Juventus Fan token vs Recall — how do they compare? Juventus Fan token trades at Rp5,404 (market cap Rp85,83M, Rp79,43M 24h volume), while Recall trades at Rp874.4 (market cap Rp286,58M, Rp22,82M 24h volume). The key difference: Recall is far larger — about 3.3× Juventus Fan token's market cap, and Juventus Fan token's circulating supply is 15,9M / 20M JUV (80%) versus 329,4M / 1B RECALL (33%) for Recall. Which is the better fit depends on your goals — on Pluang, investors hold Juventus Fan token for 42 Days and Recall for 8 Days on average.
| JUV | RECALL | |
|---|---|---|
Market Cap | Rp85,83M | Rp286,58M |
Volume (24h) | Rp79,43M | Rp22,82M |
Circulating Supply | 15,9M / 20M JUV (80%) | 329,4M / 1B RECALL (33%) |
Typical Hold Time | 42 Days | 8 Days |
Signals from Pluang's Aura AI — not financial advice
JUV is trading at Rp5,404 with a bearish technical signal, below the pivot point of Rp5,524. The moving averages are strongly bearish, while oscillators are neutral. Support levels are at Rp5,310 and Rp5,114. No recent protocol updates or major ecosystem developments are noted.
Overall outlook is cautious due to bearish momentum and limited fundamental catalysts. Key opportunities include potential rebounds from support zones, but risks involve low liquidity and high volatility. Investors should monitor for any token utility enhancements or exchange listings.
No Aura AI signal available yet.
What Pluang investors did over the last 30 days
JUV is a fan token of the Juventus football team. Token holders can get exclusive experiences such as VIP hospitality access to Allianz Stadium, meet and greets, and signed merchandise. The token also gives fans to influence decisions such as goal celebration songs, official bus design, J icon, pennants, and playlists.
Read more on JUV →Recall is a decentralized skill marketplace where communities fund, rank, and find AI solutions that fit their needs. It provides transparent, verifiable reputation infrastructure for the AI agent economy through economic incentives and performance-based evaluation.
Read more on RECALL →