The Front Door: Reading the Supreme Court’s Cert Tells

Want insight into the cert process? Using a modern dataset of paid petitions (2017–2024), this piece turns relists, pre-cert amici, calendar rhythms, and specialist lineups into practical odds.

Most people think the Supreme Court’s big moments happen at argument. They don’t. The decisive act for nearly every case is earlier and quieter: a secret vote on whether the Court will even hear it. That gateway vote—granted or denied “certiorari” (cert)—happens behind closed doors, guided by a short public rule and a long list of unwritten habits. Because the Court rarely explains those habits, even seasoned lawyers talk about cert in the language of hunches.

Here’s where Justice Harry Blackmun helps. During his years on the Court he kept meticulous private notes about the agenda-setting process, including what the Justices were inclined to do with incoming petitions. Take those notes as a credible window into how the Court thinks about cert, and they become a map for reading today’s tells. I’m using that map to frame a modern, data-driven look at what really moves a petition from the slush pile to the merits docket—leaning on Blackmun’s records as the historical backbone.

Several years ago, I co-authored a study that looked at the largest cert level Supreme Court dataset at the time and focused on some of the most important factors that impact cert grants. That study looked at data through 2015. This article looks at data starting at the beginning of 2017 and runs through petitions filed by the end of 2024. It looks at some of the same, but also at several different factors.

What is Examined?

First, I look at relisting, the practice of carrying a petition over to a later private conference. Instead of treating each relist as a simple plus or minus, I examine it as a curved signal: there appears to be a zone where a few relists mark a petition as ripening, while very short or very long strings often mean something else entirely—messy facts, disagreement over the question presented, or an effort to narrow the case. The graph you’ll see plots grant rates across relist “buckets” to show that pattern.

Second, I track pre-cert amicus briefs—the friends of the Court who file before the Justices decide whether to take the case. The key question is whether those briefs create momentum or merely certify that momentum already exists. Later in the article, a companion chart groups cases by the number of pre-cert amici and shows how the likelihood of review changes as that count climbs.

Third, I treat Supreme Court specialists as a two-sided feature, not a badge for petitioners alone. The analysis compares four matchups—no specialists, specialist only for the petitioner, specialist only for the opposition, and specialists on both sides—to see how each configuration lines up with the odds of a grant. A separate figure previews those four bins and the different trajectories they follow.

Because docket choices ebb and flow, I also model timing. One set of graphs shows how grant rates vary by month, another shows how filings themselves rise and fall over the calendar, and a third traces year-to-year shifts in both grants and petition volume. The point isn’t trivia about Court culture; it’s practical: your chances can change with the calendar, and planning around those rhythms can matter.

Finally, I preview a few interactions that practitioners actually debate. Do extra relists help or hurt when both sides are represented by specialists? Do dense amicus coalitions substitute for specialists—or amplify them? And do the calendar rhythms blunt or boost those signals? The article tests those questions with the same dataset and presents them visually, alongside simple, calibrated probabilities that translate the signals into odds.

If Blackmun’s certiorari notes show anything, it’s that the screening stage has patterns—even if the Court doesn’t publish them. The sections that follow aim to surface those patterns with clear visuals and explanations: when to file, when to oppose, when to invite another relist, when to recruit support, and when to let a weak vehicle go.

The Data

Here’s where we leave the vantage point of chambers and look at the pile itself. On the first Monday of October 1992, Blackmun scrawled a weary but familiar note in green pencil—“OT 1992—here we go again”—as another year’s worth of petitions rolled toward the Long Conference. That annual ritual is still the heart of the modern cert machine. To study it honestly, I built the dataset around the part of the docket that actually feeds most grants: the paid petitions.

A quick word on definitions. Every cert petition is either paid (filed with the fee, typically by represented parties) or in forma pauperis (IFP)—filed without a fee by indigent litigants, often pro se prisoners challenging criminal convictions or prison conditions. IFP filings make up the bulk of incoming cert petitions numerically, but they are granted far less often: many raise fact-bound or vehicle-poor issues, lack clean conflicts, or present questions the Court has repeatedly declined to revisit. Paid petitions, by contrast, are where Rule 10 showings most often appear, where amicus coalitions tend to form, and where the Justices most frequently find clean vehicles for nationwide rulings.

The analysis that follows therefore focuses on more than 12,300 paid petitions filed from 2017 through the end of 2024, excluding IFP filings by design. That focus does two things. First, it keeps the signal-to-noise ratio high by studying the petitions that realistically contend for limited merits slots. Second, it zeros in on the levers attorneys can actually pull—timing, counsel lineup, coalition building, and how to manage (or resist) relists—without mixing in a mass of pro se cases that follow a very different path to almost-certain denial.

With that scope set, the figures walk through the story the way a clerk or advocate experiences it. It starts wide—how many petitions arrive and how many get in each year—then map the Court’s calendar rhythm month by month. From there, it turns to the three operative “tells” you can act on: what relists really mean (and when they stop helping), how pre-cert amici function as momentum rather than decoration, and why the configuration of Supreme Court specialists on each side changes the odds. It then puts those signals in one frame to show which levers buy the most probability, and close with a quick check that the signals aren’t just proxies for each other.

Petitions Filed per Year

Annual filing totals put the whole period in context. Big swings change the denominator of the grant rate and can push the Court to rely more heavily on relists and other aspects for quality control. This bar chart is the macro backdrop for everything in the article.

We can also see the change in yearly grant rates below (I removed GVRs or granted, vacated, and remanded petitions from this analysis to avoid conflating grant rates).

While the averages generally hover in the mid 4% range, there was a clear drop off in 2021 and the rates went over 5% in both 2019 and 2024.

Average Petitions Filed per Month

This figure is the supply side of seasonality. It shows how many petitions hit the docket each month, which in turn shapes what the Long Conference must process and how crowded the fall pipeline becomes. Use it to understand whether a given month’s grant rate is a function of appetite or crowding—or both.

Filings ramp up from late spring into fall, peaking around September–November. That peak aligns with the Long Conference’s heavy lift and helps explain why grant rates can be strong in early fall even as volume surges: the Court must stock a merits calendar quickly. For filers, this can cut both ways: you’re in a bigger crowd, but the Court needs viable cases. A crisp petition with a clean split and no vehicle hair can benefit from that stocking pressure. In a crowded month, clarity wins.

Grant Rates by Relist Counts

Relisting is the Court’s most visible, day-to-day tell during the cert stage. When the Justices “relist” a petition, they carry it to a later private conference rather than resolve it immediately. The outside world can see this because the case keeps reappearing on the discussion list. Practitioners often assume that “more relists” equal “better odds,” but that treats relisting like a linear throttle when it behaves more like a ripening curve. This figure groups petitions by adjusted relist counts—normalizing for housekeeping moves like administrative reschedules—so we can see whether there’s a zone where a petition looks ready to grant, and whether very short or very long strings of relists tend to mean something else (e.g., a vehicle problem the Justices are trying to fix, a push to narrow the question presented, or simply unresolved internal disagreement). Read the bars left to right as the Court’s patience curve: how many passes at Conference typically signal momentum versus friction.

The climb from zero to a small number of relists is steep—the petition moves from almost no chance to genuinely live. From there, the odds crest in the 3–4 relist “sweet spot,” then decline for longer runs. That decline is the practical takeaway. If you’re the petitioner and you’re past the fourth relist, you may assume the Justices are wrestling with a defect (for example vehicle messiness, a split that isn’t square, or an ill-posed Question Presented (QP)). From the opposition side, the same curve counsels patience: past the sweet spot, the marginal value of another relist gets you less, not more. Either way, the figure reframes a common myth: relists are information, not a trophy count.

Grant Rates by Number of Pre-Cert Amicus Briefs

Pre-cert amici are a classic way to signal that a case has national stakes, a mature split, or both. But the Court has seen amicus inflation before, so the real question is whether additional briefs create momentum or merely document it. This bar chart buckets cases by amicus counts and tracks how the odds change across thresholds. Look for step-ups rather than a straight line—those steps are what you can aim for when you’re building a coalition on the clock.

The pattern is monotonic and stair-stepped: each bucket up is associated with a higher grant rate, but the steps get smaller as the count climbs. Translation: three or four well-targeted briefs often buy more than a dozen repetitive ones. For petitioners, that means curating credible voices that cover different angles—doctrine, industry reliance, government impact—rather than collecting signatures. The figure turns a mushy question—“How many amici is enough?”—into a realistic target.

Grant Rates by Elite Petitioner and Opposition Attorney Combinations

Supreme Court specialists change the way petitions read. They trim the QP, anticipate obstacles, and, frankly, signal that the parties think the case is grant-worthy. But the effect is not symmetric across sides, and it’s not all or nothing. This figure compares four matchups—no specialists, petitioner-only specialist, opposition-only specialist, and specialists on both sides—so we can see how each configuration aligns with the odds of review. Specialists were designated based on Chambers & Partners Star Individuals and Band 1 Attorneys. Think of it as a matrix for deciding whether, when, and how to bring in a specialist.

“No specialist” cases rarely get in—unsurprising, but useful as a baseline. More interesting: elite opposition counsel on its own corresponds to a bigger lift than elite petitioner counsel on its own, and both-sides elite is the strongest of all. The asymmetry supports a practical rule of thumb: if cert is plausible and you’re opposing, strong opposition counsel may signal case importance in a way that actually persuades the Court to grant the petition. If you’re the petitioner, a specialist helps—but you’ll still need a clean vehicle and a square split to cash it in. And when both sides are elite, the Court appears more comfortable granting: the case will likely be well-presented and opinions easier to craft. That’s selection, yes—but it’s also a real screen the Court uses.

Marginal Effects on Cert Grant Probability

Different signals don’t operate in a vacuum. This horizontal bar chart shows average marginal effects from a unified model: how much each factor changes the probability of a grant when the others are held constant. That “all-else-equal” perspective matters because many cert tells travel together (e.g., strong cases attract amici and specialists and multiple relists). The error bars are 95% confidence intervals, so you can eyeball which effects are both large and precise. Use this figure to compare the practical lift from things you can influence (amicus recruiting, counsel lineup) versus things you can only partially steer (relist posture).

Four levers consistently move the needle: three-plus relists, elite opposition counsel, elite petitioner counsel, and three-plus pre-cert amici. Amicus lift exists but is smaller and steadier—useful as confirmation of importance and to frame stakes, but not a substitute for other important aspects surrounding the case. Attorneys can treat this plot as a budget tool: if you can’t pull every lever, this ranking tells you which ones tend to buy the most probability.

Pairwise Correlations Among Key Cert Signals

To understand the relative importance of these factors, you want to know whether the predictors are just measuring the same thing. This table reports simple pairwise correlations among the headline features: multiple relists, pre-cert amici, and elite counsel on each side. Low correlations mean each signal contains independent information; high correlations would warn that one variable is a proxy for another.

The correlations are small, topping out around 0.23. That’s good news: relists, amici, and counsel appear to capture distinct slices of the Court’s screening process. It also means the marginal effects in the prior graph aren’t artifacts of one variable standing in for another. For practitioners, this answers a common worry: “If we bring in a specialist, do we still need amici?” The short answer is yes—because these signals don’t collapse into each other. Each adds its own piece to the story the Court is reading.

Final Thoughts

The cert stage isn’t a mystery so much as a quiet market with readable signals. By isolating the paid docket and watching how relists, amici, counsel, and the calendar actually behave, you get a map of where probability lives—and where it dies. That matters because Supreme Court strategy is mostly resource allocation under scarcity: when to spend credibility, when to bring in reinforcements, and when to stop pushing a weak vehicle.

For petitioners, the playbook is straightforward. Use targeted pre-cert amici to confirm stakes rather than to wallpaper over defects. If you add a specialist, make the presence of elite opposition part of the plan, not an afterthought; the Court seems most comfortable granting when both sides can carry the load. Above all, fix vehicle hair early. If the case needs narrowing, do it yourself before the Court does it for you—or before a run of relists turns into a slow “no.”

For respondents, the data justify a different posture. Elite opposition counsel may be beneficial for crafting a strong argument but can also lead to higher grant odds. If the case is genuinely grant-prone, elite opposition counsel is a force multiplier: it helps shape the relist arc and signals case importance.

Seasonality is not trivia. Filing and extension choices that position a petition for decision during higher-yield windows can meaningfully change the odds, and so can pacing that avoids getting trapped in the troughs. Treat timing as a strategic variable, not an accident of the calendar.

None of this proves causation; selection effects are real, and the Court will always keep some habits behind the curtain. But these patterns are stable enough to replace folklore with planning. The signals don’t collapse into one another, and their combined use beats any single lever.

Cert is rationing under secrecy, but it’s not random. Read the tells, budget for the levers that actually move probability, and be willing to pivot when the relist curve turns against you. Strategy at the Supreme Court isn’t about confidence; it’s about calibration.

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