> For the complete documentation index, see [llms.txt](https://serotolabs.gitbook.io/tradeclash/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://serotolabs.gitbook.io/tradeclash/legacy-documentation/tournament-history.md).

# Historical: Tournament History

> **This is legacy documentation.** These tournaments used the previous AI leader + Hivemind game concept. Trade Clash has since pivoted to a [sealed-lot auction game](/tradeclash/game-design/core-mechanics.md). Preserved for historical reference and traction validation.

***

## Traction & Milestones

* 1st Place — Base On-Chain Summer (New Consumer App category)
* 100,000 wallets connected across 4 tournaments
* 4 complete tournaments with full leaderboard results
* $2,000 USDC distributed to top players
* Built on Base

***

## Tournament Timeline

### Tournament #1: "Genesis" (Oct 28, 2024)

* 56 rounds over 7 days, $500 USDC prize pool
* 8,200 wallets
* First live implementation of Polymarket + Hivemind mechanic
* Players discovered Gates' 85% contrarian threshold organically
* Winner (AlphaTrade): +3,240 P\&L, focused on Gates and Laglord rounds

### Tournament #2: "Pattern Recognition" (Nov 4, 2024)

* 56 rounds, $500 USDC, 18,500 wallets
* Grudge tracking became the meta
* Winner (HivemindPro): +3,890 P\&L, specialized in Lei grudge cycles

### Tournament #3: "Divergence Trading" (Nov 11, 2024)

* 56 rounds, $500 USDC, 32,800 wallets
* Second-order thinking emerged (predict the predictors)
* Winner (ContrarianKing): +4,120 P\&L, faded obvious consensus plays

### Tournament #4: "Championship" (Nov 18, 2024)

* 56 rounds, $500 USDC, 40,500 wallets
* Clear skill separation: top 10 dominated wire-to-wire
* Winner (EconSim): +4,580 P\&L, 14/14 perfect start then played conservative defense

***

## Aggregate Statistics

| Metric        | Average     | Top 10%     | Top 1%      |
| ------------- | ----------- | ----------- | ----------- |
| Rounds Played | 46/56 (82%) | 43/56 (77%) | 41/56 (73%) |
| Win Rate      | 52%         | 64%         | 71%         |
| Final P\&L    | +240        | +2,100      | +3,800      |

Key insight: top players skipped more rounds but won at higher rates on rounds played.

***

## Base On-Chain Summer Victory

**Category**: New Consumer App (200+ projects)

**Why Trade Clash Won**: First reflexive prediction market where crowd behavior becomes input. 100K wallets in first month. All inputs/outputs verifiable on Base. Fast-swipe interface with 3-hour cycles.

***

## Prize Distribution

| Tournament   | 1st  | 2nd  | 3rd | Total Winners |
| ------------ | ---- | ---- | --- | ------------- |
| Genesis      | $150 | $100 | $75 | 10            |
| Pattern      | $150 | $100 | $75 | 10            |
| Divergence   | $150 | $100 | $75 | 10            |
| Championship | $150 | $100 | $75 | 10            |

Distribution: automatic via Base smart contract within 1 hour of tournament end.


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter:

```
GET https://serotolabs.gitbook.io/tradeclash/legacy-documentation/tournament-history.md?ask=<question>&goal=<endgoal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal.

The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.
