Start with clean data
A session record should include game, table, event ID, settled timestamp and outcome. Resolve duplicated or missing records before drawing charts; otherwise a data-quality issue can look like an exceptional event.
Use multiple measures
Occurrence count, missed-round streak, hit streak and deviation describe different aspects of a session. A rare category can have a long miss streak simply because its baseline probability is small.
Compare windows appropriately
A short window is useful for recent context. A long window gives a more stable observed frequency. Avoid comparing the deviation values of unrelated games without accounting for their different probabilities.
Working with the historical data
For a useful comparison, specify the recording date, timezone, game table and observation window. A historical count without those details can easily be interpreted outside the circumstances in which it was measured. Distinguish theoretical probabilities described in game rules from estimated frequencies measured in a particular data source.
Record-based tools are most useful when they make observations reproducible. If a chart cannot be reconciled with the underlying event history, it needs a data-quality review before anyone treats its values as authoritative.
Frequently asked question
What is an anomaly in this context?
It is an observation that is unusual under a defined model or historical comparison, not proof that the game will behave differently next.