Paper-Order Trigger-to-Entry Price Difference in Prediction Markets

Define the two observations before calculating a difference

The trigger price is the first market price preserved when TEMIRIN creates a watchlist-derived opportunity record. The paper entry is the price a user later types when creating a simulation. They are different records captured for different purposes. Before subtracting them, verify the same market ID, outcome side, price scale, and timestamps. A mismatch between yes and no outcomes or between similar contracts can create a precise but meaningless number.

Call the result a trigger-to-paper-entry difference, not execution slippage. TEMIRIN does not route a venue order, reserve a quote, control a wallet, or know whether the entered paper price could have filled. The comparison measures change between one saved reference and one user-entered simulation. Fees, queue position, cancellations, hidden activity, and complete depth are not represented by that simple calculation, so it should remain an operational review metric.

• Verify market, outcome, scale, and both timestamps.
• Use paper-entry difference rather than execution slippage.
• Keep venue fill assumptions outside the calculation.

Reconstruct the path from evidence to the paper ledger

Open the configured watchlist record and inspect any stored evidence carrying its supported explicit market identifier. Note the trigger time, later current-price observation, alert attempts, and in-app decision record where one exists. These identifiers establish what TEMIRIN stored and when. They do not prove that an external alert was read, that a person acted immediately, or that evidence caused the price movement. Missing stages should stay missing rather than being inferred from the final paper entry.

Use the delivery ledger to diagnose configured email, Telegram, Slack, or webhook attempts separately from reviewer latency. An alert failure may explain why context did not reach a destination, while a successful delivery proves transport only. Approve or reject is authenticated in the workspace and may be blocked by the configured price-move guard. Any paper order remains a separate user-created simulation.

• Trace stored IDs across evidence, alert, and decision records.
• Do not infer human action from successful delivery.
• Preserve missing stages as explicit gaps.

Read spread and depth around both price moments

If public bid, ask, spread, and visible depth are available, record which fields describe the trigger moment and which describe the later paper-entry review. A midpoint can move because either side of the book changed, and a thin top level can disappear quickly. Comparing only two headline probabilities hides those conditions. Market-structure observations improve the explanation of the difference without turning the simulation into a reconstructed live fill.

The user supplies the paper notional. TEMIRIN’s current server checks evaluate per-order notional, rolling twenty-four-hour notional, per-market exposure, and portfolio concentration. Bid, ask, spread, and visible depth remain separately timestamped public observations. Record any manual liquidity assumption in the journal so it remains distinguishable from the implemented policy result and the paper-only simulation.

• Compare the correct market field at each moment.
• Inspect depth changes instead of midpoint movement alone.
• Label manual liquidity assumptions as reviewer notes.

Separate decision latency from market movement

Break elapsed time into observable segments: source publication to collection, collection to opportunity record, opportunity to alert attempt, and authenticated review to paper entry. Not every article will expose every clock, and a source can publish an event time that differs from its page time. Keep unavailable values blank. A single end-to-end number may look convenient, but it prevents the team from identifying whether source coverage, delivery operations, or human review deserves attention.

Interpret the price difference alongside the reason for the paper decision. A larger move may mean the reviewer waited, the market was thin, a correction arrived, or unrelated information changed participant behavior. It does not automatically mean the workflow failed. Conversely, a small difference does not prove good analysis. Use attributable notes to describe uncertainty and preserve blocked decisions, rejected records, and simulations that later marked unfavorably.

• Measure each observable interval independently.
• Leave unknown times blank instead of estimating them.
• Pair the difference with an attributable review reason.

Use the metric for process review without hindsight

Aggregate the comparison only across a clearly defined sample and period. Include positive, negative, blocked, rejected, and no-paper cases so the analysis does not become a highlight reel. Report counts and missing-data rates beside averages. Separate trigger-to-entry differences from later paper mark-to-market and from read-only public-wallet results. Those measures use different records and answer different questions; combining them can imply performance that TEMIRIN did not generate.

Journal analytics and export can support a team review of its source configuration, alert reliability, price-move blocks, and paper behavior. Improvements may include correcting an explicit market ID, clarifying a review checklist, or fixing a delivery destination. They should not be presented as guaranteed faster fills or higher returns. The metric is valuable when it makes the paper-decision timeline more understandable while preserving that every real Polymarket transaction happens elsewhere.

When presenting the metric, use a distribution rather than one average whenever the sample permits. Report median and broad ranges alongside counts of missing trigger quotes, missing book context, price-move blocks, and user-entered paper records. Break out different outcome sides only after confirming the price scale is comparable. Review individual outliers by opening their evidence, alert, decision, and paper IDs. This method can identify a slow operational stage while resisting the false precision of an execution-quality statistic built from simulations and incomplete public observations.

Document the calculation itself in the journal or export notes: paper entry minus trigger for the same outcome, along with the sign convention and observation times. If the market uses a different display unit, normalize it explicitly before comparison. Exclude any row whose market identity or side cannot be verified. A smaller valid sample is more informative than a larger average containing inverted outcomes, replaced trigger values, or paper prices copied from another contract.

Repeat the calculation from exported identifiers against a small workspace sample before presenting it. If the values differ, inspect updated market observations, corrected outcome identity, and later paper edits rather than replacing the earlier result silently. Reconciliation notes should identify the record and time responsible for the change. This keeps the metric reproducible across review meetings and prevents a refreshed dashboard from being mistaken for the original paper-decision state.

• Include unfavorable, blocked, and absent paper entries.
• Publish sample size and missing-data rates with averages.
• Keep paper analytics separate from outside wallet activity.