Revenue Forecasting
Data source:
Projected Revenue (Next 90d)
$1.47M
+11.2%
Avg Forecast Accuracy
91.4%
+2.1%
Projected Attendance
62,300
+4.8%
Demand Confidence
High
P75–P90
Revenue Forecast — Bull / Base / Bear
BullBaseBear
Shaded region = forecast uncertainty window. Dashed line = current month.
Attendance Forecast
Actual vs. model prediction
Forecast Confidence Intervals
vs. Orlando City — Apr 12
High
$430K
$545K
Base: $487K
vs. Nashville SC — Apr 19
Medium
$355K
$468K
Base: $412K
Inter Miami — Apr 26
High
$455K
$580K
Base: $510K
How these forecasts are calculated
Revenue Forecast (Bull / Base / Bear)
Base: Your median event revenue from uploaded data, projected forward at the same event cadence.
Bull (+15%): Assumes your best-performing events this season repeat - strong opponent, good weather, effective marketing.
Bear (-12%): Assumes some events underperform due to weather, scheduling conflicts, or lower opponent demand.
Confidence Intervals by Event
High confidence: Events with similar historical matchups in your data. The range is tighter because we have more reference points.
Medium confidence: Events with fewer historical comparisons. The range is wider to reflect greater uncertainty.
Avg Forecast Accuracy (91.4%): Industry benchmark for sports demand models with 1+ seasons of data. Your accuracy will improve as more data is collected.
Projected Attendance
Average paid tickets per event multiplied by estimated events in the next 90 days. Excludes complimentary tickets to show true market demand.
Demand Confidence Level
Based on how many events are in your dataset. 10+ events = High. 5-9 events = Medium. Under 5 = Low. More historical data means narrower confidence intervals and better forecasts.