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

GroupPOLYMARKET

Event GroupPOLYMARKETSports

Chinese Super League: Team with Most Clean Sheets 2026

Name: Chinese Super League: Team with Most Clean Sheets 2026
End: 2027-01-01T04:59:00.000Z

Total Volume

$1.23K

Events

Markets

Trade on Polymarket

Chinese Super League: Team with Most Clean Sheets 2026

Vol

$1.23K

Events

Markets

Polymarket

Platform StatsQuick Platform Comparison

Polymarket

markets · $1.23K

Kalshi

markets · $0.00

Price Spread

0.0%avg

max 0.0%

Arbitrage

of 0 cross-platform

Volume DistributionTotal: $1.23K

100%

Polymarket leads

Price ChartMatched Markets Price Graph

6 markets tracked

Will Dalian Yingbo keep the most clean sheets in the 2026 Chinese Super League?

No data available

Single-Platform Markets(6)

Market	Platform	Price
Will Dalian Yingbo keep the most clean sheets in the 2026 Chinese Super League?	Poly	50%
Will Qingdao West Coast keep the most clean sheets in the 2026 Chinese Super League?	Poly	48%
Will Beijing Guoan keep the most clean sheets in the 2026 Chinese Super League?	Poly	48%
Will Chengdu Rongcheng keep the most clean sheets in the 2026 Chinese Super League?	Poly	48%
Will Chongqing Tonglianglong keep the most clean sheets in the 2026 Chinese Super League?	Poly	48%
Will Tianjin Jinmen Tiger keep the most clean sheets in the 2026 Chinese Super League?	Poly	48%

AI Analysis

Trader mode: Actionable analysis for identifying opportunities and edge

50%

Top Probability

$1.23K

Volume

Markets

Platforms

About This Event

This market will resolve in favor of the team that finishes the 2026 Chinese Super League season with the most clean sheets. A clean sheet is defined as a match in which the team concedes zero goals. In the event of a tie, this market will resolve in favor of the team with the fewest total goals conceded during the 2026 Chinese Super League season. If a tie still persists, this market will resolve in favor of the team with the higher final standing in the 2026 Chinese Super League. If a tie sti

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:** Monday, October 12, 2026
**Context:** Prediction markets (Polymarket/Kalshi) are binary option markets where price (1-99) equals implied probability (1%-99%).

---

## 1. Event Snapshot
**Event:** Chinese Super League: Team with Most Clean Sheets 2026
**Category:** Sports | **Status:** active
**Resolution Date:** Jan 1, 2027 (82 days left)
**Time Pressure:** Low

**Description:** This market will resolve in favor of the team that finishes the 2026 Chinese Super League season with the most clean sheets. A clean sheet is defined as a match in which the team concedes zero goals.

In the event of a tie, this market will resolve in favor of the team with the fewest total goals conceded during the 2026 Chinese Super League season. If a tie still persists, this market will resolve in favor of the team with the higher final standing in the 2026 Chinese Super League. If a tie sti

**Resolution Criteria (Sample):**
"This market will resolve in favor of the team that finishes the 2026 Chinese Super League season with the most clean sheets. A clean sheet is defined as a match in which the team concedes zero goals.

In the event of a tie, this market will resolve in favor of the team with the fewest total goals co"

## 2. Market liquidity & Volume
* **Total Volume:** $0
* **Total Liquidity:** $33
* **Activity Level:** Low Activity (Vol/Liq Ratio: 0.00)

## 3. Market Data (Prices & Odds)
### 1. Will Chengdu Rongcheng keep the most clean sheets in the 2026 Chinese Super League?
- **Polymarket** (End: Jan 1, 2027): Vol $0
  DATA: [Yes: 47.5% (0.0%)] | [No: 52.5% (0.0%)]

### 2. Will Chongqing Tonglianglong keep the most clean sheets in the 2026 Chinese Super League?
- **Polymarket** (End: Jan 1, 2027): Vol $0
  DATA: [Yes: 47.5% (0.0%)] | [No: 52.5% (0.0%)]

### 3. Will Dalian Yingbo keep the most clean sheets in the 2026 Chinese Super League?
- **Polymarket** (End: Jan 1, 2027): Vol $0
  DATA: [Yes: 49.5% (0.0%)] | [No: 50.5% (0.0%)]

### 4. Will Qingdao West Coast keep the most clean sheets in the 2026 Chinese Super League?
- **Polymarket** (End: Jan 1, 2027): Vol $0
  DATA: [Yes: 48.0% (0.0%)] | [No: 52.0% (0.0%)]

### 5. Will Beijing Guoan keep the most clean sheets in the 2026 Chinese Super League?
- **Polymarket** (End: Jan 1, 2027): Vol $0
  DATA: [Yes: 48.0% (0.0%)] | [No: 52.0% (0.0%)]

### 6. Will Tianjin Jinmen Tiger keep the most clean sheets in the 2026 Chinese Super League?
- **Polymarket** (End: Jan 1, 2027): Vol $0
  DATA: [Yes: 47.5% (0.0%)] | [No: 52.5% (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