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Reference Winter Worn

Reference Tires Premium Touring Winter

The Reference Winter Worn is a Premium Touring Winter tire designed to be fitted to Passenger Cars.

4.9
Tire Reviews Score Based on Professional Tests
Limited Confidence View Breakdown
Dry Grip
0%
Wet Grip
0%
Road Feedback
0%
Handling
0%
Wear
0%
Comfort
0%
Buy again
0%
Snow Grip
0%
Ice Grip
0%
2 Tests (avg: 18th)
Reference Winter Worn

Reference Winter Worn

Winter Budget
BETA
4.9 / 10
Based on Professional Tests · Limited Confidence · Updated 23 Feb 2026

The Tire Reviews Score is the most comprehensive tire scoring system available. It aggregates professional test data from multiple independent publications, user reviews, and consistency analysis using Bayesian statistical methods, weighted normalisation, and recency-adjusted scoring to produce a single, reliable performance rating.

Learn more about our methodology
Category Scores
Dry
61.7
1.13x / 4 tests
Wet
52
1.93x / 4 tests
Comfort
48.5
0.32x / 2 tests
Cross-Category Performance

Cross-category scores are derived metrics that combine data from multiple test disciplines to evaluate real-world performance characteristics.

Braking
57.8
4 tests
Handling
55
4 tests
Score Components
Professional Tests
Weight: 80%
Tests: 2
Publications: 1
Period: 2018 - 2019
User Reviews
Weight: 15%
Reviews: 0
Avg Rating: 0%
Min Required: 5
Consistency
Weight: 5%
Score Std Dev: 0.82
History Points: 10
Methodology & Configuration
Scoring Process
  1. Collect Test Data: Gather results from professional tire tests across multiple publications. Minimum 1 test(s) required.
  2. Normalize Positions: Convert test positions to percentile scores using exponential weighting (factor: 1.2).
  3. Apply Recency Weighting: More recent tests are weighted higher with a decay rate of 0.95.
  4. Incorporate User Reviews: Factor in user review data (minimum 5 reviews). Weight: 15%.
  5. Bayesian Smoothing: Apply Bayesian prior (score: 7, weight: 1.5) to prevent extreme scores with limited data.
  6. Calculate Final Score: Combine all components using normalization factor of 1.1. Max score with limited data: 9.5.
Component Weights
Test Data
80%
User Reviews
15%
Consistency
5%
All Configuration Parameters
ParameterValueDescription
safety_weight 0.7 Weight multiplier for safety-related metrics
performance_weight 0.55 Weight multiplier for performance metrics
comfort_weight 0.4 Weight multiplier for comfort metrics
value_weight 0.45 Weight multiplier for value-for-money metrics
user_reviews_weight 0.15 How much user reviews contribute to the final score
test_data_weight 0.8 How much professional test data contributes to the final score
consistency_weight 0.05 How much score consistency contributes to the final score
recency_decay_rate 0.95 Rate at which older test results lose influence (higher = slower decay)
min_test_count 1 Minimum number of professional tests required
min_review_count 5 Minimum number of user reviews required
score_version 1.9 Current version of the scoring algorithm
score_normalization_factor 1.1 Factor used to normalize raw scores to the 0-10 scale
confidence_factor_weight 0.2 How much data confidence affects the final score
position_penalty_weight 0.2 Penalty applied for poor test positions
gap_penalty_threshold 12 Score gap (%) that triggers additional penalties
min_metrics_count 2 Minimum number of test metrics needed per test
limited_data_threshold 2 Number of tests below which data is considered limited
single_test_penalty 0.75 Score multiplier when only one test is available
critical_metric_penalty 0.7 Penalty for poor performance on critical safety metrics
critical_metric_threshold 70 Score below which a critical metric penalty applies
position_exponential_factor 1.2 Exponent used to amplify position-based scoring
position_exponential_threshold 0.9 Position percentile below which exponential scoring applies
gap_multiplier_critical 3 Multiplier for critical gap penalties
max_category_weight 2 Maximum weight any single category can have
max_score_limited_data 9.5 Score cap when data is limited
bayesian_prior_weight 1.5 Weight of the Bayesian prior in smoothing
bayesian_prior_score 7 Prior score used for Bayesian smoothing
evidence_test_multiplier 1.9 Multiplier for test evidence in confidence calculation
evidence_metric_divisor 3 Divisor for metric count in evidence calculation
evidence_review_divisor 10 Divisor for review count in evidence calculation
combined_penalty_floor 0.2
Data Sources
TestPublicationDateSizePositionMetrics
2019 Summer and All Season Tire Test Auto Navigator 2019 205/55 R16 18/18 5 metrics
2018 New and Worn Summer Tire Test Auto Navigator 2018 205/55 R16 17/17 5 metrics
All Tests
View Test Results
2
Tests
18th
Average
17th
Best
18th
Worst
Latest Tire Test Results
2019 Summer and All Season Tire Test
205/55 R16 • 2019
18th/18
2018 New and Worn Summer Tire Test
205/55 R16 • 2018
17th/17
View Test Results

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