How to Stop Abnormal Winning Patterns: Detect & Fix Suspicious Wins

Abnormal winning patterns — a specific player winning far more than probability allows, a machine paying out at twice its expected rate, or sudden clusters of wins that coincide with specific times — are the clearest evidence of cheating in progress. This guide explains how to identify abnormal patterns, what causes them, and how to stop them for good.

What Constitutes an Abnormal Winning Pattern?

Before you can stop abnormal patterns, you need to know what “normal” looks like. Here are the benchmarks:

Win rate baseline: On a machine set to 80% hold (pays out 20% of total amount wagered over time), a fair player’s long-term win rate should converge to approximately 20%. Short-term variance means a player can win 30-40% over 10-20 games — that is normal luck. But a player who wins 70%+ over 50+ sessions is not winning by luck. The probability of 70% win rate over 50 fair games on an 80% hold machine is essentially zero.

Win amount baseline: Track win amount per session. A fair player who plays 50 credits per game and 20 games per session (1,000 credits total) should win approximately 200 credits per session on average (20% win rate). Session-to-session variance is normal (±100 credits). A player who consistently wins 500+ credits per session (50%+ effective win rate) is abnormal.

Time pattern baseline: Fair winning patterns are random — wins occur unpredictably throughout the day, across different shifts, and on different days. Abnormal patterns cluster: wins spike between 2-4 PM every day (attacker’s schedule), or wins spike every Tuesday and Thursday (attacker’s visiting pattern), or wins spike whenever a specific staff member is off duty.

Machine pattern baseline: A fair machine’s win rate across all players should approximate the configured hold percentage. If the machine’s overall win rate (total wins / total wagers) is consistently above 30% when it should be 20%, something is causing excess wins — either a configuration error (hold set too low) or cheating (payout trigger attacks).

Pattern 1: Player-Centric Abnormal Wins

Symptoms: One or a small number of players consistently win far more than probability allows.
Cause: The players are using electronic cheating devices to control game outcomes.
Detection: Extract per-player win rate data (most modern machines record this). Sort by win rate, highest first. Flag any player with >60% win rate over 20+ sessions. Cross-reference with session data — does this player also have abnormally short sessions with high win amounts?
Stop it: Install bus monitoring devices on all machines. The devices block the wireless signals the cheating players use to control outcomes. Within 1-2 weeks, the cheating players discover their equipment no longer works and leave. Their win rates disappear from the data — not because you banned them, but because their cheating stopped working.

Pattern 2: Machine-Centric Abnormal Wins

Symptoms: A specific machine shows a consistent overall win rate far above its configured hold percentage, across all players.
Cause: Either: (a) hold percentage incorrectly configured (set to 10% instead of 20%), or (b) the machine is under sustained electronic attack from multiple players.
Detection: Check the machine’s configured hold percentage in the settings menu. Compare to expected value. If hold is correct but win rate is still high, check bus monitor logs for payout trigger signals on that machine. If no bus monitor is installed, check whether the excess wins cluster around specific players (then it is player-centric, Pattern 1) or are distributed across all players (then it is a configuration or hardware issue).
Stop it: For configuration error: correct the hold percentage. For electronic attack: install bus monitoring device. For hardware issue: the machine’s mainboard or payout mechanism may be faulty — replace after ruling out other causes.

Pattern 3: Time-Centric Abnormal Wins

Symptoms: Win rates spike during specific time windows — 2-4 PM, or midnight to 2 AM, or every Tuesday afternoon.
Cause: An attacker (or group) operates on a schedule — either their personal availability, or they have identified when staff attention is lowest.
Detection: Plot win rate by hour, by day, or by shift. A fair machine should show similar win rates across all time windows (allowing for higher volume during peak hours). If a specific time window has a win rate 2-3x higher than other windows, the time window is being exploited.
Stop it: Install bus monitoring devices. The devices operate 24/7 regardless of the time. The attacker arrives at their usual time, tries their equipment, gets no response, and leaves. The time-centric win pattern disappears because the protection is always active.

Pattern 4: Intermittent Abnormal Wins

Symptoms: Win rates are normal on some days and abnormally high on others. No clear-time pattern.
Cause: Multiple attackers independently targeting the venue on different days, or a single attacker who varies their schedule to avoid detection.
Detection: Plot daily win rate over 30 days. Count the number of “spike days” (win rate >1.5x baseline). If spike days are frequent (>5 per month) and unpredictable, you have intermittent cheating.
Stop it: Install bus monitoring devices on all machines. Continuous 24/7 protection stops attacks regardless of when they occur. Within one month, spike days should drop to zero.

The Complete Stop Strategy

Step 1: Establish baselines. Measure your normal win rates — per player, per machine, per time window. You need to know what normal looks like to recognize abnormal. Track for at least 2 weeks before deploying protection (the data will also serve as a before-and-after comparison).

Step 2: Identify the pattern. Which of the four patterns matches your data? Player-centric, machine-centric, time-centric, or intermittent? The pattern tells you what kind of protection you need. Player-centric = bus monitors on all machines. Machine-centric = check configuration first, then bus monitors. Time-centric = bus monitors (active 24/7). Intermittent = bus monitors (active 24/7).

In every case, the solution is bus monitoring devices with electrical fingerprint authentication. The pattern tells you whether there are additional steps (configuration check, hardware check) but the core solution is always bus monitoring.

Step 3: Deploy bus monitors. Install one device per machine. Wait for learning period (24-48 hours). All devices should show green LED (active protection).

Step 4: Monitor the stop. Track win rates for 4 weeks after deployment. The abnormal patterns should progressively disappear. Week 1: blocked attacks in logs, win rates still abnormal (attacker still trying). Week 2: win rates start normalizing (attacker reducing attempts). Week 3-4: win rates fully normal (attacker moved on).

Step 5: Maintain vigilance. Continue to track win rates. New abnormal patterns mean new attackers testing your machines. The bus monitors will block them, but you should investigate to confirm the protection is working.

Our guide includes win rate tracking spreadsheets and abnormal pattern identification worksheets.

Common Questions

What if I cannot extract per-player win rate data from my machines?

Older machines may not record per-player data. In that case, use machine-level data (total wins / total wagers) and time-window analysis. You will not identify individual cheating players but you can identify machines with abnormal overall win rates. Deploy bus monitors on those machines.

What if the abnormal pattern returns after I deploy bus monitors?

First, verify all bus monitors are active (green LED). An inactive device is not providing protection. Second, check the configuration — has someone changed the hold percentage? Third, check for physical tampering — does the machine show signs of cabinet access? If all three checks pass, report the pattern to the bus monitor vendor for a firmware update (new attack method discovered).

How long should I track win rates before concluding the problem is solved?

At least one full business cycle (one month) with no abnormal patterns. A week of normal data could be a gap in the attacker’s schedule. A full month of normal data, covering all days of the week and all shifts, is strong evidence the problem is solved.

Abnormal Patterns Are Solvable

Abnormal winning patterns are not mysterious. They have causes — electronic attacks, configuration errors, hardware faults. Identify the pattern. Deploy bus monitoring devices. The abnormal patterns will stop. Your win rates will normalize. Your machines will earn what they should.