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GroupPOLYMARKET

Event GroupPOLYMARKETSports

LoL: Eintracht Spandau vs Team Orange Gaming (BO1) - Prime League 1st Division Regular Season

Name: LoL: Eintracht Spandau vs Team Orange Gaming (BO1) - Prime League 1st Division Regular Season
End: 2026-04-10T22:00:00.000Z

Total Volume

$108.34K

Events

Markets

Trade on Polymarket

LoL: Eintracht Spandau vs Team Orange Gaming (BO1) - Prime League 1st Division Regular Season

Vol

$108.34K

Events

Markets

Polymarket

Platform StatsQuick Platform Comparison

Polymarket

markets · $108.34K

Kalshi

markets · $0.00

Price Spread

0.0%avg

max 0.0%

Arbitrage

of 0 cross-platform

Volume DistributionTotal: $108.34K

100%

Polymarket leads

Price ChartMatched Markets Price Graph

1 market tracked

Game 1: Odd/Even Total Kills?

No data available

Single-Platform Markets(1)

Market	Platform	Price
Game 1: Odd/Even Total Kills?	Poly	50%

AI Analysis

Trader mode: Actionable analysis for identifying opportunities and edge

50%

Top Probability

$108.34K

Volume

Markets

Platforms

About This Event

This market refers to the LoL match between Eintracht Spandau and Team Orange Gaming in the Prime League 1st Division Regular Season, initially scheduled for April 10 at 12:00PM ET. This market will resolve to "Eintracht Spandau" if Eintracht Spandau win the match against Team Orange Gaming. This market will resolve to "Team Orange Gaming" if Team Orange Gaming win the match against Eintracht Spandau. If the match is canceled (not played at all), ends in a tie, or is delayed beyond 7 days fro

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:** Friday, July 10, 2026
**Context:** Prediction markets (Polymarket/Kalshi) are binary option markets where price (1-99) equals implied probability (1%-99%).

---

## 1. Event Snapshot
**Event:** LoL: Eintracht Spandau vs Team Orange Gaming (BO1) - Prime League 1st Division Regular Season
**Category:** Sports | **Status:** active
**Resolution Date:** Apr 10, 2026 (Ended)
**Time Pressure:** Expired

**Description:** This market refers to the LoL match between Eintracht Spandau and Team Orange Gaming in the Prime League 1st Division Regular Season, initially scheduled for April 10 at 12:00PM ET.

This market will resolve to "Eintracht Spandau" if Eintracht Spandau win the match against Team Orange Gaming.

This market will resolve to "Team Orange Gaming" if Team Orange Gaming win the match against Eintracht Spandau.

If the match is canceled (not played at all), ends in a tie, or is delayed beyond 7 days fro

**Resolution Criteria (Sample):**
"This market will resolve to "Odd" if the total combined kills by both teams in Game 1 is an odd number.

This market will resolve to "Even" if the total combined kills by both teams in Game 1 is an even number.

"Total combined kills" includes all champion kills recorded during the match by both Ein"

## 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. Game 1: Odd/Even Total Kills?
- **Polymarket** (End: Apr 10, 2026): Vol $0
  DATA: [Odd: 50.0% (0.0%)] | [Even: 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.

POLYMARKETSports