Snow Day Stats is an independent educational website about school closures: how districts decide to call one, how closure predictions are built, and why those two things so often disagree.
We are not an alert service, and we do not announce closures. We explain the system behind them.
The site sits where three subjects overlap. The first is winter weather forecasting, including what a snowfall range actually means and why a probability is not a promise. The second is school district operations: bus routes, road crews, staffing, and the written policies sitting behind a 5 a.m. phone call. The third is school calendar policy, which determines what a closure costs a district in March, long after the snow has melted.
Our aim is straightforward. When you understand the inputs a superintendent is working with, you can read a storm the way they read it. You can also judge any prediction on its merits, including ours.
Who Is Mateo Elias?
Mateo Elias is the founder, primary writer, and editor of Snow Day Stats. Every article here is written or reviewed by him, and he is the person accountable for what appears on this site.
The project began with a small frustration. A popular snow day calculator showed a 92 percent chance of closure. School opened on time. The forecast had not been wrong in any obvious way, so something else was going on. The answer, it turned out, was not in the weather at all. It was in the district's own operating rules and in the hour the snow arrived.
That question turned into a habit, and the habit turned into a site. Mateo now spends his winters doing fairly unglamorous work: reading district policy handbooks and school board minutes, saving closure announcements before they scroll off a district's social feed, matching those announcements to archived National Weather Service products, and keeping a record of what was predicted against what actually happened.
He is a researcher and writer rather than a forecaster, and he is careful about that distinction. Snow Day Stats does not issue weather forecasts and does not compete with the meteorologists who do. Its contribution is elsewhere: connecting the forecast to the decision, and showing the reader where the seams are.
That commitment shapes how the writing works. Claims are traced to a source you can check. Where the evidence is thin, the article says so. Where district practice varies, the article shows the variation instead of averaging it away. And where a previous post got something wrong, it gets corrected rather than quietly buried.
Why Snow Day Stats Exists
Conversations about snow days tend to collapse into one of two extremes.
At one end sits prediction hype. A number appears on a screen, often with no explanation of what went into it, and readers treat it as a forecast of their own morning. When the number is high and school opens anyway, the tool looks broken and the reader feels misled. Neither reaction is quite fair, because the number was never doing what people assumed it was doing.
At the other end sits flat dismissal. In this telling, closures are a coin flip, superintendents decide on a whim, and the only sensible thing is to wait for the robocall. This is more comfortable, and it is also wrong. Closure decisions are among the most rule-bound calls a district makes. Many districts have a written wind chill threshold. Most have a documented decision window and a chain of people who get consulted in a fixed order. Very little of it is improvised.
Snow Day Stats occupies the space between those positions. School closure decisions are patterned and partly predictable, because they follow documented rules and repeat across seasons. They are also genuinely uncertain, because they are made by people under time pressure, with incomplete information, at four in the morning. Both statements are true at once. Good analysis has to hold them together.
Local context matters just as much. The same two inches of snow means something very different in northern Minnesota than it does in northern Georgia, and not because of the snow. It is the number of plows, the age of the bus fleet, how many students walk, how many ride down unpaved hills, how many rely on a school breakfast, and how many families have no childcare option if school closes. A district is not only reacting to weather. It is reacting to its own community.
We do not tell readers what to conclude. We show the rules, the records, and the reasoning, and we trust readers to work out how their own district behaves.
What We Cover
1. Closure Forecasting and Prediction Accuracy
This is where we examine the prediction tools themselves: what goes into a snow day calculator, what its output actually represents, and why a high percentage and an open school are not necessarily a contradiction. We look at why a forecast of "3 to 6 inches" is a statement about uncertainty rather than a quiet way of saying 4.5 inches, and why that difference changes the decision. We also cover the limits of geography-based prediction, including the problem faced by any district that spans two ridgelines and cannot be described by a single ZIP code.
Alongside this, we document our own methods. That includes where district closure announcements are archived, how we log them, and what our records can and cannot support. The perspective throughout is evaluative and statistical: we test predictions against outcomes rather than defending or attacking any particular tool.
2. Reading Winter Weather the Way a District Does
Districts do not read a forecast the way a commuter does. Timing often matters more than totals, which is why a small overnight accumulation can close a district while a larger midday snowfall does not. Precipitation type matters even more. A quarter inch of freezing rain creates a very different problem for a bus fleet than several inches of dry snow, and we look closely at why.
We also cover the gap between official weather alerts and district action, including why a Winter Storm Warning can be in effect while school runs a normal day. This section is educational and practical. The goal is forecast literacy, so that readers can look at the same information a district sees and understand which parts of it drive the call.
3. How District Decisions Get Made
This pillar follows the decision itself. We walk through what typically happens between roughly 3:30 and 5:30 a.m., when road crews report in, transportation directors drive routes, and neighboring superintendents compare notes before anyone announces anything. We look at the written thresholds that sit underneath those conversations, particularly wind chill cutoffs, which are far more often documented in board policy than parents realize.
We also examine the cases that puzzle people most: two districts in the same county making opposite calls on the same storm, and districts closing on a morning when the roads look perfectly clear. Both usually have explanations rooted in staffing, bus logistics, forecast timing, or liability rather than in the road surface itself. The perspective here is procedural and documentary, drawn from policy manuals, board minutes, and district communications.
4. Delays, Remote Days, and What Counts as Attendance
A closure is not the only outcome, and a delay is not always a stable one. We track how often a two-hour delay is later converted into a full cancellation, and what conditions tend to precede that reversal. We also cover the growing category of days that are neither open nor off: remote instruction days, asynchronous work, and the attendance rules that decide whether such a day counts toward a state's required instructional time.
This section is policy-oriented and increasingly consequential, because the answer determines whether a "snow day" is a day off at all.
5. Calendars, Makeup Days, and What a Closure Costs
Every closure has a bill attached, and it usually comes due in spring. Here we explain built-in inclement weather days, the point at which a district exhausts them, and what happens next: extended school days, shortened breaks, a later end to the year, or a waiver request to the state. We look at how many closures it typically takes before a district starts taking days back, and how state instructional-hour requirements shape that math.
The perspective is administrative and long-range. It is the part of the story that is invisible in January and impossible to ignore in May.
Our Editorial Approach
- Plain language first. Technical accuracy does not require technical vocabulary. We define terms like wind chill advisory, instructional hour, and probability of closure the first time they appear.
- Primary sources wherever possible. We work from district policy documents, board meeting minutes, state statutes and education codes, official district announcements, and archived National Weather Service products rather than from secondhand summaries.
- Context before conclusions. Closure practices differ by region, climate, district size, and budget, and they have changed considerably over the past two decades. We provide that background rather than presenting one district's practice as a national norm.
- A clear line between fact, estimate, and tradition. Documented policy is labeled as documented policy. Our own analysis is labeled as analysis, with its method and limits stated. Folklore, from pajamas worn inside out to spoons under pillows, is presented as culture, not causation.
- Visible methods. When we publish a figure, we say where the underlying records came from, what seasons and districts they cover, and how many observations sit behind it.
- No manufactured certainty. We avoid dramatic framing, absolute predictions, and headlines that promise more confidence than the evidence supports. When we do not know something, the article says so.
- Errors get corrected, openly. Accuracy is a process rather than a one-time claim.
Use of Digital Tools
Producing this site involves a range of digital tools. Spreadsheets and small scripts help organize closure records. Archived weather data is retrieved programmatically. AI-assisted tools are sometimes used to help structure research notes, check readability, tidy formatting, or suggest alternative phrasing during drafting.
These tools assist the work; they do not perform it, and they do not determine what is true. Every factual claim, figure, policy citation, and conclusion published here is verified against its original source and reviewed by Mateo Elias before publication. Editorial judgment, accuracy, and responsibility rest entirely with him. If something on this site is wrong, the error is ours to own and ours to fix.
Editorial Independence
Snow Day Stats is produced independently. Our coverage is not shaped by advertisers, sponsors, or commercial partners, and no outside party reviews or approves articles before they are published.
We are not affiliated with the National Weather Service, with any school district or state education agency, or with any commercial snow day prediction service, including any tool we happen to analyze. Where a page carries advertising or affiliate links, that relationship is disclosed and kept entirely separate from editorial decisions. No sponsor has ever been given the ability to add, alter, soften, or remove a finding, and none ever will.
Corrections and Updates
If we publish something inaccurate, we correct it. Substantive corrections are made directly in the article and accompanied by a dated note explaining what changed, so the record stays honest rather than tidy.
Winter policy is also a moving target. Districts revise thresholds, states amend instructional-time rules, and remote learning provisions change from one legislative session to the next. Articles covering active policy are reviewed ahead of each winter season and updated where the underlying rules have shifted.
Reader corrections are genuinely welcome, and some of the most useful ones come from people inside the system: superintendents, transportation directors, bus drivers, teachers, and district communications staff. If you can point us to a document, a policy, or a record that contradicts something we have written, we would like to see it.
A Note for Readers, and a Disclaimer
This site is written for a wide audience. Parents timing their morning, students running the numbers, teachers and administrators comparing their district to others, weather enthusiasts, data-minded skeptics, and readers in climates where snow closes schools twice a decade rather than twice a month. You do not need a background in meteorology or education policy to follow anything here.
We would rather you think than agree. Check our sources, look up your own district's policy documents, keep your own record of what happened this winter, and push back when your local experience does not match what we have written. Curiosity is the point.
Disclaimer. Snow Day Stats is an educational and informational website. It is not an official source of school closure information, and it does not announce, confirm, or predict closures for any specific school or district. Always confirm closures, delays, and schedule changes through your district's official channels. Any predictions, estimates, or probabilities discussed here are analytical exercises and should never be treated as guarantees or used as the basis for travel, safety, or attendance decisions. For weather safety and road conditions, rely on the National Weather Service and your local emergency management and transportation authorities. Nothing on this site constitutes professional medical, legal, financial, educational, or mental health advice. For guidance on your specific situation, please consult a qualified professional.
Come In From the Cold
Every closure is a decision before it is an announcement. Someone read a forecast, drove a route, checked a policy, and made a call while most of the district was asleep. Snow Day Stats is here to make that process visible, one storm at a time.
If you have a question, a correction, a district policy document worth examining, or a story about a morning that did not go the way anyone predicted, we would like to hear it. Reach us through our contact page
Thank you for reading, and enjoy the snow when it comes.
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