Our Pricing Methodology
Transparent, Data-Driven, and Accurate: How SteamAnalyst Calculates CS2 & CS:GO Skin Prices
Last updated: January 2026
Why Our Methodology Matters
For 12 years, SteamAnalyst has been trusted by millions of traders because we do one thing exceptionally well: we provide accurate prices based on real market data.
Unlike many competitors who display inflated listing prices or manipulated data, we track actual completed sales from the Steam Community Market and verified third-party platforms. This page explains exactly how we do it.
Core Principle: Our prices reflect what items actually sell for, not what sellers hope they will sell for. This distinction is what makes SteamAnalyst the industry standard.
Data Sources
The CS2 skin economy has evolved significantly since 2013. Today, trading happens across multiple platforms - from Steam Market to BUFF163 to dozens of other marketplaces. SteamAnalyst aggregates data from all major markets to give you a complete picture of what skins are actually worth.
Why Multi-Market Matters: A skin might sell for $100 on Steam Market (with 15% fees) but $85 on BUFF163 (with ~2.5% fees). Which is the "real" price? We believe you need to see both - that's why we show prices across all major platforms.
Integrated Marketplaces
We aggregate real transaction data from the following verified sources:
BUFF163 (buff.163.com)
The world's largest CS2 skin marketplace by transaction volume. BUFF163 has become the de facto price reference for serious traders due to its low fees (~2.5%) and high liquidity. We integrate BUFF pricing directly into our multi-market comparison.
Steam Community Market
The official Valve marketplace. While fees are higher (~15%), Steam Market remains important for:
- New players and casual traders who prefer convenience
- Items that are rarely traded on third-party platforms
- Historical data going back to 2013
- Official transaction verification
Additional Integrated Markets
- CS.MONEY: Instant trade bot with real-time buy/sell prices
- BitSkins: Popular Western marketplace with competitive fees
- DMarket: Global marketplace with fiat and crypto options
- Skinport: European-focused marketplace
- CSGOFloat: Float-specific marketplace for collectors
How We Use Multi-Market Data
Having data from multiple markets allows us to:
- Show real market prices: Compare what you'd actually pay across platforms
- Identify arbitrage: Find profit opportunities between markets (see our Profit Generator)
- Validate accuracy: Cross-check prices to detect anomalies
- Account for fees: Help you understand true costs after marketplace fees
- Track global demand: See how prices differ across regions
Price Calculation Method
Once we collect raw transaction data, we apply a multi-step calculation process to derive the final displayed price.
Step 1: Data Aggregation
We aggregate sales data across multiple time periods to capture both short-term volatility and long-term trends:
- 7-day average: Recent market sentiment (60% weight)
- 30-day average: Medium-term stability (25% weight)
- 60-day average: Long-term trend validation (10% weight)
- 90-day average: Historical baseline (5% weight)
Why time-weighted? Recent sales are more relevant for current trading decisions, but longer-term data prevents short-term price manipulation from distorting the market view.
Step 2: Volume Weighting
Not all sales are equal. High-volume items (100+ daily sales) have more reliable pricing than rare items (1-5 sales per week). We adjust for this:
Volume-Based Adjustments
- High Volume (100+ sales/day): Real-time pricing with 7-day average (minimal lag)
- Medium Volume (10-99 sales/day): 7-day and 30-day blend for stability
- Low Volume (1-9 sales/day): 30-day and 60-day blend to reduce outlier impact
- Rare Items (<1 sale/day): 60-day to 180-day average with manual review flags
Step 3: Outlier Detection & Removal
Price manipulation attempts (wash trading, fake sales, bot manipulation) must be filtered out to maintain accuracy.
Our outlier detection algorithm:
- Statistical Analysis: Calculate mean and standard deviation for each item's recent sales
- 3-Sigma Rule: Flag sales that fall outside 3 standard deviations from the mean
- Velocity Checks: Detect suspicious rapid buy/sell patterns (wash trading indicators)
- Cross-Market Validation: Compare Steam prices to third-party markets; flag discrepancies >30%
- Manual Review Queue: Human analysts review flagged transactions for final determination
Example: If an AWP | Dragon Lore typically sells for $2,000-$2,500, and we detect a sale at $50 or $15,000, this is automatically flagged and excluded from our calculations until verified as legitimate.
Step 4: Bot Trade Filtering
Automated trading bots can create artificial volume that distorts market data. We filter these transactions using:
- Transaction velocity analysis: Human traders don't complete 50 purchases per minute
- Account age verification: New accounts (<30 days) with high volume are flagged
- Pattern recognition: Repetitive buy/sell at identical prices indicates bot activity
- Steam API restrictions: We honor Steam's bot-flagged accounts and exclude their trades
Step 5: Currency Conversion
SteamAnalyst displays prices in 15+ currencies. Our conversion methodology ensures accuracy:
Multi-Currency Support
- Base Currency: All calculations are performed in USD for consistency
- Forex Data Source: Live exchange rates from European Central Bank (ECB) and XE.com
- Update Frequency: Currency rates refreshed hourly
- Regional Adjustments: Steam applies different regional pricing; we account for these variations
Quality Assurance & Verification
Accurate pricing requires continuous validation and quality control. Our QA process includes:
Automated Quality Checks
- Daily Consistency Audits: Compare today's prices to historical trends; flag anomalies >15% deviation
- Cross-Source Validation: Verify Steam prices against 3+ third-party markets
- Data Integrity Tests: Ensure no missing data, corrupt records, or API failures
- Volume Anomaly Detection: Alert on sudden volume spikes (possible manipulation or new case release)
Manual Review Process
Our team of veteran traders reviews:
- High-value items (>$500): Manual verification of all transactions
- Rare items: Low-volume skins receive weekly price reviews
- Flagged outliers: Human judgment on borderline cases
- New releases: Case openings and new skins get enhanced monitoring for first 30 days
User Feedback Integration
We encourage community feedback:
- Traders can report suspected pricing errors via our feedback form
- Reports are reviewed within 24-48 hours
- Verified errors trigger immediate price recalculation and data source investigation
Update Frequency
Pricing data is updated on different schedules based on item liquidity and market dynamics:
| Item Category | Update Frequency | Data Latency |
|---|---|---|
| High-Volume Items (AK-47 | Redline, AWP | Asiimov, etc.) | Real-time (5-15 min) | <15 minutes |
| Popular Knives (Karambit, Butterfly, etc.) | Hourly | <1 hour |
| Mid-Tier Skins | Every 4 hours | <4 hours |
| Rare/Low-Volume Items | Daily | <24 hours |
| Stickers & Collectibles | Daily | <24 hours |
Why SteamAnalyst vs. Competitors
Here's how our methodology compares to other CS2/CS:GO pricing sites:
| Feature | SteamAnalyst | Most Competitors |
|---|---|---|
| Data Source | Actual sales data | Listing prices |
| Outlier Filtering | Advanced statistical filtering | Minimal or none |
| Bot Trade Filtering | Comprehensive bot detection | Unfiltered data |
| Multi-Market Validation | 5+ marketplace cross-checks | Single source only |
| Manual Review | Expert trader oversight | Fully automated |
| Methodology Transparency | Fully documented (this page) | Undisclosed methods |
| Historical Data | 12 years of records | Limited history |
Limitations & Disclaimers
While we strive for maximum accuracy, traders should be aware of inherent limitations in any pricing system:
Market Volatility
CS2 and CS:GO skin prices can change rapidly due to:
- Game updates: New cases, operations, or balance changes can instantly shift demand
- Professional play: Major tournament usage can spike prices within hours
- Social media influence: Streamer showcases or viral posts create temporary demand surges
- Steam sales: Discounts or promotions affect purchasing behavior
Our recommendation: Always check the timestamp on price data. For volatile items, refresh prices before making large trades.
Regional Variations
Steam applies regional pricing that can create 10-30% price differences between countries. Our prices reflect global average pricing weighted by transaction volume in each region.
Float Value Impact
For wear-based skins (Factory New, Field-Tested, etc.), float values (0.00-1.00) significantly impact price. Our base prices represent median float values. Exceptionally low floats (0.00x) or pattern-specific variants (e.g., Karambit Case Hardened "Blue Gem") can trade at 2-10x our listed price.
Private Sales & Trades
High-value skins ($5,000+) are often traded privately or via third-party platforms with limited transparency. Our prices for these items may lag behind private market valuations by 5-15%.
Ongoing Improvement
Our methodology is continuously refined based on:
- Machine learning enhancements: We deploy ML models to improve outlier detection and trend prediction
- Community feedback: Trader reports help us identify blind spots in our data
- Market evolution: As new marketplaces emerge, we integrate them into our validation process
- API improvements: When Steam or third-party platforms enhance their APIs, we leverage new data points
Our Commitment: SteamAnalyst will always prioritize accuracy over convenience, transparency over opacity, and real market data over inflated listings. That's why traders have trusted us for 12 years—and why we'll remain the industry standard for years to come.
Questions About Our Methodology?
We believe in complete transparency. If you have questions about how we calculate prices, concerns about specific items, or suggestions for methodology improvements, please reach out:
- Feedback Form: Contact Us
- Twitter/X: @SteamAnalyst
- Discord: Join our community
