Solutions · Sportsbook
Sportsbook analytics.
Beyond the headline margin.
Read the margin.
Understand the mix.
Connect stakes, results and bettor activity with the context trading teams need. Compare sports, leagues and markets, investigate changes and bring risk, commercial and finance onto the same business definitions.
The sportsbook playbook
The result is one number.
The story has many parts.
Sportsbook analytics examines betting activity, market performance and player behaviour across the operation. Gamblitude helps teams compare like-for-like periods and breakdowns, so a margin change can be investigated alongside the mix of events, bet types and customers behind it.
Explain the performance mix.
Use Dashboards and Master Chart to compare stakes, GGR and margin by sport, league, market and bet type. Separate in-play from pre-match where those fields are available. Keep period, settlement status and metric definitions aligned when comparing trading results with financial reporting.
Review risk signals with context.
Set recurring checks for changes in margin, betting patterns and acceptance behaviour. Where your feeds provide open-bet and liability data, include that exposure context in the investigation. Inspect the underlying observations before deciding whether a pattern requires action from the trading team.
Connect the bettor and the business.
Use Attributes and Segments to compare betting frequency, stake distributions and product preferences. Player Profiles support individual investigation across connected records. Bring findings into Reports and compare KPIs with Targets so trading reviews can inform CRM, support and commercial planning.
For player-level CRM review, combine Player GGR Prediction with Player Churn Prediction as distinct inputs for value and disengagement risk.
The data foundation
From bet events
to shared business definitions.
Connect the data required for the agreed analysis. Align event identifiers, reporting periods, settlement rules and dimensions before comparing results. Your source feeds determine which exposure, acceptance and in-play details are available and how frequently they update.
Sources to connect
- Bet, stake and settlement records
- Sports, events, leagues, markets and bet-type dimensions
- Player, payment and bonus records
- Open-bet, liability and acceptance feeds where supplied
Metrics to define
- Stakes, settled winnings and sportsbook GGR
- Margin under agreed settlement and reporting rules
- Active bettors, bet counts and average stake
- Acceptance rates and exposure measures where supported
Example questions
Start with the question
behind the number.
Which leagues and bet types account for the change in sportsbook margin?
How do stakes, margin and acceptance patterns differ between in-play and pre-match?
Which bettor cohorts changed their activity during the latest fixture period?
AI in the workflow
Ask. Follow. Investigate.
AI Agent
Start with a trading question, inspect the supporting figures and ask for a different sport, league, market or comparison period.
Insight Radar
Choose the trading review you want repeated and when. Receive findings with the context needed to investigate.
Autonomous Agent
The agent chooses threads across the connected business data and develops related observations. The trading team evaluates the finding and owns the response.
Explore the products
The capabilities
behind the workflow.
Data Warehouse
Bring bet, settlement, payment and player records into the same analytical foundation.
Business Intelligence
Explore trading views, Reports, Targets, Segments and Player Profiles.
AI for iGaming
Ask trading questions and schedule the checks your team follows.
Autonomous Agent
See how independent investigations connect related business signals.
Predictive Models
Review the available models and their separately agreed scope.
Questions & answers
Sportsbook analytics
explained.
What is sportsbook analytics?
It is the analysis of betting activity, trading performance and bettor behaviour. Gamblitude connects operational data with governed definitions so trading, risk, CRM and finance can compare results and investigate the detail behind changes.
Can we compare sports, leagues, markets and bet types?
Yes, when those dimensions are present in the connected sources. Dashboards and Master Chart support the comparisons, while Metrics define how measures such as stakes, GGR and margin are calculated. Consistent settlement scope and periods make comparisons meaningful.
Does it support in-play and exposure analysis?
The analysis can include in-play versus pre-match and available exposure information when your feeds contain those fields and records. We agree data coverage, calculation rules and freshness during setup; open-bet visibility depends on the supplied data.
Does AI set odds, suspend markets or make risk decisions?
AI Agent, Insight Radar and Autonomous Agent investigate data and present findings. Your trading team reviews the evidence and decides what to do about pricing, limits, markets or player cases. Any downstream connection is scoped separately from the analytical finding.
How can reports and Segments support other teams?
Reports combine charts and written analysis for regular trading reviews or focused questions. Segments group bettors using agreed Attributes and conditions. CRM, support and commercial teams can then work with relevant context under their access permissions.
Which Predictive Models can we scope for a sportsbook?
The available model family includes player-value and retention applications. Each model is separately scoped and quoted, with agreed data requirements and evaluation. A market-pricing or exposure forecast would require its own assessment of the target, source history and validation.
See Gamblitude in action
Bring a trading question.
Follow the evidence.
We'll explore sportsbook performance using demo data, then discuss your source feeds, reporting rules and the questions your trading and commercial teams need to answer.