Jungle Fang
 We check the relevance every 3 hours

Jungle Fang

g4skins.com
Case Price
$175.75
Total EV
$151.46
EV Ratio
0.862×
Skins in case
22
EV Ratio = Total EV / Case Price. A ratio of 0.862× means that statistically, each case opening returns 86.2% of the case cost. Results are random - individual outcomes will vary from statistical estimates.

Simulate openings

Roll Jungle Fang against its real drop rates and watch the math play out.

Skins in Jungle Fang (14)

g4skins.com★ Falchion Knife | Tiger Tooth

★ Falchion Knife | Tiger Tooth

g4skins.com★ Huntsman Knife | Tiger Tooth

★ Huntsman Knife | Tiger Tooth

g4skins.com★ Ursus Knife | Tiger Tooth

★ Ursus Knife | Tiger Tooth

g4skins.com★ M9 Bayonet | Tiger Tooth

★ M9 Bayonet | Tiger Tooth

g4skins.com★ Karambit | Tiger Tooth

★ Karambit | Tiger Tooth

g4skins.com★ Butterfly Knife | Tiger Tooth

★ Butterfly Knife | Tiger Tooth

About this case

Where Is This Case Available?

The Jungle Fang case is available on g4skins.com. It contains 22 skins with published drop rate statistics. The Expected Value and drop rate data below reflect current statistical data for this specific case listing on g4skins.com.

Case Overview

The inventory is organized into common, intermediate, and premium categories. Most outcomes are concentrated in higher-frequency segments, while premium entries account for a smaller share of total probability. This layered structure creates a balanced distribution model that can be examined through rarity segmentation, item diversity, and value concentration. Market relevance is influenced by asset demand, liquidity, and the breadth of included inventory.

Value and Risk Factors

Expected return characteristics are shaped by rarity allocation, demand stability, and the distribution of theoretical value across tiers. When projected value depends heavily on rare outcomes, variance increases and observed results may diverge from long-term averages. Broader representation across common and mid-tier categories may reduce volatility over larger datasets. Assessment should prioritize probability distribution, inventory composition, and demand resilience.