Damages Math 2026: Modeling Payout Ranges with Real Inputs
In serious litigation, “how much is this case worth?” is not a philosophical question. It is a capital allocation problem. Law firms decide where to spend partner time, funders decide which claims to back, and defendants decide when to fight or settle based on one thing: a believable range of outcomes, expressed in money, across time.
Damages math is the discipline of turning messy, human facts into that believable range. In 2026, it is no longer enough to throw a single “headline number” into a complaint and hope experts fix it later. Sophisticated counterparties, litigation funders, and even judges increasingly expect a structured, scenario-based view — something closer to a valuation memo than a one-line prayer.
This article walks through a defense-and-economics framework for modeling payout ranges using real inputs: payroll records, business interruption data, market benchmarks, discount rates, risk weights, and time-to-resolution assumptions. We connect this to themes explored in Litigation Math: How Law Firms Calculate Case Value and Time Cost , and extend it with “compensation metrics” and “settlement value engineering” tools that speak both to courts and capital providers.
Scope note: This is a modeling and strategy overview, not legal advice or an expert report. Jurisdiction-specific rules and retained experts remain essential.
From Story to Spreadsheet: Why 2026 Demands Better Damages Math
Juries and judges still respond to human stories. But the pricing of those stories increasingly happens offstage, in Excel models, funding committees, and insurer reserving meetings. If your numbers are fuzzy, the narrative will not save you.
Three forces are pushing damages analysis toward more disciplined, model-driven work:
- Litigation funding: outside capital wants risk-adjusted returns, not slogans.
- Data-rich claim files: payroll, CRM, telemetry, and medical billing data allow granular loss reconstruction.
- Defense analytics: insurers and corporate defendants benchmark thousands of cases to spot outlier demands instantly.
Against that backdrop, a credible damages model does three things at once:
1. Translates facts into cash flows over time.
2. Applies realistic risk and discounting assumptions.
3. Produces a compact payout range — not a single magic number — that can survive expert scrutiny and cross-examination.
Done well, this becomes a common language across plaintiff counsel, defense, and funders. Done poorly, it becomes exactly the kind of “back of the envelope” math that sophisticated counterparties discount heavily.
Core Building Blocks: What Actually Drives Damages Numbers
Every damages model is unique in its facts. The inputs are not. Over and over, valuation work reduces to the same categories of assumptions, whether the case involves personal injury, employment disputes, or complex commercial contracts.
1. Loss categories
Start with a clear taxonomy of claimed harms. Common economic buckets include:
- Past and future wage loss or lost profits.
- Loss of benefits, bonuses, equity compensation, or business value.
- Medical expenses and related care costs.
- Out-of-pocket costs tied directly to the wrongful conduct.
Non-economic damages — pain and suffering, emotional distress, loss of consortium — resist precise math, but they still sit against reference points: comparable verdicts and settlements in similar fact patterns.
2. Time horizon and accrual pattern
Damages rarely arrive as a single lump in reality. Income and costs are streams. For each loss category, you need:
- The start date and expected end date of the harm.
- The shape of the stream (flat, rising, falling, one-time shock).
- Any step changes such as career plateau, retirement, or business ramp-up.
3. Growth and mitigation
Two questions dominate: “What would have happened but for the wrongful act?” and “What mitigation is reasonably achievable?” That means:
- Projected wage or profit growth in the but-for world.
- Realistic mitigation earnings, business pivots, or replacement contracts.
- Credible timelines for re-employment or business recovery.
4. Discount rates and risk weights
Future cash flows must be discounted to present value. The choice of rate — and whether you apply additional scenario weights — is one of the most heavily contested parts of damages math. At minimum, you should articulate:
- The baseline discount rate (often built from risk-free rates plus a risk premium).
- Separate risk adjustments for liability (chance of winning) and collection (chance of getting paid).
- Case-duration assumptions tied to realistic procedural timelines.
A Simple Damages Math Framework: From Inputs to Range
Conceptually, most damages models boil down to the present value of expected incremental cash flows, plus any non-economic components benchmarked to comparable outcomes.
Working formula (economic portion):
Economic damages ≈ Present value of (But-for cash flows − Actual / mitigated cash flows), across all relevant periods, adjusted for liability probability and collection risk.
You typically do not show this formula verbatim to a jury. You do use it backstage to ensure consistency: if your expert, complaint, and funding deck each rely on different silent assumptions about time, growth, and discounting, the case will feel unstable long before trial.
Scenario Table: Turning One Number into a Range
Credible damages work rarely offers a single “all-or-nothing” number. Instead, you frame low, base, and high scenarios with explicit drivers. That is where modeling stops feeling like advocacy and starts feeling like analysis.
Consider a simplified employment case where a senior employee alleges wrongful termination with three main economic components:
- Lost salary and bonus.
- Lost equity vesting.
- Lost benefits and ancillary compensation.
| Component | Low Scenario | Base Scenario | High Scenario |
|---|---|---|---|
| Remaining career wage loss (PV) | $250,000 | $450,000 | $700,000 |
| Equity / long-term incentive loss (PV) | $80,000 | $150,000 | $260,000 |
| Benefits and ancillary compensation (PV) | $30,000 | $60,000 | $100,000 |
| Total economic damages (PV) | $360,000 | $660,000 | $1,060,000 |
You can then overlay liability and collection probabilities to derive expected values. For example, if you assign:
- 60% chance of winning on liability,
- 95% chance of collecting from a well-capitalized defendant,
- 40% / 40% / 20% weights on low / base / high scenarios,
you can derive an expected economic payout and then consider how non-economic components, fees, and costs adjust the overall settlement range. This is the kind of thinking deepened in Litigation Math and extended here into full payout bands.
Compensation Metrics: Making Numbers Intuitive
Raw totals — “a $900,000 case” — are hard for non-specialists to feel. Compensation metrics translate those totals into relatable units: per month, per year, per life impact. Used carefully, they sharpen both negotiation and storytelling.
Examples include:
- Average annual replacement income needed to make the plaintiff whole.
- Implied hourly value of lost time or capacity.
- Ratio of proposed settlement to documented economic loss.
In personal injury and employment cases, you can connect these metrics to strategy insights like those in Personal Injury 2025: Winning Legal Strategies for Maximum Compensation , where positioning of “full value” versus “discounted value” becomes central.
Caution: compensation metrics are double-edged. Used crudely, they can look like attempts to anchor juries with emotionally charged but analytically weak numbers. The goal is to clarify, not manipulate.
Settlement Value Engineering and Litigation Funding
Once you have a payout range, the question becomes: where should you aim within it, given capital costs, risk tolerance, and portfolio context? That is settlement value engineering — treating your damages model as the engine of a structured negotiation plan.
Litigation funders already think this way. They live inside models that look not unlike private equity deal screens: entry valuation (capital committed), expected exit (payout), timeline, and downside scenarios. Articles such as Litigation Funding Filters: How Capital Firms Evaluate the Financial Worth of Your Case show how aggressively funders interrogate assumptions behind headline demand numbers.
For counsel, the practical implication is simple: if your damages math cannot withstand the questions a funder would ask, it will rarely withstand well-prepared defense experts and actuaries. Aligning your internal modeling standards with funding-grade scrutiny raises the floor of your entire docket.
Operational Playbook: Building a Damages Model Step by Step
A good damages model is not a one-off spreadsheet from a single associate. It is an operational asset that can be updated as facts, discovery, and strategy evolve. The following sequence offers a practical starting point.
Step 1: Define the valuation question precisely
Are you modeling total case value, economic damages only, or a specific component (e.g., lost profits from a breached contract)? Clarity here prevents models from becoming patchworks of inconsistent assumptions.
Step 2: Map data sources and gaps
For each damages component, list the data you have (payroll histories, financial statements, sales records, medical bills) and what is missing. Treat discovery as a targeted data acquisition campaign, not just a document dump.
Step 3: Build a structured timeline
Construct a simple, date-based view of key events: pre-incident baseline, wrongful conduct, mitigation efforts, procedural milestones, and likely end date. Many disagreements about damages are actually disagreements about implicit timelines.
Step 4: Model but-for and actual trajectories
For each stream (earnings, profits, costs), build parallel views: one for the but-for world, one for actual/mitigated outcomes. The gap between them is your economic damages engine.
Step 5: Layer discounting and risk
Apply discount rates and scenario weights explicitly. Document why you chose specific rates, and test sensitivity: how much does the range move if you adjust duration or win probability by ±10%?
Step 6: Translate into negotiation-ready bands
Convert your model outputs into a few clear bands: “walk-away floor,” “target settlement cluster,” and “trial-only upside.” Align these with fee arrangements, funding terms, and client expectations so everyone sees the same landscape.
Red Flags in Damages Math: Signals That Models Will Collapse
From a defense or funding perspective, certain patterns in damages modeling are immediate warning signs. Spotting them early lets you triage which cases deserve more capital — and which models need rebuilding before they face hostile fire.
- Single headline number with no documented assumptions or time structure.
- Mixing nominal and real dollars without clear inflation treatment.
- Ignoring mitigation or assuming zero recovery effort without evidence.
- Using “rule of thumb” multipliers with no link to actual loss data.
- Non-economic figures completely disconnected from comparable outcomes.
- No sensitivity analysis: one model, one outcome, no alternatives.
Many of these weaknesses echo the broader concerns raised in pieces like Reprogramming Justice: How AI Is Transforming Legal Strategy and Case Intelligence , where overconfident models without transparency invite painful surprises.
Integrating Damages Math into a Broader Litigation Economics Strategy
Damages modeling is not a side exercise for experts alone. It is the backbone of how you select cases, price risk, allocate teams, and negotiate. Firms that treat it as a core discipline look more like investment managers than traditional case shops — and that is precisely the point.
On the plaintiff side, rigorous damages math supports docket selection, contingency-fee sizing, and funding negotiations. On the defense side, it underpins reserve setting, settlement authority bands, and early case assessment. For both, it creates a shared, numeric language that narrows the battlefield to genuine disagreements about facts and law.
Over time, firms that build reusable modeling templates — by case type, industry, and jurisdiction — accumulate an internal “compensation metrics” library. That library becomes a strategic asset: new cases can be benchmarked within hours, and outlier positions on either side are easier to spot.
Key Takeaways for 2026
Damages Math 2026 is not about making litigation mechanical. It is about giving structure to the financial side of justice, so that risk, effort, and payout are aligned in ways clients and capital providers can understand.
- Think in ranges, not magic numbers — anchored in explicit scenarios and timelines.
- Use real inputs: payroll, financials, medical billing, and comparable outcomes, not folklore.
- Apply transparent discounting and risk weights that can be defended if challenged.
- Translate models into intuitive compensation metrics that speak to human intuition.
- Align your modeling standards with the scrutiny of litigation funders and defense actuaries.
When your damages math is this disciplined, it stops being a vulnerability and becomes a competitive advantage. Cases are screened more intelligently, negotiations are framed more clearly, and capital — including your own time — flows toward the matters where it can do the most good.
Disclaimer: This article is for educational and informational purposes only. It does not constitute legal, financial, or investment advice, and it is not a substitute for jurisdiction-specific expert analysis or counsel.