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Market DataMarket Data · Updated September 2026

CS2 StatTrak antkainio analizė: kaip 10% traukimas virsta 20–250% kainos daugikliais

StatTrak traukimo matematika, empirinis antkainis įvairiose kategorijose ir kodėl StatTrak kartu su retumu sukuria vieną asimetriškiausių kainodarų visoje CS2 ekonomikoje.

Elena Voss
CS2REF Research
9 min

StatTrak is the simplest secondary feature in CS2 — a kill counter visible on the weapon's body, applied to roughly 10% of rolled items — and one of the most consequential for pricing. Across the catalog, StatTrak finishes trade at premiums ranging from 20% to 250% above their non-StatTrak equivalents, with the multiplier varying systematically by category, rarity tier, and float.

The StatTrak roll mechanics

When a case is opened, two independent rolls determine the StatTrak status of the resulting item:

  1. The standard rarity-tier roll (79.92% Mil-Spec / 15.98% Restricted / 3.20% Classified / 0.64% Covert / 0.26% Special) selects the finish.
  2. An independent Bernoulli trial with approximately 10% probability determines whether the resulting item is StatTrak.

StatTrak rolls are conditional on case eligibility. Some early CS:GO cases (notably the original Glove cases) and a small set of operation cases do not include StatTrak. For all standard cases that include StatTrak, the 10% rate has been empirically validated:

Why StatTrak premium varies so widely by category

The StatTrak premium is not a fixed multiplier; it scales with the collector demand for the underlying skin and the rarity of StatTrak variants of that skin. Three factors compound:

  1. Rarity compounding. A Covert finish has 0.64% drop probability. A StatTrak Covert is 0.064% — already 10× rarer. The structural scarcity layer is doubled compared to non-StatTrak.
  2. Display asymmetry. A StatTrak counter is constantly visible during gameplay. Players who use a skin in matches see and value the counter, which generates an in-game-specific demand layer that does not exist for purely-displayed skins.
  3. Collector status. StatTrak knives and high-tier rifles often serve as 'showpiece' items, where the counter is itself a collectible feature. Top-end StatTrak Karambit Doppler examples carry premiums far in excess of the rarity math.

Empirical StatTrak premiums by category

Empirical StatTrak premium by category (2025–2026 transaction medians)
CategoryMedian StatTrak premiumRange observed
Mil-Spec rifles (low-end)20–35%12–48%
Restricted rifles30–55%20–80%
Classified rifles45–80%30–110%
Covert rifles (e.g., AK Vulcan, M4 Howl)60–110%45–180%
AWP (Classified+)55–95%40–140%
Pistols (most)25–50%15–75%
Mid-tier knives (Bayonet, M9 Slaughter, etc.)70–130%55–180%
Top-tier knives (Karambit Doppler, Ruby gems)120–250%90–350%
Discontinued case knives150–250%100–400%
Premium ranges shift with market regime. The table reflects 2025–2026 transaction medians for non-rare-pattern items at typical floats.

Why the premium scales with rarity

The pattern is not coincidental — it reflects the multiplicative effect of independent low-probability events. For a Mil-Spec finish, the underlying skin is common (79.92% × within-tier-uniform), so the StatTrak roll merely adds a feature to a widely available item. For a Covert knife with multiple gem-phase variants, every layer compounds:

Compounded rarity for top-tier StatTrak variants
ItemBase probability× StatTrakEffective rarity
Mil-Spec finish (any)1 in 13× 0.101 in 130
Covert finish (specific)1 in 312× 0.101 in 3,120
Specific knife-finish1 in 36,500× 0.101 in 365,000
Specific knife-finish-FN-StatTrak~1 in 5.2M
Karambit Doppler Ruby StatTrak FN~1 in 1.3 billion
The most extreme combinations are effectively non-existent in circulation — fewer than a dozen confirmed examples exist for some entries.

The kill counter and the 'used' premium

Unique to StatTrak items, the kill counter introduces a sub-feature pricing dimension. A StatTrak knife with a kill count of 1 (essentially unused) trades at a premium over a counter-zero example because it indicates the buyer can begin building their own count. Higher counts generally do not add value — the buyer cannot reset the counter — except in specific niche cases:

  • 'Round-number' counters (1,000 / 10,000 / 100,000) sometimes attract a small collector premium.
  • Counter-zero examples are essentially priced equivalent to counter-one because the difference is functionally negligible.
  • 'Holy grail' counters — extremely high counts on a top-tier StatTrak item — can attract anomalous pricing as one-of-a-kind specimens.

StatTrak in trade-ups

StatTrak inputs in a trade-up contract produce StatTrak outputs — the StatTrak status is preserved across the trade. However, the input cost premium (StatTrak inputs cost 30–250% more than non-StatTrak equivalents) is rarely offset proportionally by the output premium. As a result:

  • StatTrak trade-ups are typically more expensive per attempt than non-StatTrak trade-ups by 30–150%.
  • Output EV margin is smaller in absolute terms because the StatTrak output premium does not always scale 1:1 with the input premium.
  • StatTrak trade-ups are a high-variance, niche strategy rather than a general method of edge-building.

Practical takeaways

  • StatTrak is an independent ~10% roll layered on every standard case opening.
  • Premium scales with rarity: 20–35% on Mil-Spec, 120–250% on top knives.
  • The compounded scarcity of StatTrak top-tier items produces some of the rarest CS2 instances in circulation.
  • Counter values rarely add value beyond the round-number novelty premium.
  • StatTrak trade-ups are higher-variance and typically lower-margin than non-StatTrak alternatives.

StatTrak premium is one of the most predictable pricing relationships in the CS2 economy. It compounds with rarity in a structured way, varies systematically by category, and creates the high-end of the multi-thousand-dollar knife market through the multiplication of two independent low-probability events. Anyone analyzing the CS2 market without modeling StatTrak as a separate dimension will systematically underprice the top of the distribution.

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CS2REF Research · 2026

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