Autumn Bounty
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Autumn Bounty

g4skins.com
Case Price
$2.50
Total EV
$2.22
EV Ratio
0.888×
Skins in case
31
EV Ratio = Total EV / Case Price. A ratio of 0.888× means that statistically, each case opening returns 88.8% of the case cost. Results are random - individual outcomes will vary from statistical estimates.

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About this case

Where Is This Case Available?

The Autumn Bounty case is available on g4skins.com. It contains 31 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 case should be assessed as a probability-based pool in which higher-frequency items establish the typical outcome range, while lower-frequency tiers increase dispersion and extend the upper end of the distribution. Market positioning is influenced by the proportion of items with active secondary-market demand, the concentration of value within rare tiers, and the liquidity of individual cosmetics. A diversified pool with several marketable items may produce a different statistical profile from a pool where most theoretical value is concentrated in a small number of scarce entries. Item relevance, trading activity, and supply conditions therefore matter when comparing the case with similar alternatives.

Value and Risk Factors

Expected value is derived by multiplying each possible item's market value by its probability and combining those weighted outcomes. EV should not be treated as a prediction of a single opening because the actual distribution may be highly uneven. If rare items contribute a large share of total theoretical value, variance increases and the median outcome can remain materially below the arithmetic average. Realized return is also affected by liquidity, resale spreads, item condition, supply changes, and shifts in buyer demand. Stable demand across multiple rarity tiers can reduce dependence on individual high-value outcomes, while concentrated value structures create greater sensitivity to market repricing and probability distribution.