Lurk Score

What Lurk Scores are

Lurk Scores are a scoring layer built on top of Track Records.

While Track Records show the underlying history, Lurk Scores turn that history into a faster credibility signal.

The goal is to help users quickly understand whether a trader, strategy, source, or signal history appears reliable based on documented performance.

How Lurk Scores relate to Track Records

Track Records are the evidence.

Lurk Scores are the summary.

A Track Record may show:

• past calls
• resolved outcomes
• win/loss history
• market categories
• confidence levels
• timestamps
• notes
• performance over time

A Lurk Score takes that history and creates a cleaner high-level signal that is easier to compare.

A Lurk Score should never replace the Track Record. It should point users toward it.

What Lurk Scores are for

Use Lurk Scores when you want to:

• quickly compare credibility
• identify stronger signal sources
• filter noisy users or strategies
• review performance at a glance
• decide whether a Track Record deserves deeper review
• understand whether someone has been consistently useful over time

Lurk Scores are designed to save time, not make decisions automatically.

What may affect a Lurk Score

A Lurk Score may consider factors like:

• accuracy
• consistency
• sample size
• recency
• specificity of calls
• category performance
• confidence calibration
• resolved versus unresolved entries
• quality of documented reasoning
• performance across different market types

The score should reward useful, specific, and historically grounded signal.

It should not reward volume alone.

Why sample size matters

A small Track Record can look impressive without proving much.

Someone who gets 2 out of 2 calls right may have a perfect record, but not enough history to prove consistency.

Lurk Scores should account for this by weighing larger, cleaner records more heavily than tiny records with limited evidence.

Why recency matters

Markets change.

A user or strategy that performed well a year ago may not be as useful today.

Lurk Scores may weigh recent performance more strongly while still preserving long-term history inside the full Track Record.

Why category matters

A person may be strong in one area and weak in another.

For example, someone may perform well in:

• politics
• sports
• crypto
• macro
• entertainment
• breaking news markets

But that does not mean their signal quality transfers across every category.

A good Lurk Score should help users understand general credibility while still allowing category-specific review.

What a Lurk Score is not

A Lurk Score is not:

• a guarantee of future performance
• a trading recommendation
• proof that someone is always right
• a replacement for reviewing the underlying record
• a measure of popularity alone
• a reward for posting constantly

A high score means the available record appears stronger based on Lurk’s scoring logic.

It does not mean the next call will be right.

Using Lurk Scores

A typical workflow:

1. Find a trader, source, strategy, or signal.
2. Check the Lurk Score for a quick credibility read.
3. Open the full Track Record.
4. Review the underlying calls and outcomes.
5. Check sample size, category, and recency.
6. Decide whether the signal deserves attention.

Best practices

Use Lurk Scores as a filter, not a final answer.

Before trusting a score, check:

• how many entries support it
• whether the record includes losses
• how recent the performance is
• which market categories it applies to
• whether the person makes specific calls
• whether the score is based on resolved outcomes

A score with strong supporting history is more useful than a score built on limited activity.

Common issues

“Why does someone with a high win rate have a lower Lurk Score?”

Their sample size may be small, their calls may be vague, or their performance may not be recent enough.

Win rate is only one part of credibility.

“Why does someone with losses still have a strong Lurk Score?”

Losses are normal.

A strong record can include losses if the overall history shows useful judgment, good calibration, clear reasoning, and consistent performance.

“Why did a Lurk Score change?”

Scores may update as:

• markets resolve
• new calls are added
• old calls become less recent
• entries are corrected
• additional performance data becomes available

“Can a Lurk Score be wrong?”

Yes.

A Lurk Score is a tool for summarizing evidence. It depends on available data, scoring logic, and the quality of the underlying Track Record.

Always review the full record when the decision matters.

Important note

Lurk Scores are credibility signals.

They help users evaluate documented history faster, but they do not guarantee future results or replace independent judgment. Use them as a starting point for deeper review.