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Forecast Horizon: Why Early Predictions Are Harder

January 1, 2026 Scorecards

What forecast horizon means

Forecast horizon is the time between when you make a prediction and when the event resolves (or settles).

• Predicting 30 days before resolution is a long horizon.

• Predicting 30 minutes before resolution is a short horizon.

Why early forecasts are harder

Long horizon forecasts are harder because:

• more things can change

• information arrives later

• base rates matter more early on

So if you compare early forecasts to late forecasts without adjusting, you will usually reward people who forecast late.

How horizon affects Brier score

Brier score measures squared error. Early forecasts tend to be closer to 0.50 because uncertainty is higher. Late forecasts can become sharper as information arrives.

If you score everyone at their last update, the best strategy is often to wait. That is not what you want if your goal is to measure skill, learning, or process quality.

Two fair ways to evaluate across time

Option 1: fixed evaluation checkpoints

Use a defined evaluation checkpoint, then score the forecast that exists at that moment.

Examples:

• score the last forecast at T-24h

• score the last forecast at T-6h

• score the last forecast at market close

This makes comparisons fair because everyone is evaluated at the same horizon.

Option 2: horizon buckets

Split performance by horizon ranges:

• 7+ days

• 1 to 7 days

• 1 to 24 hours

• under 1 hour

This shows where skill is coming from. Some forecasters are strong early. Others are strong late.

Common pitfalls

Pitfall: scoring only final forecasts

If you only score the final forecast, you are mostly measuring who updates late and who follows information quickly.

Pitfall: mixing early and late forecasts in calibration

Calibration can look worse if you mix very different horizons. Consider separate calibration tables by horizon bucket.

Pitfall: look ahead bias

If your evaluation accidentally uses information that was not available at the time of the forecast, you introduce look ahead bias. Clear timestamps and an audit trail prevent this.

How to use horizon in a scorecard

A clean scorecard pattern:

• headline: BS and BSS at a fixed checkpoint

• breakdown: horizon bucket table

• diagnostics: calibration per bucket and a forecast distribution

Takeaway

Forecast horizon changes difficulty. Earlier predictions are usually harder, so fair evaluation needs either fixed checkpoints or explicit horizon splits. If you ignore horizon, your leaderboard will reward timing, not forecasting skill.

Related

Forecast Horizon

Evaluation Checkpoint

Audit Trail

Look Ahead Bias

How to Read a Forecast Scorecard