Travel Distance & Circadian Disruption
Quantifying jet lag's impact on player performance.
Overview
This pillar analyzes how cross-country travel and circadian disruption affect NBA team performance. It provides a unique edge by identifying physically compromised teams that the market often overlooks.
What It Does
It calculates a 'Circadian Disruption Score' based on the number of time zones a team crosses, the direction of travel, and the length of their road trip. This score models the physiological stress on players, which directly correlates with decreased athletic and cognitive performance, especially early in a game before their bodies can adjust.
Why It Matters
The betting public often focuses on recent wins and losses, ignoring the hidden variable of travel fatigue. This pillar offers a predictive edge by highlighting situations where a statistically strong team is likely to underperform due to physiological factors, creating value in spread and first-half betting markets.
How It Works
The model first ingests a team's game and travel schedule. It then measures the time zones crossed for an upcoming away game, applying a higher weight for eastward travel which is harder on the body clock. This data is combined with days on the road to generate a final disruption score, which is then compared against historical performance data in similar scenarios.
Methodology
The core metric is the Circadian Disruption Score (CDS). CDS = (TimezonesCrossed * DirectionalWeight) + (DaysOnRoad * 0.1). The DirectionalWeight is set to 1.25 for eastward travel and 1.0 for westward travel. The analysis is most effective for games played within 48 hours of a team crossing 2 or more time zones.
Edge & Advantage
This pillar finds an edge in early-game markets (first quarter, first half) where the effects of jet lag are most pronounced before players can acclimate.
Key Indicators
-
Time Zones Crossed
highThe net number of time zones a team travels through for an away game.
-
Direction of Travel
highIndicates if a team is traveling East (harder adjustment) or West (easier adjustment).
-
Days on Road
mediumCumulative number of consecutive days spent away from home, indicating accumulated fatigue.
Data Sources
-
Provides game dates, times, and locations for all teams.
-
Historical game data, including scores and betting lines, used to backtest the model.
Example Questions This Pillar Answers
- → Will the Lakers cover the first-half spread against the Knicks on the first game of a long East coast road trip?
- → Will the total score for the Celtics vs Warriors game go under the projected total?
- → Will the Miami Heat win the first quarter against the Denver Nuggets after traveling across two time zones?
Tags
Use Travel Distance & Circadian Disruption on a real market
Run this analytical framework on any Polymarket or Kalshi event contract.
Try PillarLab