End-to-end automated signal generation and delivery system for a professional betting advisory service — consuming real-time Betfair Streaming API data, applying proprietary signal logic, and pushing time-critical notifications via multiple channels within milliseconds of the trigger condition.
Goldcall's manual signal delivery process introduced 10–30 seconds of lag between a market condition being identified and a notification reaching subscribers — enough time for the price to have moved materially. Missed events during periods of inattention and no audit trail compounded the problem.
Betfair Streaming API consumer maintaining a live order-book view with LTP tracking and Weight of Money calculation, feeding a configurable signal detection engine evaluated on every market update. AWS SQS provided durable queuing with retry and dead-letter handling; Spring Boot consumers dispatched to subscriber endpoints. Every signal event written to a persistent store with full market context snapshot.
Signal-to-delivery latency dropped from 10–30 seconds (manual) to under 200ms (automated). The system has run in production without incident since deployment, covering live UK and Irish racing. Client satisfaction was unequivocal.
"Samuel built our Betfair integration and automated signal delivery system from scratch — on time, on budget, and exactly to spec. What impressed us most was how quickly he absorbed our domain requirements and translated them into a system that genuinely works in the real world of betting markets, where the edge between a good signal and a late one is everything. We'd have no hesitation bringing him back for future work."
Goldcall — Freelance — Betting Advisory & Signal DeliveryGoldcall operates a professional betting advisory service where the value of a signal is entirely dependent on the speed of delivery. In a Betfair market, a price can move from 3.0 to 2.6 in seconds. A signal that arrives ten seconds late is not just reduced in value — it is worthless.
The brief was clear: build a system that could reliably detect specific market conditions in real time, and deliver a notification to subscribers before the price moved.
Existing manual processes meant signals were identified by a human watching a screen and sent via a group messaging app. This introduced lag, missed events during periods of inattention, and no consistent audit trail. The goal was to replace the human-in-the-loop with an automated pipeline that maintained the accuracy of the signal logic while removing the latency.
Real-time market data ingestion via the Betfair Streaming API — maintaining a live, delta-updated view of the order book for target markets, with LTP tracking and Weight of Money calculation running continuously.
Signal detection engine applying configurable threshold logic — WoM imbalance triggers, LTP velocity conditions, and price compression patterns — evaluated on every market update with sub-100ms decision time.
Multi-channel delivery pipeline using AWS SQS for durable queuing and Spring Boot service consumers dispatching to subscriber endpoints — ensuring no signal was lost even under downstream delivery failure, with retry and dead-letter handling built in from day one.
Audit and replay — every signal event, with its full market context snapshot at the moment of trigger, written to a persistent store for post-hoc analysis and strategy refinement.
Delivered on time and on budget. The system has been running in production without incident since deployment, handling live racing across UK and Irish meetings. Signal-to-delivery latency dropped from 10–30 seconds (manual) to under 200ms (automated). Client satisfaction was unequivocal.