GroupPOLYMARKET

Event GroupPOLYMARKETSports

Newcastle United vs. Bayer Leverkusen - Total Corners

Name: Newcastle United vs. Bayer Leverkusen - Total Corners
End: 2026-08-15T14:00:00.000Z

Total Volume

$506.71

Events

Markets

Trade on Polymarket

Newcastle United vs. Bayer Leverkusen - Total Corners

Vol

$506.71

Events

Markets

Polymarket

Platform StatsQuick Platform Comparison

Polymarket

markets · $506.71

Kalshi

markets · $0.00

Price Spread

0.0%avg

max 0.0%

Arbitrage

of 0 cross-platform

Volume DistributionTotal: $506.71

100%

Polymarket leads

Price ChartMatched Markets Price Graph

1 market tracked

Newcastle United vs. Bayer Leverkusen: Team to Take First Corner

No data available

Single-Platform Markets(1)

Market	Platform	Price
Newcastle United vs. Bayer Leverkusen: Team to Take First Corner	Poly	50%

AI Analysis

Trader mode: Actionable analysis for identifying opportunities and edge

50%

Top Probability

$506.71

Volume

Markets

Platforms

About This Event

Total corners markets for the Club Friendlies game between Newcastle United and Bayer Leverkusen, scheduled for August 15, 2026 at 10:00 AM ET.

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

Custom AI Analysis Prompt

Tap to expand

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:** Saturday, September 5, 2026
**Context:** Prediction markets (Polymarket/Kalshi) are binary option markets where price (1-99) equals implied probability (1%-99%).

---

## 1. Event Snapshot
**Event:** Newcastle United vs. Bayer Leverkusen - Total Corners
**Category:** Sports | **Status:** active
**Resolution Date:** Aug 15, 2026 (Ended)
**Time Pressure:** Expired

**Description:** Total corners markets for the Club Friendlies game between Newcastle United and Bayer Leverkusen, scheduled for August 15, 2026 at 10:00 AM ET.

**Resolution Criteria (Sample):**
"In the upcoming Club Friendlies game between Newcastle United and Bayer Leverkusen, scheduled for August 15, 2026 at 10:00 AM ET: This market will resolve to the team that takes the first corner in the game (regardless of format). If no corner is taken within that timeframe, this market will resolve"

## 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. Newcastle United vs. Bayer Leverkusen: Team to Take First Corner
- **Polymarket** (End: Aug 15, 2026): Vol $0
  DATA: [Newcastle United: 50.0% (0.0%)] | [Bayer Leverkusen: 50.0% (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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Educational content is AI-generated and sourced from Wikipedia. It should not be considered financial advice.

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