Beginner
What Can You Trade on with Prediction Markets?
The practical guide to prediction market categories, with examples and the rules-based limits that shape them - plus the boundaries you should know before you trade.
This guide is for educational purposes, not legal advice. U.S. rules and enforcement positions can evolve, and availability may vary by state.
Before trading, you should review the rules that apply in your jurisdiction and confirm that any platform you use is authorized to operate in the United States.
This guide will explain:
- Which categories are commonly available on regulated prediction markets, and what each category typically includes
- What you can trade on, category by category with concrete examples so you can recognize them quickly
- What regulated platforms usually restrict or avoid, and why those topics trigger scrutiny
- How to spot markets you personally should not trade, even if they are listed, because of conflicts or non-public information
What can you trade on with prediction markets?
Prediction markets let you trade on real-world outcomes that can be checked after the fact. The key constraint on regulated U.S. platforms is not whether a topic is interesting. It’s whether the outcome can be defined clearly, verified objectively, and settled using a named source in a way that leaves as little room for interpretation as possible.
That’s why you’ll see deep coverage in categories like economics, politics, policy, weather, and culture - and much more selective coverage in categories that create obvious public-interest, safety, or gaming concerns. Availability can also change over time as platforms adjust what they list and how they write their rules.
Sports Prediction Markets
Sports prediction markets are built around what fans argue about nonstop: who wins, who advances, and who hits key milestones. They let you take a position on outcomes tied to games, seasons, and player performance - everything from tonight’s winner to long-range futures like playoff spots and championship runs.
They also solve a very practical problem: not everyone lives in a state with legal online sports betting. For those users, sports prediction markets can be one of the only ways to put real money behind a sports opinion without using an offshore sportsbook. Even in legal betting states, some people prefer the market-style format because prices can move faster and reflect the crowd’s view in real time.
Sports markets move quickly because the information cycle is nonstop - injuries, rotations, weather, travel, and late-breaking reports can swing probabilities in minutes. Expect the most action around major events, especially NFL Sundays, playoff series, and marquee matchups where news and attention hit peak levels.
Common Sports Prediction Market Types
These markets settle on the winner of a specific matchup. On regulated venues, the rules typically spell out what counts as a win if the game is postponed, suspended, or ends differently than expected (for example, extra time, shootouts, overtime).
Real-life examples:
- Kansas City Chiefs defeat the Buffalo Bills
- Los Angeles Lakers defeat the Boston Celtics
- Manchester City defeat Liverpool
These markets settle on a season-end achievement like winning a title, finishing first, or qualifying for playoffs. They’re popular because the league publishes official standings and champions, so settlement is usually clean.
Real-life examples:
- Kansas City Chiefs win the Super Bowl
- Los Angeles Dodgers win the World Series
- Barcelona win La Liga
These markets settle on who wins a multi-game series (playoffs are the classic use case). They work well because the series format is defined in advance and the league declares an official winner.
Real-life examples:
- Boston Celtics win an NBA playoff series against the Miami Heat
- New York Rangers win a Stanley Cup playoff series against the New Jersey Devils
- Houston Astros win an MLB playoff series against the New York Yankees
These markets settle on whether a named player or team hits a stat milestone in a game or over a defined span. The key is that the contract should name the official stats source (league box score) and how corrections are handled.
Real-life examples:
- LeBron James records a triple-double
- Patrick Mahomes throws 3 or more passing touchdowns
- Shohei Ohtani hits a home run
These markets settle on the winner of a defined competition that ends with an official champion. This includes brackets, cups, majors, and single-elimination tournaments.
Real-life examples:
- Winner of the NCAA men’s basketball tournament
- Winner of the UEFA Champions League
- Winner of the Masters Tournament
Are Sports Prediction Markets Just Sports Betting With Extra Steps?
At a glance, sports prediction markets and sportsbooks look similar. In both cases, you’re taking a position on a game, a season outcome, or a player milestone and hoping you’re right.
The difference is structural. A sportsbook sets odds and takes the other side of your wager. A prediction market runs as an exchange, where prices move based on supply and demand between traders. One is house-driven pricing. The other is market-driven pricing.
Legally, that structural difference is exactly why sports prediction markets exist in the first place - and why they’re now being challenged in court. Some states and sportsbook operators argue they function too much like traditional betting, while Prediction Markets. For now, federally regulated sports event contracts remain active, but the landscape is evolving.
Politics and Elections
Politics and election markets cover outcomes tied to elections, nominations, party control, and political milestones that can be verified through official results. This category attracts attention because it’s naturally binary, highly followed, and full of dates and deadlines. It also tends to be one of the most scrutinized categories in the U.S., so on regulated platforms you’ll often see tighter rule-writing and more careful selection of what gets listed.
For a trader, the practical distinction is between markets that resolve off official election outcomes and markets that resolve off political process events (like whether a candidate is the nominee by a specific date). The second type can be perfectly legitimate, but it is more sensitive to rule wording. If the rules don’t specify exactly what counts as the milestone and who confirms it, you can end up with a market that feels obvious until the edge case happens.
Common Types of Politics Prediction Markets
These settle on who wins a specific race as officially recorded. The cleanest versions settle on certified results rather than election-night projections.
Examples:
- Winner of the US presidential election
- Winner of the California governor election
- Winner of the New York City mayoral election
These settle on which party controls a legislative body after official outcomes are determined (and rules should specify what counts as control).
Examples:
- Which party controls the US House after the midterms
- Which party controls the US Senate after the election
- Which party controls the UK House of Commons after a general election
These settle on who becomes the official nominee under party rules, usually by a convention milestone or formal certification.
Examples:
- The Democratic nominee for US president
- The Republican nominee for US Senate
- Winner of a party leadership vote (for example, UK Conservative Party leader)
These settle on whether a candidate appears on the ballot under official rules in a jurisdiction. Great markets here specify the authority and the deadline.
Examples:
- A third-party candidate appears on the ballot in Texas for president
- A specific candidate appears on the ballot for New York governor
- A named independent appears on the ballot in a named state for US Senate
These settle on whether a political process event happens by a date. The key is that the event must be verifiable and defined.
Examples:
- The US Senate holds a confirmation vote on a named nominee by a deadline
- Congress passes a continuing resolution to fund the government before a shutdown deadline
- A state certifies election results by a specified date
Economics and Macro Data
Economics and macro markets focus on scheduled, widely reported releases and central bank decisions that shape everything from borrowing costs to consumer prices.
'In practice, this category covers inflation, jobs data, growth, and interest-rate policy. It’s common on regulated platforms because settlement can usually be anchored to a specific published number (with a clear timestamp and source), which reduces disputes about what happened.
These markets are also approachable for a new trader because the calendar is predictable. Many of the biggest events repeat monthly or quarterly, and major central bank meetings are scheduled in advance. That gives you a clean way to express views like inflation is cooling, the labor market is weakening, or rates will stay higher for longer, without needing to predict every second-order effect in stocks or crypto.
The main thing to watch is how precisely the market is defined, especially when revisions or multiple versions of a statistic exist.
Common Types of Economics Prediction Markets
These settle on whether a single published number is above or below a line. The line is the whole game: you’re trading the probability the number prints on one side of it.
Examples:
- US CPI year-over-year is at least 3.0% on the next Bureau of Labor Statistics release
- US unemployment rate is below 4.0% on the next BLS jobs report
- Eurozone inflation (HICP) is above 2.5% on the next Eurostat release
Instead of above/below, the outcome is whether the number lands inside a band. This is useful when you don’t have a strong directional view but have a view on how extreme the result will be.
Examples:
- US CPI year-over-year falls between 2.5% and 3.0% on the next release
- US nonfarm payrolls are between 150k and 250k on the next jobs report
- UK CPI is between 3.0% and 3.5% on the next Office for National Statistics release
These settle on an official decision from a named body on a known date. Most commonly: central banks. These are popular because the event is discrete and publicly confirmed.
Examples:
- The Federal Reserve holds rates at the next FOMC meeting
- The European Central Bank cuts its key rate at the next Governing Council meeting
- The Bank of England raises Bank Rate at the next MPC decision
These settle on whether something happens by a deadline. In economics, these work best when the milestone is precisely defined (not interpretive).
Examples:
- The NBER Business Cycle Dating Committee announces a recession start date by a certain deadline
- The US Treasury’s cash balance falls below a defined threshold by a date (if the market specifies the exact published source)
- Inflation falls below a defined level by year-end using a specific CPI series
These settle on how many times something happens within a window. In macro, the classic form is counting rate moves across meetings.
Examples:
- Number of Fed rate cuts in the next calendar year
- Number of ECB rate changes between now and a specified meeting
- Number of months US CPI prints above 0.3% month-over-month in a defined period
These settle on whether a number moves up or down compared with a reference value, usually the prior print.
Examples:
- US unemployment rate is higher than last month on the next release
- US CPI year-over-year is lower than last month on the next release
- US GDP growth is higher than the prior quarter on the next BEA report
Courts and Legal Decisions
Court and legal-decision markets cover outcomes tied to formal rulings and case milestones. These can be some of the most useful markets when a major case has clear, widely followed endpoints, because the outcome is typically confirmed by an official court action. They can also be some of the easiest to misunderstand if the market is written too loosely, since legal processes have multiple stages and results can be narrow even when headlines make them sound sweeping.
For beginners, the most important habit in this category is to treat every contract as a question about a specific procedural fact, not as a vibe about who is right. A market might settle on whether a court grants a stay, whether a case is accepted for review, whether an injunction is issued, or whether a final judgment is entered by a certain date. Those are verifiable events.
What gets tricky is when contracts try to capture what a decision means, rather than what the court actually did.
Common Types of Legal Decision Prediction Markets
These settle on whether a higher court accepts a case (for example, grants certiorari). The rules should specify the exact docket and action.
Examples:
- US Supreme Court grants certiorari in a named case
- A federal appeals court agrees to hear an en banc rehearing
- A state supreme court agrees to hear a high-profile appeal
These settle on temporary or preliminary court actions, which are often the real “swing” points in litigation.
Examples:
- A federal court issues a nationwide injunction blocking a rule
- The Supreme Court grants a stay pending appeal
- A judge grants a temporary restraining order in a named case
These settle on whether a court issues a ruling by a deadline (often end of term or before a scheduled date).
Examples:
- The US Supreme Court issues a decision in a named case by the end of the term
- A court rules on a motion to dismiss by a certain date
- A court issues a final order before a compliance deadline
These settle on the formal disposition: affirmed, reversed, vacated, remanded — but only when the market defines these clearly and ties them to the controlling judgment.
Examples:
- Supreme Court reverses a named circuit court decision
- A federal appeals court vacates a rule and remands it to the agency
- A state supreme court affirms a lower court ruling in a named dispute
These settle on whether a specific procedural event happens: oral arguments held, filings made, judgments entered.
Examples:
- Supreme Court hears oral arguments in a named case
- A court enters final judgment by a deadline
- A prosecutor files formal charges in a named case by a date (when anchored to official records)
Weather and Natural Events Prediction Markets
Weather and natural event markets focus on outcomes tied to measurable environmental conditions and official storm reporting.
They can be some of the cleanest markets on regulated platforms when they’re anchored to a specific metric, location, and reporting station or agency definition. They’re also a category where beginners often underestimate how precise the rules need to be. Weather is messy in real life, so a good contract has to be exact about what counts.
What makes this category useful is that it lets you trade on events that have clear seasonality and clear timestamps. If you follow a hurricane season, a snow forecast, or heat waves that affect energy demand, these markets can be a straightforward way to express a view without needing to model every downstream consequence. The best-designed weather markets settle off a single, named source that publishes the result in a consistent way.
Common Types of Weather Prediction Markets
These settle on a specific reading from a defined station/authority. Good markets specify location, station, and time window.
Examples:
- High temperature in Phoenix reaches at least 110°F on a specific date (using NOAA station data)
- New York City’s Central Park station records a low at or below 20°F in a defined window
- Miami records a high above 95°F on a specified day
These settle on accumulation, which means the rules must define the measurement station and window.
Examples:
- Snowfall at Boston Logan Airport is at least 6 inches in a defined 24-hour window
- Rainfall in Los Angeles exceeds 1 inch over a weekend window
- Total precipitation in Seattle exceeds a defined threshold over a week
These settle on whether a named storm reaches a category or status by a date, typically using official hurricane center classifications.
Examples:
- A named Atlantic storm becomes a hurricane (Category 1+) by a deadline
- An Atlantic storm reaches Category 3+ by a deadline
- The National Hurricane Center names at least one storm by a certain early-season date
These settle on cumulative totals over a season at a specified station/location.
Examples:
- Seasonal snowfall total for Denver exceeds 50 inches
- Seasonal rainfall total for Miami exceeds a threshold
- Total named storms in the Atlantic hurricane season exceeds a number
These settle on whether a defined event occurs, but the definition has to be objective (for example, an NHC designation, a NOAA classification, etc.).
Examples:
- A hurricane makes landfall in Florida as defined by the National Hurricane Center
- A heat advisory is issued for a named county by the National Weather Service
- A tropical storm warning is issued for a defined coastal area
Government Policy and Regulation
Policy and regulation markets cover outcomes tied to government actions: agency rules, deadlines, program decisions, executive actions, and legislative milestones. This category is powerful because policy moves can reshape entire industries, and markets let you take a view on whether something will actually happen, not just whether people will talk about it.
The catch is that policy outcomes can be messy if the market tries to capture something too broad. The strongest markets in this category are the ones that pin settlement to a clean event like a specific bill being enacted, a rule being published in a specific venue, or a deadline being met under a named program. The weakest ones are framed around intent, direction, or tone, because those are harder to verify and easier to dispute.
Common Types of Government Policy and Regulation Prediction Markets
These settle on whether a bill clears a defined step: passed one chamber, passed both, signed, or becomes law.
Examples:
- The US Congress passes a government funding bill before a shutdown deadline
- The US Senate passes a major FAA reauthorization bill by a deadline
- A state legislature passes a recreational cannabis legalization bill by a deadline
These settle on whether an agency issues, delays, withdraws, or finalizes a rule - usually anchored to official publication.
Examples:
- The US EPA issues a final vehicle emissions rule by a deadline
- The SEC finalizes a specific market structure rule by a deadline
- The FDA grants full approval for a named drug indication by a deadline (when tied to a formal action)
These settle on changes to named government programs, when the decision is formal and documented.
Examples:
- The US Department of Education announces a defined student loan repayment change by a deadline
- CMS finalizes a Medicare reimbursement rule for a named program year
- DHS ends or extends a specific temporary status program by a deadline
These settle on whether the government meets or misses an explicit deadline (statutory or formally announced).
Examples:
- Congress extends government funding before the current funding expires
- The US government hits the debt ceiling without suspension before a deadline
- A federal agency publishes guidance by a date stated in the Federal Register timeline
These settle on whether a funding event happens (shutdown, extension, appropriations package) with the event precisely defined.
Examples:
- The US government enters a shutdown because funding lapses
- Congress passes a continuing resolution to keep funding in place
- A full-year appropriations package is signed into law
Entertainment and Culture Prediction Markets
Entertainment and culture markets cover outcomes tied to awards, releases, and measurable public signals like charts or rankings. This category tends to be popular because it blends events that are widely followed with outcomes that can be settled using clear, published results.
It can also be a category where headline interpretation gets people in trouble. The contract is not about what you think should win - it’s about what the official source says happened.
For beginners, entertainment markets are a good place to learn how rule-writing matters, because the resolution often depends on a single institution or publication. If the rules clearly specify the awarding body, chart provider, or published ranking, settlement is usually straightforward.
Common Types of Entertainment Prediction Markets
These settle on an official award result from a specific body.
Examples:
- Best Picture winner at the Academy Awards
- Album of the Year winner at the Grammys
- Ballon d’Or winner
These settle on who receives nominations, not who wins. The authority is the nominators list.
Examples:
- Oscar nominees for Best Actor include a named person
- Grammy nominations for Record of the Year include a named song
- Emmy nominations include a named show in a category
These settle on whether something reaches a chart position using a named chart provider.
Examples:
- A song reaches No. 1 on the Billboard Hot 100
- An album debuts in the Top 3 on the Billboard 200
- A track reaches No. 1 on the UK Official Singles Chart
These settle on whether a release happens by a deadline, but the rule must define what counts as released.
Examples:
- Grand Theft Auto VI releases by a deadline
- A Marvel Studios film releases in theaters by a deadline
- A named Apple product launches by a deadline (for example, new iPhone model)
These settle on reported revenue numbers from a named source with a defined window (opening weekend, worldwide gross, etc.).
Examples:
- A named film earns over $100M domestic opening weekend
- A named film crosses $1B worldwide gross
- A named film’s opening weekend exceeds a defined threshold by Comscore reporting
These markets settle on a published review aggregate score from a named ratings source, measured at a defined cutoff time.
Many of these markets will use sites like Rotten Tomatoes or Metacritic and reference the percentage of professional critic reviews that are positive. Some markets may also reference audience-based scores, including Rotten Tomatoes’ Verified Audience Score built from ticket-verified ratings.
Examples:
- A named film’s Rotten Tomatoes Tomatometer is 70% or higher by end of opening weekend
- A named film’s Tomatometer is “Fresh” (60%+) once it reaches 50 critic reviews
- A named film’s Verified Audience Score is 90% or higher by Monday after opening weekend
- A named film’s Metacritic Metascore is 75 or higher within 7 days of wide release
Business and Companies
Business and company markets cover outcomes tied to corporate actions and measurable company milestones. This can include things like executive changes, earnings outcomes, product announcements, or corporate transactions.
What makes the category appealing is that it maps to events that can move industries and markets. What makes it tricky is that companies can change plans, disclosures can be nuanced, and rumors can muddy the waters.
The strongest contracts point to specific filings, official press releases, or clearly defined outcomes. The weaker ones rely on headlines or broad claims that can be argued about after the fact.
Common Types of Business Prediction Markets
These settle on a reported metric from a company’s official earnings release (or defined filing). Strong markets specify GAAP vs non-GAAP and the exact metric line.
Examples:
- Apple reports quarterly revenue above a defined level
- NVIDIA reports quarterly data center revenue above a threshold
- Tesla reports quarterly deliveries above a threshold
These settle on formal corporate actions: IPO, merger close, spin-off, stock split - generally anchored to filings or official releases.
Examples:
- A high-profile private company like Stripe files for an IPO by a deadline
- Disney completes the Hulu ownership purchase arrangement by a deadline
- A major merger closes, like Paramount-WB Discover “deal closes by date”
These settle on an official appointment/resignation. Clean if rules specify what counts (board announcement, filing).
Examples:
- CEO change at a major firm like Boeing is announced by a deadline
- A named company appoints a new CFO by a deadline
- OpenAI CEO appointment/resignation is formally announced by a deadline
These settle on measurable business outputs (stores, subscribers, deliveries), but only if the company publishes the figure consistently.
Examples:
- Netflix reports subscriber additions above a threshold in a quarter
- Starbucks reports store count above a defined number by year-end
- Amazon reports that Prime membership reaches a threshold
These settle on official enforcement, settlements, approvals, or fines - anchored to a regulator/court or official filings.
Examples:
- The SEC approves a spot Bitcoin ETF (issuer-specific approvals by date)
- A major antitrust case ends in a settlement by a deadline
- A regulator issues a fine against a named bank by a deadline
Technology and Product Milestones
Technology and product milestone markets focus on whether a product, feature, or technical event happens by a given deadline, or whether a measurable adoption outcome is reached.
This category can be genuinely useful because product timelines matter and public roadmaps are often incomplete. It can also be messy if the contract tries to settle on a claim like “launches” or “releases” without defining what that means.
For beginners, the safe way to approach tech markets is to insist on rule clarity: what counts as a launch, what geography counts, what version counts, and what source confirms it. A feature can soft-launch, roll out gradually, or be available to some users but not others. Good contracts anticipate those realities.
Common Types of Technology Prediction Markets
These settle on whether a product is released by a date, but the contract must define release (GA vs beta, regions, platforms).
Examples:
- Apple releases the next major iOS version by a deadline
- Meta releases a named product feature to the public by a deadline
- Tesla releases Full Self-Driving feature version milestones by a deadline
These are about when something becomes generally available, which matters because many products soft-launch.
Examples:
- A new Google AI feature becomes available to all US users by a deadline
- Microsoft releases a named Windows feature broadly by a deadline
- OpenAI releases a named feature to all ChatGPT users by a deadline
These settle on published adoption metrics, but only workable when there’s a stable public source.
Examples:
- Threads (Meta) reaches a publicly reported monthly active user threshold
- TikTok reaches a defined download milestone
- A new Apple Vision product hits a defined shipment estimate
These settle on explicit platform actions: approval, removal, policy enforcement - anchored to official announcements.
Examples:
- Apple App Store approves a named app update by a deadline
- Google Play removes a named app by a deadline
- X (Twitter) changes verification policy by a deadline
These settle on publication or adoption of standards by a known standards body.
Examples:
- W3C publishes a final recommendation for a named web standard
- IEEE approves a named wireless standard update
- NIST publishes final guidance on a named cybersecurity framework update
Finance and Market Indicators
Finance and market indicator markets cover outcomes tied to broad financial benchmarks, rates, and other measurable market signals. This category sits close to traditional derivatives in spirit, but prediction-market contracts still settle on a defined event or level at a defined time.
For beginners, the appeal is simplicity: instead of managing a leveraged product, you’re trading on whether a benchmark is above or below a level, or whether a rate decision hits a specified outcome.
well-designed market will specify the benchmark, the time of measurement, and what happens on holidays, early closes, or data interruptions. This is also a category where small details can matter a lot, because a price can cross a level briefly and then move away.
Common Types of Finance Prediction Markets
These settle on whether an index is above/below a level at a defined close/time, with a defined source.
Examples:
- S&P 500 closes above 5,000 on a specified date
- Nasdaq-100 closes below a defined level on a specified date
- Dow Jones closes above a defined level at month-end
These settle on yields/rates at a defined time and source (Treasury yields, mortgage rate benchmarks, etc.).
Examples:
- US 10-year Treasury yield closes above 4.5% on a specified date
- US 2-year Treasury yield closes below a defined threshold
- 30-year fixed mortgage rate (Freddie Mac PMMS) is above 7% on the next weekly release
These settle on whether a benchmark reaches a level by a deadline. Needs clear definition of what counts as reaching.
Examples:
- S&P 500 reaches a defined level at any point before quarter-end
- Gold reaches $2,500/oz by year-end using a named benchmark
- EUR/USD reaches 1.15 by a deadline using a named reference rate
These settle on whether something finishes up/down over a period.
Examples:
- S&P 500 is higher at month-end than at month start
- US 10-year yield is lower at quarter-end than at quarter start
- USD Index (DXY) is higher at year-end than mid-year
These settle on a defined financial event that affects markets, but the event itself must be objectively confirmed.
Examples:
- A specific central bank announces a rate cut at the next meeting
- The US Treasury announces a change in auction sizing at the next refunding statement
- A major index provider (like S&P Dow Jones) announces an index inclusion/exclusion for a named company
Crypto Prediction Markets
Crypto-related markets cover outcomes tied to crypto prices, network milestones, and ecosystem events.
On regulated platforms, what you’ll actually see can vary a lot, and it tends to be shaped by what a venue can define and settle cleanly.
The main benefit is that these markets can offer a simpler way to express a view than trading spot or leveraged crypto products, especially when the contract is a straightforward threshold. The main caution is the same as everywhere else, but amplified: sources and timing matter. Crypto trades around the clock, prices differ across venues, and “official” settlement prices depend on what the contract specifies.
These settle on whether an asset is above/below a level at a defined time and source (exchange or index).
Examples:
- Bitcoin is above $100,000 at 4:00pm ET on a specified date
- Ethereum is below $2,000 at a specified timestamp
- Solana is above a defined level at month-end
These settle on whether a price level is reached before a deadline, requiring clear definition of what counts as reaching.
Examples:
- Bitcoin hits $120,000 at any time before year-end
- Ethereum reaches $5,000 before a deadline
- A named token reaches a defined market cap threshold
These settle on official approvals or verifiable events, commonly around ETFs or regulatory decisions.
Examples:
- The SEC approves a specific spot ETF issuer by a deadline
- A court rules on a major crypto-related case by a date (e.g., SEC v. Ripple type outcomes)
- A stablecoin issuer receives a named regulatory license by a deadline
These settle on protocol upgrades or network events, but need authoritative confirmation and clear definitions.
Examples:
- Ethereum activates a named hard fork by a deadline
- Bitcoin completes a named upgrade milestone by a deadline
- A major chain (e.g., Solana) hits a defined uptime threshold over a period
These settle on public, official actions by exchanges/platforms or regulators affecting market access.
Examples:
- Coinbase lists a named token by a deadline
- Binance resumes withdrawals for a named network by a deadline
- A regulator approves a named crypto exchange product in a jurisdiction by a deadline
What you cannot trade on in regulated U.S. prediction markets
Regulated U.S. venues do not have a blank check to list any question people want to speculate on.
Certain categories are widely treated as incompatible with the public interest, and others are scrutinized because they look too much like gaming rather than risk management or price discovery.
The important point for a trader is not to memorize every edge case. It is to recognize the types of markets that are likely to be prohibited, quickly removed, or written so tightly that casual assumptions fail.
Prohibited Public-Interest Categories
Some market topics are treated as inherently problematic because they invite harmful incentives or directly touch violence and unlawful activity. Even when a contract could be written in a way that is technically verifiable, a regulated platform may still avoid it because the category itself creates unacceptable incentives or conflicts with public-interest standards.
Common Prohibited public-interest contract types you’ll see
- Outcomes tied to acts of violence or mass harm
- Outcomes tied to terrorism or terror-related events
- Outcomes tied to assassination or targeted physical harm
- Outcomes tied to criminal activity or explicit unlawful conduct
- Outcomes where participating could plausibly incentivize wrongdoing
What tends to get restricted or avoided in Prohibited public-interest categories
- In practice, these topics are generally avoided entirely on regulated venues
- Attempts to reframe harmful outcomes as neutral events still tend to be scrutinized
- Markets that reward predicting or benefiting from harm create obvious incentive problems
Examples of Prohibited public-interest markets
- A named attack occurs in a specified location by a date
- A named public figure is harmed or killed by a date
- A terrorist incident occurs in a defined region this month
- An illegal act occurs or is successfully carried out by a date
- A criminal enterprise milestone happens by a date
- A violent event count exceeds a threshold in a window
Even when a market is not framed as violence, death- and harm-linked markets are often treated as high-risk because they create obvious incentive problems and reputational risk. On regulated platforms, you should expect these to be restricted, removed, or avoided, and you should treat them as a clear signal that category boundaries are being tested.
Common Death and harm-related market types you’ll see
- Death or serious injury of a named person
- Hospitalization outcomes tied to a named person
- Disaster casualty thresholds
- Harmful event outcomes that are personally attributable
What tends to get restricted or avoided in Death and harm-related markets
- Named-person outcomes are especially sensitive
- Markets that could be seen as encouraging harm are typically avoided
- Outcomes with unclear confirmation sources create settlement disputes on top of ethical risk
Examples of Death and harm-related markets
- A named person dies by a date
- A named person is hospitalized by a date
- A disaster causes deaths above a threshold in a defined window
- A violent incident causes injuries above a threshold
- A specific harm event occurs in a location by a date
- A casualty count exceeds a threshold this month
Know when you are personally not allowed to trade
Even if a market is listed and well-defined, you may be the wrong person to trade it. If you have non-public information, a professional role with access, or influence over the outcome, trading can be inappropriate and potentially prohibited under platform rules or law.
Common Personal restriction situations you’ll see
- You have access to non-public information relevant to settlement
- You are employed by or contracted with an organization that can affect the outcome
- You are in a role with direct influence over the decision
- You are subject to professional trading restrictions
- You are trading on behalf of someone else with restricted access
What you should avoid for personal eligibility
- Trading markets tied to your employer’s confidential decisions
- Trading markets tied to a process you can influence
- Trading based on unpublished data or internal metrics
- Coordinated trading where you can shape outcome perception
- Any situation that would not withstand disclosure
Examples of personal restriction red flags
- You work on a policy team and trade on that policy outcome
- You are part of a legal team with non-public case details
- You are employed at a company and trade on unannounced actions
- You have access to embargoed data releases
- You have influence over a decision timeline
- You are trading a market you helped create or promote
Ari started his gaming career as a poker grinder, then a crypto trader, before stumbling onto prediction markets. He’s now deep into betting on everything from politics to pop culture to tech layoffs. If it has uncertainty and odds, Ari’s in.
Skeptical by nature, Ari is fully convinced that the weirdest bets often hide the sharpest edges. If you’ve ever wondered whether it’s possible to beat the market by reading the news better than everyone else - Ari’s here to show you how.
