Market snapshot: Oct 13, 2026, 12:27 PM UTC. Prices may have changed since this snapshot.

GroupPOLYMARKET

Event GroupPOLYMARKETSports

Counter-Strike: Pandaric eSports vs BIG Academy (BO3) - DACH CS Masters Regular Season

Name: Counter-Strike: Pandaric eSports vs BIG Academy (BO3) - DACH CS Masters Regular Season
End: 2026-10-15T00:00:00.000Z

Total Volume

$0.00

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Counter-Strike: Pandaric eSports vs BIG Academy (BO3) - DACH CS Masters Regular Season

Vol

$0.00

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Polymarket

Platform StatsQuick Platform Comparison

Polymarket

markets · $0.00

Kalshi

markets · $0.00

Price Spread

0.0%avg

max 0.0%

Price gaps

of 0 cross-platform

Saved prices are comparisons, not executable quotes. A price difference does not establish arbitrage. Check both contracts, live order prices, fees and available size.

Price ChartMatched Markets Price Graph

5 markets tracked

Historical observations can differ from current quotes. Kalshi points are hourly trade averages.

Saved prices are comparisons, not executable quotes. A price difference does not establish arbitrage. Check both contracts, live order prices, fees and available size.

Counter-Strike: Pandaric eSports vs BIG Academy - Map 1 Winner

No data available

Single-Platform Markets(5)

Market	Platform	Price
Counter-Strike: Pandaric eSports vs BIG Academy - Map 1 Winner	Kalshi	—
Counter-Strike: Pandaric eSports vs BIG Academy - Map 2 Winner	Kalshi	—
Counter-Strike: Pandaric eSports vs BIG Academy (BO3) - DACH CS Masters Regular Season	Kalshi	—
Games Total: Over/Under 2.5	Kalshi	—
Map Handicap: BIG.A (-1.5) vs Pandaric eSports (+1.5)	Kalshi	—

AI Analysis

Trader mode: Actionable analysis for identifying opportunities and edge

51%

Top Probability

$0.00

Volume

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About This Event

This market refers to the Counter-Strike match between Pandaric eSports and BIG Academy in the DACH CS Masters Regular Season, initially scheduled for October 14, 2026 at 2:00 PM ET. This market will resolve to "Pandaric eSports" if Pandaric eSports win the match against BIG Academy. This market will resolve to "BIG Academy" if BIG Academy win the match against Pandaric eSports. If the match is canceled (not played at all) or ends in a tie, this market will resolve to 50-50. If the match is

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:** Counter-Strike: Pandaric eSports vs BIG Academy (BO3) - DACH CS Masters Regular Season
**Category:** Sports | **Status:** active
**Resolution Date:** Oct 15, 2026 (2 days left)
**Time Pressure:** Critical

**Description:** This market refers to the Counter-Strike match between Pandaric eSports and BIG Academy in the DACH CS Masters Regular Season, initially scheduled for October 14, 2026 at 2:00 PM ET.

This market will resolve to "Pandaric eSports" if Pandaric eSports win the match against BIG Academy.

This market will resolve to "BIG Academy" if BIG Academy win the match against Pandaric eSports.

If the match is canceled (not played at all) or ends in a tie, this market will resolve to 50-50.

If the match is 

**Resolution Criteria (Sample):**
"This market refers to the Counter-Strike match between Pandaric eSports and BIG Academy in the DACH CS Masters Regular Season, initially scheduled for October 14, 2026 at 2:00 PM ET.

This market will resolve to "Pandaric eSports" if Pandaric eSports win Map 1 against BIG Academy.

This market will "

## 2. Market liquidity & Volume
* **Total Volume:** $0
* **Total Liquidity:** $522
* **Activity Level:** Low Activity (Vol/Liq Ratio: 0.00)

## 3. Market Data (Prices & Odds)
### 1. Counter-Strike: Pandaric eSports vs BIG Academy - Map 1 Winner
- **Polymarket** (End: Oct 14, 2026): Vol $0
  DATA: [Pandaric eSports: 50.0% (0.0%)] | [BIG Academy: 50.0% (0.0%)]

### 2. Counter-Strike: Pandaric eSports vs BIG Academy - Map 2 Winner
- **Polymarket** (End: Oct 14, 2026): Vol $0
  DATA: [Pandaric eSports: 50.0% (0.0%)] | [BIG Academy: 50.0% (0.0%)]

### 3. Counter-Strike: Pandaric eSports vs BIG Academy (BO3) - DACH CS Masters Regular Season
- **Polymarket** (End: Oct 15, 2026): Vol $0
  DATA: [Pandaric eSports: 27.0% (0.0%)] | [BIG Academy: 73.0% (0.0%)]

### 4. Games Total: Over/Under 2.5
- **Polymarket** (End: Oct 15, 2026): Vol $0
  DATA: [Over: 50.5% (0.0%)] | [Under: 49.5% (0.0%)]

### 5. Map Handicap: BIG.A (-1.5) vs Pandaric eSports (+1.5)
- **Polymarket** (End: Oct 15, 2026): Vol $0
  DATA: [BIG Academy: 50.0% (0.0%)] | [Pandaric eSports: 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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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.

POLYMARKETSports