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Fear and Greed Index

SENTIMENT:

KOL CALLS

Long/Short Calls

MINDSHARE:

Intelligence

Emotions

Social Momentum

FEED:

Cultiness Index

Followers

Volume ($)

Volatility

Mcap vs BTC

Sentiment Timeframes

Chiliz (CHZ) Sentiment & Fear and Greed Index

As of July 14, 2026, Chiliz's Nebula Fear & Greed Index is 21 (Fear), its social sentiment score is 33/100 (bearish), it holds 0.00% of crypto social mindshare. These signals are computed by Nebula from social posts across crypto Twitter/X and other sources, scored with large language models rather than keyword counts.

Updated continuously · Source: Nebula

Fear & Greed21 · Fear
Sentiment33/100
Mindshare0.00%
Price$0.0167 +3.1%

Latest Chiliz insights

Chiliz Deploys CHZ and PEPPER on Robinhood ChainJul 13, 2026

Chiliz has gone live on Robinhood Chain, deploying its native token CHZ and the PEPPER token. This marks the beginning of Chiliz's omnichain strategy to expand Fan Tokens and SportFi across multiple blockchain networks.

Chiliz Brings Fan Tokens to Solana, Base: Historic ExpansionApr 28, 2026

Chiliz has announced a major expansion of its Fan Token support. Fan Tokens will now be available on the Solana and Base networks, marking a significant growth for the platform. This move is considered the biggest expansion in the history of digital assets in sports.

Frequently asked questions

What is Chiliz's Fear & Greed Index?

Chiliz's Nebula Fear & Greed Index is currently 21 out of 100, which is Fear. The index blends social sentiment, social interest, price momentum, volatility, and emotional intensity into a single 0–100 sentiment score, updated continuously.

Is Chiliz bullish or bearish right now?

Chiliz's social sentiment is currently bearish, with a sentiment score of 33/100 based on how bullish or bearish the crypto social conversation is. Sentiment reflects the mood of the market, not price direction or financial advice.

How does Nebula measure Chiliz sentiment?

Nebula reads every relevant social post about Chiliz across crypto Twitter/X and other sources and scores it with large language models — capturing bullish/bearish tone, emotion, and who is speaking (from retail to smart money) — rather than counting keywords.