Skip to main content
0xinsider scores activity so you can sort noise from signal. There are a few distinct scores, and each answers a different question. How good is this trader? How strong is this single trade? Which way is smart money leaning on this market? This page names each field and what it measures, so you do not confuse one for another.

​
Trader quality: grade and score

On every trader and leaderboard entry:
  • grade: a letter from S to F. The headline quality signal. See Grades.
  • score: the numeric composite (0-100) behind the grade.
  • streak_tier: recent form, separate from the all-time grade. One of hot, rising, neutral, cooling, cold.
  • rank: position on the leaderboard.
Grade is the long-run verdict. streak_tier is the trailing-form overlay: an A-grade trader can be cooling, and a B-grade trader can be hot.

​
Deeper trader metrics: quant_metrics

grade and score are the headline verdict. When you want the risk and performance detail behind them, request quant_metrics on a trader (expand=quant_metrics). It returns nine curated fields, including two 0-100 scores that answer different questions:
  • smart_score: how skilled is this trader, risk-adjusted, versus the field.
  • copy_score: how safely could you copy them, after penalising traits that make a strategy hard to replicate.
The other seven fields (30- and 7-day Sharpe, profit factor, edge consistency, and their cross-sectional percentiles) are the inputs behind those scores. See Quant metrics for the full field set and how to read null.

​
Per-trade strength: signal_score

Each whale trade carries a signal_score: how strong that single fill is as a signal. Use it to rank a feed of trades, not to judge a trader overall.

​
Market direction: smart money

Market intel and smart-money flows return a smart_money object. This is the canonical view of where graded money is flowing on a market:
net_flow_usd is the field to read for “which way is smart money leaning, and how hard.” A large positive net_flow_usd with direction: YES means graded traders are buying YES.

​
Market discovery: smart_score

The explore feed ranks markets with a separate set of discovery aggregates:
  • smart_score: a per-market smart-money intensity used for ranking.
  • smart_count: how many graded traders are active on the market.
  • smart_label: a short human-readable tag.
  • discover_score: the backend-owned score behind the default hot sort.
These power discovery sorting and are distinct from the smart_money flow object above. When you want a number to act on for a specific market, use smart_money.net_flow_usd. When you want to rank a list of markets to surface, use the explore sort parameter, which is driven by these scores.

​
Picking the right field