Space Public Sale Sparks Controversy: $2.5 Million Target Actually Oversubscribed 8-Fold, Team Attempts to Retain Millions
BlockBeats News, January 22nd, according to SolanaFloor, the decentralized leveraged prediction market Space triggered market controversy in its latest ICO round, with the project originally disclosing a fundraising target of $2.5 million, but eventually raising a total of $20 million.
The project team later responded that the $2.5 million was a "soft cap" rather than a "hard cap," in line with Launchpad industry practices, thus allowing for an expansion of the fundraising size in the face of strong market demand. The team stated that $2.5 million would only support the project's "first few months of development" and would not be sufficient to support the construction of a leveraged prediction market infrastructure over several years.
According to the team's disclosure, they plan to retain around $13 million of the oversubscribed funds out of a fully diluted valuation of approximately $69 million, with the remaining portion to be used for liquidity, ecosystem, and market-related purposes.
However, this explanation did not quell the skepticism. Ethos CEO Serpin Taxt stated that the behavior of the project, raising a "nominal $2.5 million, actually raising $20 million, and retaining around $14 million of it," was a malicious operation, drawing parallels to the previously controversial Trove project.
Community discussions believe that this event once again exposed structural issues in some current ICOs regarding information disclosure, fundraising cap design, and transparency in fund utilization.
You may also like

Who is the true winner of the "Tokenization" narrative?

Moss: The Era of AI-Traded by Anyone | Project Introduction

Chip Smuggling Case Exposes Regulatory Loophole | Rewire News Evening Update

How a Structured AI Crypto Trading Bot Won at the WEEX Hackathon
Ritmex demonstrates how disciplined risk control and structured signals can make an AI crypto trading bot more stable and reliable on WEEX, highlighting the importance of combining execution discipline with scalable AI trading systems.

Old Indicator Fails, Three Major New Signals Emerge: BTC True Bottom May Still Be Below $60K

Meeting OpenClaw Founder at a Hackathon: What Else Can Lobsters Do?

Huang Renxun's Latest Podcast Transcript: NVIDIA's Future, Embodied Intelligence and Agent Development, Soaring Demand for Inferencing, and AI's PR Crisis
How a Structured AI Crypto Trading Bot Won at the WEEX Hackathon
Crypto_Trade shows how structured inputs and controlled adaptability can build a more stable and reliable AI crypto trading bot within the WEEX AI Trading Hackathon, highlighting a practical path toward scalable AI trading systems.

AI Starts to Devour the Manufacturing Industry | Rewire News Morning Edition

When Scaling Meets Speed, Ethereum Foundation Introduces "Hardness" to Safeguard the Base Layer

Google, Circle, Stripe Flock Together to Let AI Spend Money: Payment Giants' Joys and Worries in 2026 Q1

$100 Billion Factory Purchase: Bezos and Middle Eastern Capital Shift AI Money from Cloud to Shop Floor

Xiaomi and MiniMax both unleash their ultimate moves, signaling the start of the Agent Pricing War.

Predicting markets has taken the spotlight, but the Perp DEX has been quietly waging war on traditional exchanges.

Is the Market Slump Still Making Millions a Day? Is pump.fun's Revenue Real?

Understanding x402 and MPP in One Article: The Two Paths of Agent Payments

Quick Look at the Latest 18 Graduation Projects from Alliance: Who's the Next Pump.fun?

It's not just the prediction market that profits from the Iraq War
Who is the true winner of the "Tokenization" narrative?
Moss: The Era of AI-Traded by Anyone | Project Introduction
Chip Smuggling Case Exposes Regulatory Loophole | Rewire News Evening Update
How a Structured AI Crypto Trading Bot Won at the WEEX Hackathon
Ritmex demonstrates how disciplined risk control and structured signals can make an AI crypto trading bot more stable and reliable on WEEX, highlighting the importance of combining execution discipline with scalable AI trading systems.