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AVM Model Details: St. Catharines, 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)7.8%Half of our predictions are within this percentage of the actual value
Testing R² Score0.730How much of the price variation our model explains
Root Mean Square Error$155162Average prediction error in dollars
Mean Absolute Error$83746Average absolute difference between predicted and actual

Accuracy Distribution

Percentage of predictions within various error ranges

Within 5%32.5%
Within 10%56.8%
Within 15%73.2%
Within 20%83.3%

Prediction Bias Analysis

Does the model tend to overestimate or underestimate?

Mean Bias-$8919Average prediction bias (+ means overestimate)
Median Bias+$2500Typical prediction bias
Over-prediction Rate51.6%Percentage of predictions that are above the actual value
Under-prediction Rate48.4%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$8094$20495$45518$90478$175030$276861

Model Configuration & Training

Training Samples3807
Testing Samples952
Training R²0.800
Testing R²0.730
Last Updated2025-07-03

Additional Performance Metrics

Mean Absolute Percentage Error12.6%Average percentage error across all predictions
Forecast Standard Deviation$154905Spread of prediction errors
Coefficient of Variation24.9%Relative variability of predictions
10th Percentile Error %1.5%10% of predictions have error less than this
90th Percentile Error %28.2%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 Score0.730How much of the price variation our model explains
Root Mean Square Error$164412Average prediction error in dollars
Mean Absolute Error$88521Average absolute difference between predicted and actual

Accuracy Distribution

Percentage of predictions within various error ranges

Within 5%33.5%
Within 10%58.3%
Within 15%72.8%
Within 20%82.8%

Prediction Bias Analysis

Does the model tend to overestimate or underestimate?

Mean Bias-$7298Average prediction bias (+ means overestimate)
Median Bias+$5843Typical prediction bias
Over-prediction Rate52.7%Percentage of predictions that are above the actual value
Under-prediction Rate47.3%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$9411$23687$48181$96671$187144$285943

Model Configuration & Training

Training Samples3807
Testing Samples952
Training R²0.810
Testing R²0.730
Last Updated2025-07-03

Additional Performance Metrics

Mean Absolute Percentage Error12.6%Average percentage error across all predictions
Forecast Standard Deviation$164250Spread of prediction errors
Coefficient of Variation24.8%Relative variability of predictions
10th Percentile Error %1.5%10% of predictions have error less than this
90th Percentile Error %27.1%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