Civil Litigation Dynamics Simulator

An interactive simulation that models the dynamic interplay between procedural strategy, information asymmetry, litigation economics, and settlement negotiations in civil lawsuits.

Live Demo

Try the simulator

Features

Case Configuration

• Liability Strength: Set the true probability plaintiff prevails (parties discover this through litigation)
• Damages Range: Configure potential damages if plaintiff wins
• Claim Complexity: Affects discovery scope, expert needs, and trial length
• Forum Selection: Federal Court, State Court (Urban/Rural), or Arbitration
• Multiple Claims: Model cases with 1-8 distinct legal claims

Party Attributes

• Litigation Budgets: Asymmetric resources create leverage
• Risk Tolerance: Risk-averse parties settle more readily
• Time Sensitivity: Delay costs differ between parties
• Reputation Concerns: Public litigation may harm business relationships
• Fee Arrangements: Hourly, contingency (33%/40%), or hybrid
• Insurance Coverage: Primary, excess, or reservation of rights scenarios

Procedural Dynamics

• Discovery Scope: Limited to scorched-earth discovery strategies
• Expert Witnesses: Expensive but can shift case valuation
• Fee Shifting: American Rule, English Rule, One-Way Pro-Plaintiff, FRCP 68

External Factors

• Judicial Temperament: Neutral, defense-friendly, plaintiff-friendly, or settlement-pusher
• Jury Pool Characteristics: Pro-plaintiff to pro-defense spectrum
• Court Backlog: Affects time to trial

Key Visualizations

Case Value Distributions

Two overlapping probability distributions showing each party's beliefs about case value. Watch them converge (or diverge) as discovery reveals information.

Settlement Bargaining Zone

Real-time visualization of the Zone of Possible Agreement (ZOPA):

• Plaintiff's reservation price (minimum acceptable)
• Defendant's walk-away point (maximum they'd pay)
• Settlement probability based on ZOPA width and party characteristics

Cost Accumulation Timeline

Track litigation costs as they accumulate:

• Phase-based burn rates
• Budget exhaustion warnings
• Milestone markers for key deadlines

Information Asymmetry

Visual representation of what each party knows:

• Initial knowledge vs. discovered information
• Information gap indicator
• Shared knowledge baseline

Decision Cascade Flow

See how factors cascade through the strategic calculus: Information → Beliefs → Expected Values → Reservation Prices → Settlement Probability

How Settlement Pressure Builds

The simulation captures real litigation dynamics:

1. Early Case: High uncertainty, wide belief distributions, large potential ZOPA
2. Discovery: Information revelation narrows uncertainty, costs accumulate
3. Mid-Case: Budget pressure builds, parties reassess positions
4. Late Stage: Trial costs loom, settlement pressure peaks
5. Resolution: Settlement in ZOPA, or trial if positions don't overlap

Interactive Controls

Time Controls

• Play/Pause: Automatic day-by-day advancement
• Speed Slider: 1x to 10x simulation speed
• Fast Forward: Jump 30 days at once

Trigger Events

• File motions (MTD, MSJ)
• Conduct discovery and depositions
• Retain expert witnesses
• Hold settlement conferences
• Make/receive settlement offers

Surprise Events

• Smoking gun evidence discovery
• Key witness changes testimony
• Media attention
• Budget crises
• Third-party additions

Running Locally

Option 1: Simple HTTP Server

cd litigation-simulation
npx serve .

Then open http://localhost:3000

Option 2: Python

cd litigation-simulation
python -m http.server 8000

Then open http://localhost:8000

Option 3: Just Open the File

Double-click index.html to open directly in your browser.

Deploying to GitHub Pages

1. Create a new repository on GitHub
2. Push the code:

git init
git add .
git commit -m "Initial commit"
git branch -M main
git remote add origin https://github.com/willimj3/litigation-simulation.git
git push -u origin main

3. Go to repository Settings → Pages
4. Set Source to "Deploy from a branch"
5. Select "main" branch and "/ (root)" folder
6. Save - your site will be live at https://willimj3.github.io/litigation-simulation

Technical Details

• Pure JavaScript: No frameworks or build process required
• Canvas Visualizations: High-DPI aware rendering
• Responsive Design: Works on desktop and tablet
• No Backend: Runs entirely in the browser

Files

• index.html - Main HTML structure
• styles.css - All styling
• simulation-engine.js - Core simulation logic
• visualization.js - Canvas-based charts
• app.js - UI orchestration

The Model

Belief Updates

Parties use Bayesian updating when new information is revealed. Each discovery event, deposition, or motion ruling shifts beliefs toward the true underlying case value.

Reservation Prices

Each party's reservation price (minimum/maximum acceptable settlement) is calculated from:

• Expected value at trial
• Remaining litigation costs
• Risk tolerance adjustment
• Time pressure factor
• Reputation concerns

ZOPA Calculation

The Zone of Possible Agreement exists when defendant's maximum > plaintiff's minimum. Settlement probability increases with ZOPA width and risk aversion.

Motion Outcomes

Motion success probabilities depend on:

• True case strength
• Judicial temperament
• Random variation (litigation uncertainty)

Partial grants are modeled for motions to dismiss (some claims survive) and summary judgment (some issues resolved).

License

MIT License - feel free to use, modify, and distribute.

Contributing

Issues and pull requests welcome! Areas for potential enhancement:

• Appeal dynamics
• Multi-party litigation
• Mediation modeling
• More sophisticated expert witness battles
• Daubert challenges
• Jury selection dynamics