Discovery stretches on. A hearing is postponed. A fully briefed motion sits for months without a ruling.
From inside a single case, these delays can seem random—and therefore impossible to plan around. But although every lawsuit brings its own surprises, the court systems through which lawsuits move exhibit recurring patterns. Those patterns vary across jurisdictions, judges, practice areas, attorneys, and procedural events. Measured together, they can make litigation timelines more predictable.
Every litigation plan rests on a forecast of how these variables will play out in a particular case. To begin building that forecast, we analyzed Trellis state trial court data through the ChatGPT plugin and the Claude MCP connector to answer one simple question:
Where does the time actually go?
A lawsuit is mostly waiting
We often frame litigation as a sequence of activity: complaint, answer, discovery, motions, trial. But the reality is different. Litigation is mostly a series of events separated by long stretches of inactivity. A motion might take a day to draft, and a hearing might last thirty minutes, but weeks or months pass between those milestones.
That waiting time is neither evenly distributed nor entirely random. How much accumulates depends partly on where a case is litigated. What produces it depends on the procedural events—and the participants—that shape the case.
Examining both dimensions reveals the structure of docket drag and provides a foundation for estimating not only how long a case may last, but why.
The geography of delay
The duration of a case depends in part on where it is filed. Holding the practice area constant and changing only the state produces strikingly different timelines.
Tort cases in California resolve in less than half the time they do in New York or Texas. Similar dynamics exist within each state. For example, within California alone, torts cases average 393 days in Los Angeles County but 1,021 days in San Francisco County.
These figures should not be treated as guarantees. They are planning inputs: historical baselines that can help legal teams assess how geography may affect reserve estimates, litigation budgets, client expectations, venue strategy, and the timing of settlement discussions.
Knowing the average duration, however, answers only one part of the question. To understand how delay develops, we also need to examine what happens during that time.
The architecture of delay
Consider an illustrative sample of five tort cases in Los Angeles County. Across their dockets, different sources of delay emerge: routine scheduling adjustments, court administration, and contested disputes. Not every mechanism appears in every case. In fact, that variation is the point. Cases of similar types moving through the same court can accumulate time in very different ways.
Routine scheduling. Two of the five cases included continuances or extensions categorized as routine scheduling. These events may add substantial time without indicating meaningful conflict between the parties.
Court administration. Case management conferences, trial-setting activity, and other administrative events represent a different source of elapsed time: the court’s own procedural cadence. A case may simply move from one court-scheduled milestone to another, with weeks or months passing in between regardless of what either party is doing.
Contested disputes. Discovery-compel motions, general motions to compel, sanctions motions, and stay-of-proceeding motions introduce another source of delay. Across broader Trellis data, grant rates, when these motions are actually decided, range from roughly 73% to 82%. But many never reach a ruling at all, resolving through compliance, negotiation, or settlement before the court has to decide them.
Across these five dockets, the sources of delay often overlapped. The one case involving a contested dispute also experienced routine scheduling adjustments and court administration, illustrating how different mechanisms can compound within the same litigation.
These patterns can be understood as both structural and behavioral. Some waiting is built into the court’s administration of a case; some emerges from the decisions and practices of the people litigating it. Understanding case duration means accounting for both, including how frequently a particular mechanism arises and how much time it is likely to add when it does.
Whose patterns shape the timeline?
Geography and procedural events do not explain all the variation. The people involved matter, too.
Judges shape timelines through courtroom management and procedural practices; attorneys shape them through litigation strategy, motion practice, and settlement behavior. Across a sufficient number of cases, these decisions form measurable patterns that can refine expectations for a particular matter.
Judges
Once a judge is assigned, the timeline becomes more specific. Judges differ in how they manage the procedural events that move—or stall—a case, and those differences can reveal where to expect time to accumulate.
Consider three judges with high-volume tort dockets in Los Angeles County.
The Hon. Christopher K. Lui grants continuances and compel-discovery motions more frequently than the Hon. Laura A. Seigle, yet his cases resolve nearly three months sooner. Meanwhile, the Hon. Mark E. Windham has the highest grant rates for both motion types—and the longest average case length of the three.
The comparison demonstrates why no single statistic can serve as a proxy for a judge’s expected timeline. A high continuance rate, for example, does not necessarily imply a longer overall case. Duration emerges from the interaction of multiple procedural practices, the cases assigned to the judge, and other docket characteristics.
A judge profile built across several measures can nevertheless help attorneys identify where delay has historically accumulated and how an assigned judge differs from the broader court.
Attorneys
Attorneys also develop recognizable litigation patterns over time. Those patterns become visible only when viewed across an entire practice. One California defense attorney, anonymized to protect his identity, illustrates the point.
Across 179 state trial court cases, nearly three-quarters in Los Angeles County, John Smith represents insurers, collections clients, and personal injury defendants. At first glance, it looks like the kind of practice that could produce long-running litigation. Yet the broader docket tells a different story. Nearly two-thirds of his cases end in dismissal, another 14 percent end in default judgment, and only 5 percent ever reach trial. If you were trying to forecast the timeline of a newly filed case against him, the base expectation would not be a prolonged path to trial; it would be an earlier procedural resolution.
The next question to ask is what pushes his cases away from that baseline.
Looking across Smith’s longest-running cases reveals a familiar pattern. The delay usually isn’t driven by aggressive motion practice. In one collections matter, an otherwise uncontested default judgment took nearly three and a half years because the court twice continued the case management conference needed to process it. In a personal injury case, four trial continuances—some stipulated, some ex parte—extended the litigation to roughly three years before the parties settled. Different cases, different facts, but the same underlying mechanism: scheduling and case management, not sustained litigation conflict.
For litigation planning, the attorney’s broader docket provides two inputs: the path a case is most likely to take and the mechanisms that tend to push it off that path. Together, those patterns show both the case’s expected path and where additional time is most likely to enter it.
From elapsed time to explainable forecasts
Where the time goes becomes less mysterious when cases are examined in context. Individual dockets may appear idiosyncratic, but recurring patterns emerge across jurisdictions, courts, judges, attorneys, case types, and procedural events.
Trellis brings those patterns together from millions of state trial court records, turning historical docket activity into inputs for litigation planning. Whether you’re working in ChatGPT or Claude, the question is no longer simply how long is this case likely to last? but what is most likely to make it last that long?
Litigation will always involve waiting. The advantage is knowing what the expected path looks like—and which procedural events, judicial practices, and litigation behaviors are most likely to push a case off it.
FAQ
Start by examining the duration of comparable cases in the same court and practice area. Look beyond a single average: consider the range of outcomes, the procedural paths those cases followed, and the events that most often extended their timelines.
Trellis provides access to state trial court dockets that can be analyzed by court, case type, judge, and procedural event. Using Trellis, attorneys can establish a historical baseline and identify the sources of delay most relevant to a newly filed case.
Case-duration data is most useful when it can be filtered by both geography and case type. Statewide averages may obscure substantial differences among counties, while averages across all practice areas may combine cases that follow very different procedural paths.
Trellis organizes state trial court data by jurisdiction, court, and practice area, allowing attorneys to compare the historical duration of similar cases at the county level. Those results can serve as planning inputs for budgets, reserves, client expectations, and settlement strategy.
Compare the duration and outcomes of similar cases in each potential jurisdiction. The analysis should also examine what drives the differences, including court scheduling, motion practice, continuances, settlement timing, and the frequency with which cases reach trial.
Trellis allows attorneys to analyze comparable state trial court cases across states, counties, and courts. This makes it possible to incorporate historical timing and procedural patterns into a broader venue analysis.
Review the judge’s historical rulings on comparable motions, including grant rates, disposition types, and the time between filing and resolution. Consider those measures together; a high grant rate for one motion type does not, by itself, establish that the judge’s cases move faster or slower.
Trellis judicial analytics and underlying docket records allow attorneys to examine how individual state trial court judges have handled continuances, motions to compel, and other procedural matters across prior cases.
Analyze the duration of comparable cases assigned to the judge, ideally within the same practice area and court. Review both the typical timeline and the procedural events associated with the judge’s shortest- and longest-running cases.
Trellis enables attorneys to examine an assigned judge’s historical docket and compare case duration, outcomes, motion activity, and scheduling patterns. This can refine a general court-level estimate once the judge is known.
Grant rates can be calculated from a judge’s prior motion outcomes, but the analysis must distinguish granted, denied, partially granted, withdrawn, moot, and unresolved motions. It should also specify the motion type, court, practice area, and period studied.
Trellis compiles state trial court motion and ruling data into judge-level analytics, allowing attorneys to research grant rates for motions to compel and inspect the underlying cases behind the results.
Start with counsel’s broader state trial court record. Examine the types of clients and cases they handle, the jurisdictions in which they appear, their motion activity, and how their matters most often conclude.
Trellis attorney analytics bring those docket histories together, helping attorneys identify opposing counsel’s prior cases, practice patterns, and recorded outcomes without reviewing each court docket separately.
Classify counsel’s prior cases by outcome and compare the frequency of dismissals, settlements reflected in the docket, default judgments, dispositive rulings, and trials. Then examine when those outcomes occurred and which events tended to precede them.
Trellis allows attorneys to analyze outcomes across opposing counsel’s state trial court history. The resulting patterns can provide a baseline for evaluating the likely path of a current case, although they cannot predict how counsel will act in a particular matter.
Review continuance requests filed in comparable cases and distinguish stipulated requests from contested applications. Calculate the grant rate using motions with identifiable outcomes, then examine how much time granted continuances added to the underlying cases.
Trellis provides searchable state trial court motions, rulings, and docket activity, allowing attorneys to calculate court- or judge-specific continuance rates and verify the results against the underlying records.
Identify the relevant motion category, jurisdiction, judge, case type, and period. Separate motions that received a substantive decision from those that were withdrawn, became moot, or otherwise ended without a ruling.
Trellis structures state trial court motion data so attorneys can research grant rates for motions to compel, sanctions, stays, and other motion types. Users can then inspect the source dockets to understand the context behind the aggregate result.
Timeline analysis is built from docket entries, filings, rulings, hearings, case-management events, and recorded outcomes in state trial courts. Because these records are spread across many court systems and often use inconsistent formats, turning them into comparable data requires collection, normalization, and classification at scale. Traditional legal research platforms have historically centered on published opinions and cited authority rather than comprehensive trial court docket analytics.
Trellis collects and structures state trial court records so attorneys can search individual matters and analyze patterns across courts, judges, attorneys, motions, and case types. Coverage and record availability may vary by jurisdiction.
Begin with a defined set of comparable cases and document the jurisdiction, practice area, date range, sample size, and outcome criteria. Estimate the expected path of the case, identify events likely to add cost or time, and develop a range rather than a single completion date. The final estimate should state its assumptions and remain subject to revision as the case develops.
Trellis can supply the underlying state trial court data for that analysis, including comparable case durations, motion patterns, judge history, attorney history, and sources of docket delay. Connecting each planning assumption to historical cases makes the budget and timeline more transparent, explainable, and defensible.