Market snapshot: Oct 13, 2026, 12:00 AM UTC. Prices may have changed since this snapshot.

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Event GroupKALSHIElections

Linz mayoral election winner?

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Linz mayoral election winner?

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Will SPÖ win the 2027 Linz mayoral election?

No data available

Single-Platform Markets(4)

Market	Platform	Price
Will SPÖ win the 2027 Linz mayoral election?	Kalshi	72%
Will FPÖ win the 2027 Linz mayoral election?	Kalshi	19%
Will ÖVP win the 2027 Linz mayoral election?	Kalshi	5%
Will Greens win the 2027 Linz mayoral election?	Kalshi	4%

AI Analysis

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72%

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About This Event

In 2027 If X wins the 2027 Linz mayoral election, then the market resolves to Yes. X party's market resolves Yes only if the person elected mayor, after any runoff, engere Wahl, was the candidate registered by the Linz election authority for that party's list. X candidate of any other list, including one the party backs, does not count for it; a registered party the named party merges into counts as the named party. X candidate registered under a listed party's own name counts only for that par

AI-generated analysis based on market data. Not financial advice.

Custom AI Analysis Prompt

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Open in:ChatGPT Claude Gemini Grok DeepSeek

**Role:** Expert Prediction Market Analyst & Trader
**Objective:** Analyze the provided betting market data to deliver actionable insights, identify mispricings, and perform scenario analysis.
**Current Date:** Tuesday, October 13, 2026
**Context:** Prediction markets (Polymarket/Kalshi) are binary option markets where price (1-99) equals implied probability (1%-99%).

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## 1. Event Snapshot
**Event:** Linz mayoral election winner?
**Category:** Elections | **Status:** active
**Resolution Date:** N/A (Unknown)
**Time Pressure:** Unknown

**Description:** In 2027

If X wins the 2027 Linz mayoral election, then the market resolves to Yes. X party's market resolves Yes only if the person elected mayor, after any runoff, engere Wahl, was the candidate registered by the Linz election authority for that party's list. X candidate of any other list, including one the party backs, does not count for it; a registered party the named party merges into counts as the named party. X candidate registered under a listed party's own name counts only for that par

**Resolution Criteria (Sample):**
"If SPÖ wins the 2027 Linz mayoral election, then the market resolves to Yes. Secondary rules: A party's market resolves Yes only if the person elected mayor, after any runoff (engere Wahl), was the candidate registered by the Linz election authority for that party's list. A candidate of any other li"

## 2. Market liquidity & Volume
* **Total Volume:** $0
* **Total Liquidity:** $0
* **Activity Level:** Low Activity (Vol/Liq Ratio: 0.00)

## 3. Market Data (Prices & Odds)
### 1. Will SPÖ win the 2027 Linz mayoral election?
- **Kalshi** (End: Sep 25, 2028): Vol $0
  DATA: [Yes: 72.0% (0.0%)] | [No: 28.0% (0.0%)]

### 2. Will ÖVP win the 2027 Linz mayoral election?
- **Kalshi** (End: Sep 25, 2028): Vol $0
  DATA: [Yes: 4.5% (0.0%)] | [No: 95.5% (0.0%)]

### 3. Will Greens win the 2027 Linz mayoral election?
- **Kalshi** (End: Sep 25, 2028): Vol $0
  DATA: [Yes: 4.0% (0.0%)] | [No: 96.0% (0.0%)]

### 4. Will FPÖ win the 2027 Linz mayoral election?
- **Kalshi** (End: Sep 25, 2028): Vol $0
  DATA: [Yes: 19.0% (0.0%)] | [No: 81.0% (0.0%)]

---

## Analysis Instructions
Please provide a structured analysis using the following template:

### 1. Executive Summary
*   **Verdict:** [Most Likely Outcome]
*   **Confidence:** [0-100]%
*   **Timeframe:** [Immediate / Short-term / Long-term]
*   **Actionable Trade:** [Buy YES / Buy NO / Stay Away] (Include entry price target if applicable)
*   **Rationale:** 2-sentence summary of the core thesis.

### 2. Scenario Analysis
*   **Bull Case (Why YES goes up):** List specific catalysts or data points.
*   **Bear Case (Why YES goes down):** List specifics.
*   **Invalidation Point:** What happens to prove your thesis wrong?

### 3. Market Mechanics & Risks
*   **Liquidity/Volume Analysis:** Is the market efficient? Is it easy to exit?
*   **Cross-Platform Arbitrage:** (If applicable) Is the spread tradeable after fees?
*   **Time Decay:** How does time passing affect this position?

### 4. Signal Scores (0-100)
*   **Momentum:** [Score] (Price trend & velocity)
*   **Conviction:** [Score] (Volume backing the move)
*   **Information Edge:** [Score] (Likelihood of non-public info affecting price)
*   **Risk/Reward:** [Score] (Potential upside vs downside)

**Constraints:**
- Be direct and objective.
- Use bullet points for readability.
- If data is conflicting or insufficient, explicitly state "Low Confidence".

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AI-written background. References identify the evidence used; Wikipedia links under Learn More are additional reading. Prices and provider rules are dated snapshots. This is not financial advice.

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