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AVM model details: Czechia

Performance metrics for AVMs in this location.

Model type

Select the type of valuation model you want to view.

List price estimation model

Estimates list prices in this location from historical data and market trends.

Key performance metrics

Median Absolute Percentage Error (M. MAPE)26.7%Half of our predictions are within this percentage of the actual value
Testing R² Score0.620How much of the price variation our model explains
Root Mean Square ErrorCZK 4,459,435Average prediction error in the local currency
Mean Absolute ErrorCZK 2,704,951Average absolute difference between predicted and actual

Accuracy distribution

Percentage of predictions within various error ranges

Within 5%10.0%
Within 10%20.5%
Within 15%30.0%
Within 20%39.5%

Prediction bias analysis

Does the model tend to overestimate or underestimate?

Mean Bias-CZK 730,736Average prediction bias (+ means overestimate)
Median Bias-CZK 206,189Typical prediction bias
Over-prediction Rate46.9%Percentage of predictions that are above the actual value
Under-prediction Rate53.1%Percentage of predictions that are below actual value

Error distribution percentiles

The absolute error amount at different percentiles - for example, '90th percentile: CZK 50,000' means 90% of predictions have errors less than CZK 50,000

Percentile10th25th50th75th90th95th
Error AmountCZK 296,418CZK 733,987CZK 1,680,250CZK 3,265,351CZK 5,863,162CZK 8,649,677

Model configuration & training

Training Samples5306
Testing Samples3320
Training R²0.760
Testing R²0.620
Last Updated2026-10-24

Additional performance metrics

Mean Absolute Percentage Error38.6%Average percentage error across all predictions
Forecast Standard DeviationCZK 4,399,152Spread of prediction errors
Coefficient of Variation56.0%Relative variability of predictions
10th Percentile Error %5.0%10% of predictions have error less than this
90th Percentile Error %75.6%90% of predictions have error less than this