Methodology
Deterministic Scoring Architecture
Trialeze employs a deterministic scoring engine that calculates procedural metrics using weighted formulas derived from structured litigation inputs. All scores are computed algorithmically, ensuring reproducible and explainable outputs.
Core Scoring Formula
Score = Σ(Input_Weight × Normalized_Value) × Category_FactorEach metric applies specific weights to relevant inputs, normalized to a 0-100 scale.
11 Procedural Metrics
Procedural Friction
Case complexity weighted by venue, counsel patterns, and documentation gaps
Documentation Strength
Evidence quality composite from police reports, media, witnesses, completeness
Insurance Leverage
Coverage status, visibility, liability clarity, and damages support
Venue Pressure
Backlog levels, formality, judge environment, jury factors
Opposing Counsel Intensity
Motion patterns, discovery aggressiveness, delay tendencies
Judge Structure
Procedural strictness indicators from court records
Jury Volatility
Presentation risk based on damages clarity and incident complexity
Financial Recoverability
Asset and coverage indicators affecting collection
Medical Documentation
Treatment chronology completeness and intensity
Case Economics
Composite pressure from multiple financial factors
Data Confidence
Input completeness and consistency measurement
Judge & Attorney Pattern Analysis
Procedural pattern data is aggregated from publicly available court records, docket filings, and published opinions. Analysis focuses on observable procedural tendencies, not character or competence assessments.
Data Sources
- • Court docket records
- • Published opinions
- • Bar association records
- • Public case filings
Judge Metrics
- • Motion disposition patterns
- • Scheduling tendencies
- • Settlement approaches
- • Procedural strictness
Attorney Metrics
- • Case volume distribution
- • Motion practice frequency
- • Duration patterns
- • Venue preferences
Report Narrative Synthesis
Analytical narratives are synthesized by processing structured score outputs through templated language rules. The narrative layer interprets computed scores based on threshold conditions and pattern matching, but does not influence or modify the underlying calculations.
Transparency & Reproducibility
Every Trialeze output includes data confidence scores reflecting input completeness. The same inputs will always produce identical scores, enabling verification and audit trails. This deterministic approach ensures defensible analytics suitable for professional legal work product.