Steam Market pricing algorithms explained
SteamMarketRunner pricing has two parts: first it calculates a market reference price, then it applies your coefficients, Steam fee handling, profit target, and minimum-profit clamps.
The goal is not to predict the future perfectly. The goal is to make each automated buy or sell decision traceable and bounded by settings you understand.
A pricing algorithm is a rule, not a promise. Market liquidity, fees, price movement, Steam restrictions, and user settings can all turn a calculated opportunity into a loss or a skipped trade.
Algorithm families
| Code | Meaning | Basis | Common use |
|---|---|---|---|
| MS | Most frequent sale price | Mode of sale graph | Stable liquid items |
| HG | High graph | Median of daily highs | Selling near upper range |
| HSG | Safe high graph | Minimum of daily highs | More conservative high-side selling |
| AVG | Average/weighted center | Weighted median of sales | Balanced buy/sell reference |
| LG | Low graph | Median of daily lows | Quick sell or cheaper buy reference |
| BG | Buy graph | Daily lows as buy reference | Aggressive low buying |
| OG | Order graph | Live top buy order plus offset | Queueing relative to current order book |
Buy and sell algorithms are configured separately in Trading settings.
Sale-history algorithms
MS, HG, HSG, AVG, LG, and BG use accumulated sale-history snapshots. SteamMarketRunner builds a price history from periodic market data rather than calling Steam separately for every item decision.
This makes decisions more scalable and easier to audit, but it also means a newly tracked item may need time before enough data exists.
Order-book algorithm
OG uses order-book information: the current top buy order and your offset. It is useful when you want to place buy orders relative to the live queue instead of a historical sale graph.
For buy-side decisions, combine OG with exposure and depth guards. See Buy order automation and exposure guards.
Fees and net/gross prices
Steam sell listings involve two prices:
- Net — what the seller receives.
- Gross — what the buyer pays after fees.
SteamMarketRunner sends net sell prices to Steam and uses gross comparisons when checking visible listing prices. This avoids accidentally overpricing listings by treating buyer-paid gross as seller-received net.
Coefficients and profit target
After the base algorithm price is calculated, strategy settings adjust it:
- apply the buy or sell coefficient;
- account for Steam fees where relevant;
- add target profit percentage;
- enforce minimum profit if configured;
- reject the candidate if trend, liquidity, or depth guards fail.
Choosing a first algorithm
For a cautious start:
- use HG or HSG for sell-side pricing;
- use LG or AVG for buy-side pricing;
- keep coefficients close to
1; - set explicit profit and exposure limits;
- inspect early audit decisions before scaling live trading.
Aggressive settings can increase activity, but they also increase the chance of bad fills, stale orders, and churn.
Next step
Open Trading settings, start from a preset, and use the dashboard plus event log to compare calculated prices with actual Steam Market behavior.