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AVM Model Details: East Gwillimbury, ON

Detailed performance metrics for our automated valuation models in this location.

Sale price estimation model

This model estimates the sale price of properties in this location based on historical data and market trends.

Key Performance Metrics

Median Absolute Percentage Error (M. MAPE)7.9%Half of our predictions are within this percentage of the actual value
Testing R² Score0.670How much of the price variation our model explains
Root Mean Square Error$252596Average prediction error in dollars
Mean Absolute Error$154074Average absolute difference between predicted and actual

Accuracy Distribution

Percentage of predictions within various error ranges

Within 5%32.0%
Within 10%58.4%
Within 15%76.6%
Within 20%85.2%

Prediction Bias Analysis

Does the model tend to overestimate or underestimate?

Mean Bias-$29887Average prediction bias (+ means overestimate)
Median Bias+$15095Typical prediction bias
Over-prediction Rate53.3%Percentage of predictions that are above the actual value
Under-prediction Rate46.7%Percentage of predictions that are below actual value

Error Distribution Percentiles

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

Percentile10th25th50th75th90th95th
Error Amount$22270$47585$95511$182539$313802$455270

Model Configuration & Training

Training Samples1161
Testing Samples291
Training R²0.750
Testing R²0.670
Last Updated2025-07-03

Additional Performance Metrics

Mean Absolute Percentage Error11.5%Average percentage error across all predictions
Forecast Standard Deviation$250822Spread of prediction errors
Coefficient of Variation20.1%Relative variability of predictions
10th Percentile Error %1.9%10% of predictions have error less than this
90th Percentile Error %24.8%90% of predictions have error less than this

List price estimation model

This model estimates the list price of properties in this location based on historical data and market trends.

Key Performance Metrics

Median Absolute Percentage Error (M. MAPE)7.9%Half of our predictions are within this percentage of the actual value
Testing R² Score0.610How much of the price variation our model explains
Root Mean Square Error$295353Average prediction error in dollars
Mean Absolute Error$173758Average absolute difference between predicted and actual

Accuracy Distribution

Percentage of predictions within various error ranges

Within 5%31.6%
Within 10%57.7%
Within 15%72.5%
Within 20%84.5%

Prediction Bias Analysis

Does the model tend to overestimate or underestimate?

Mean Bias-$58519Average prediction bias (+ means overestimate)
Median Bias-$3018Typical prediction bias
Over-prediction Rate49.5%Percentage of predictions that are above the actual value
Under-prediction Rate50.5%Percentage of predictions that are below actual value

Error Distribution Percentiles

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

Percentile10th25th50th75th90th95th
Error Amount$17089$48136$103363$209935$343286$577082

Model Configuration & Training

Training Samples1161
Testing Samples291
Training R²0.610
Testing R²0.610
Last Updated2025-07-03

Additional Performance Metrics

Mean Absolute Percentage Error11.9%Average percentage error across all predictions
Forecast Standard Deviation$289498Spread of prediction errors
Coefficient of Variation22.3%Relative variability of predictions
10th Percentile Error %1.4%10% of predictions have error less than this
90th Percentile Error %27.8%90% of predictions have error less than this

Monthly rent estimation model

This model estimates the monthly rent of properties in this location based on historical data and market trends.

Key Performance Metrics

Median Absolute Percentage Error (M. MAPE)8.4%Half of our predictions are within this percentage of the actual value
Testing R² Score0.460How much of the price variation our model explains
Root Mean Square Error$488Average prediction error in dollars
Mean Absolute Error$360Average absolute difference between predicted and actual

Accuracy Distribution

Percentage of predictions within various error ranges

Within 5%24.8%
Within 10%56.9%
Within 15%66.7%
Within 20%81.0%

Prediction Bias Analysis

Does the model tend to overestimate or underestimate?

Mean Bias-$48Average prediction bias (+ means overestimate)
Median Bias-$18Typical prediction bias
Over-prediction Rate47.1%Percentage of predictions that are above the actual value
Under-prediction Rate52.9%Percentage of predictions that are below actual value

Error Distribution Percentiles

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

Percentile10th25th50th75th90th95th
Error Amount$51$135$252$511$887$1021

Model Configuration & Training

Training Samples609
Testing Samples153
Training R²0.900
Testing R²0.460
Last Updated2025-07-03

Additional Performance Metrics

Mean Absolute Percentage Error12.7%Average percentage error across all predictions
Forecast Standard Deviation$486Spread of prediction errors
Coefficient of Variation17.3%Relative variability of predictions
10th Percentile Error %2.1%10% of predictions have error less than this
90th Percentile Error %27.5%90% of predictions have error less than this