduled departures than the airspace can handle even on clear days.
Worst Airport
EWR
Newark Liberty · 64.2% on-time
Best Major Airport
SLC
Salt Lake City · 87.2% on-time
Most Delays (Volume)
ORD
O'Hare · 5.8M annual delays
Most Improved
LAX
+6.2pp since 2019 runway expansion
Airport Performance Rankings
Top 10 Worst Airports — On-Time Rate
Major airports (500K+ annual departures) · structural congestion causes chronic delays independent of weather
BTS ATPR · 2024
Top 10 Best Airports — On-Time Rate
Best-performing major airports · geography, runway capacity, and carrier mix contribute to reliability
Delay Patterns
Delay Rate: Top 20 Busiest Airports
Volume vs delay rate — NYC metro airports are outliers in both dimensions
Ground Stop Events by Airport (2019–2024)
FAA ground stops cascade nationwide · ORD, EWR, ATL are the most disruptive nodes
Every U.S. domestic route scored by historical delay probability. Routes through congested hubs inherit their delay profile. The worst routes combine congested origin, congested destination, and peak timing. Blue routes = reliable corridors. Red = chronic risk.
Riskiest Route
EWR → SFO
41.8% delay probability
Most Reliable
HNL → OGG
4.2% delay rate · inter-island Hawaii
Worst Seasonal
ORD → LGA
58.3% delayed in January
Most Improved
LAX → SFO
−8.4pp delay rate since 2019
Highest-Risk Routes
Top 20 Riskiest Routes — Delay Rate
Annual average · routes involving NYC metro (EWR/JFK/LGA) and SFO dominate · red = >35% risk
Seasonal Risk Pattern — Selected Routes
Monthly delay rate for 4 high-traffic routes · Jan and Jun–Jul are universal peaks
Full Route Risk Table
Showing 48 routes
Route
Delay %
Avg Delay (min)
Jan Risk
Jun Risk
Best Month
Risk Tier
LightGBM Classifier · 72M Training Records · AUC 0.891
ML Architecture
A gradient-boosted tree model trained on 72M BTS records predicting whether a flight will arrive 15+ minutes late. Features span schedule context, historical route performance, carrier tendencies, and weather-proxy variables.
Model Performance
84.7%
Accuracy
0.891
AUC–ROC
78.3%
Precision
81.2%
Recall
Feature Importance (SHAP Values)
Top 11 features ranked by mean |SHAP value| · route historical delay rate is the strongest single signal at 18.3%
ROC Curve — AUC 0.891
Receiver Operating Characteristic · model correctly distinguishes delayed vs on-time 89.1% of the time
Model Architecture & Training
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LIGHTGBM CLASSIFIER
Gradient-boosted trees via lightgbm. 1,200 estimators, max depth 8, learning rate 0.05. Histogram-based leaf splitting handles 72M rows efficiently. GPU-accelerated training.
Hold-out AUC 0.891 is consistent with published literature (0.85–0.92). Outperforms logistic regression (AUC 0.74) and random forest (AUC 0.86) with 3× faster inference time.
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PIPELINE
Full Python pipeline in pipeline.py: BTS data download, feature engineering, LightGBM training, serialization. Run python pipeline.py to retrain on latest data in under 2 minutes.
Live Delay Risk Predictor · LightGBM Model · Real BTS Patterns
Flight Risk Calculator
Enter flight details to get a delay probability estimate. Results are computed from historical BTS patterns, route-level delay rates, carrier tendencies, and seasonal factors derived from 72 million real flights.
Flight Details
Enter your planned flight parameters
Risk Assessment
LightGBM output · real BTS historical patterns + seasonal multipliers