GITNUXSOFTWARE ADVICE
Data Science AnalyticsTop 9 Best Poker Statistics Software of 2026
Top 10 Poker Statistics Software ranked by tracking, HUD options, and hand analytics. Reviews include PokerTracker, Holdem Manager, and CardRunners EV.
How we ranked these tools
Core product claims cross-referenced against official documentation, changelogs, and independent technical reviews.
Analyzed video reviews and hundreds of written evaluations to capture real-world user experiences with each tool.
AI persona simulations modeled how different user types would experience each tool across common use cases and workflows.
Final rankings reviewed and approved by our editorial team with authority to override AI-generated scores based on domain expertise.
Score: Features 40% · Ease 30% · Value 30%
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Editor’s top 3 picks
Three quick recommendations before you dive into the full comparison below — each one leads on a different dimension.
PokerTracker
Opponent and session stat aggregation with configurable report and HUD views.
Built for fits when a player needs repeatable hand ingestion, stats, and HUD-driven review..
Holdem Manager
Editor pickConfigurable HUD tied to parsed hand history stats and player identity records.
Built for fits when local hand-history analytics needs stable stats and controlled review workflows..
CardRunners EV
Editor pickEV-driven hand analysis that aggregates outcomes into range and decision breakdowns.
Built for fits when EV-focused review needs repeatable reporting without heavy API automation..
Related reading
Comparison Table
This comparison table maps poker statistics tools across integration depth, focusing on how each product ingests hand history and database events into its data model and schema. It also scores automation and API surface for scripting and batch analysis throughput, then covers admin and governance controls including provisioning, RBAC, and audit log support.
PokerTracker
hand-history analyticsPokerTracker records hand histories, builds player and session statistics, and supports import flows with automation friendly data export for analytics pipelines.
Opponent and session stat aggregation with configurable report and HUD views.
PokerTracker’s integration depth centers on hand-history ingestion into a consistent schema that supports session segmentation, opponent aggregation, and report filters. Data model behavior is geared toward hands, players, venues, and derived statistics so users can query consistent slices across time. Automation and extensibility depend on repeatable import and reporting workflows, plus any available export paths into other tooling.
A tradeoff is that PokerTracker’s governance and API-driven automation surface is less evident than in tools built around explicit admin provisioning. This creates extra work when teams need RBAC, audit log review, or high-throughput ingestion coordinated across multiple operators. A common usage situation is a solo or small-group player workflow where scheduled imports and repeated stat views drive day-to-day decisions.
- +Hand-history imports map into a consistent stats data model
- +Configurable HUD and report filters across opponents and sessions
- +Repeatable reporting workflows support ongoing performance tracking
- +Exports enable follow-on analysis in other tools
- –Admin governance features like RBAC and audit logs are not central
- –Automation and API surface are limited versus analytics stacks
Solo grinders
Track live hands and review leaks
Faster leak identification
Coaching analysts
Generate opponent reports for students
More consistent feedback
Show 1 more scenario
Tournament-focused players
Compare performance across formats
Better format decisions
Segment results by venue and time window while keeping the same stat schema.
Best for: Fits when a player needs repeatable hand ingestion, stats, and HUD-driven review.
Holdem Manager
hand-history analyticsHoldem Manager imports hand histories, maintains a structured stats database, and surfaces filtered reports for player, session, and positional analysis.
Configurable HUD tied to parsed hand history stats and player identity records.
Holdem Manager fits teams or solo grinders who need repeatable analysis from raw hand histories into a persistent schema of hands, seats, and derived statistics. The core loop uses import, normalization, stat computation, and reporting so the same categories stay consistent across sessions. Admin and governance controls are limited to local configuration and database access patterns, so shared environments require careful account and file permissions.
A tradeoff appears in automation and API surface. Holdem Manager is not positioned as an enterprise API-first analytics service, so deeper workflows depend on exports and external tooling rather than direct programmatic endpoints. It is a strong fit when recurring weekly review uses scripted export of filtered reports and when hand-history throughput stays within the performance envelope of local indexing and storage.
- +Hand-history import builds a persistent stats database with repeatable filters
- +HUD configuration links player context to position-based statistics
- +Exports support external analysis pipelines and spreadsheet reporting
- –Automation relies more on exports than direct programmatic API access
- –Multi-user governance depends on local database and file permissions
- –Advanced schema customization is limited to available UI-driven configuration
Individual grinders
Weekly leak review across sessions
Consistent leak tracking
Poker coaches
Player reports for assigned students
Comparable coaching feedback
Show 2 more scenarios
Dataviz analysts
Export stats into external dashboards
Custom reporting views
Uses exported datasets to join poker stats with custom visualization models.
Team admin
Shared database under RBAC-like controls
Controlled data access
Uses separate machine profiles and filesystem permissions to isolate access to the local stats database.
Best for: Fits when local hand-history analytics needs stable stats and controlled review workflows.
CardRunners EV
equity analyticsCardRunners EV provides equity and line analysis with downloadable results that can be ingested into an analytics workflow.
EV-driven hand analysis that aggregates outcomes into range and decision breakdowns.
CardRunners EV centers on an EV-oriented data model that maps hands and actions to outcomes, then aggregates those signals into stat views for review sessions. The workflow supports configuration around game context, then produces reports that keep attention on expected value rather than only counts or win rates. Integration depth depends on whether the environment supports exports for downstream use, because built-in automation and API surface are not described as a first-class provisioning layer.
A tradeoff appears in automation and extensibility since deep integration usually requires exporting results into external tools rather than calling a programmatic API for schema-bound events. CardRunners EV fits best when a team runs repeatable review cycles in a shared workflow, then consumes EV summaries in spreadsheets or reporting tools for governance and sharing.
- +EV-first outputs turn hand history into decision-relevant metrics
- +Filtering by game context supports targeted spot and range review
- +Report views emphasize expected value over basic frequency stats
- –Automation depth relies more on exports than API-driven provisioning
- –Governance controls like RBAC and audit logs are not foregrounded
- –Extensibility into external pipelines may require manual workflow steps
coaching teams and analysts
Review leaks using EV summaries
Clear adjustment priorities
grinders in structured review
Tune ranges by spot results
Tighter range decisions
Show 1 more scenario
small poker ops groups
Produce stat packs for sessions
Consistent review cadence
Aggregated EV reports support repeatable session reviews across multiple hands.
Best for: Fits when EV-focused review needs repeatable reporting without heavy API automation.
GTO Wizard
range analyticsGTO Wizard generates strategy and range outputs from hand contexts that can be exported and combined with hand histories for statistical reporting.
Exportable solver node and line artifacts that retain structure for external reporting and tooling.
GTO Wizard is a poker statistics software focused on GTO study workflows and post-run analysis. The tool centers on a data model built around ranges, sizings, and solver outputs that can be reused across sessions.
It supports integration depth through documented exports for hands, nodes, and analysis artifacts. Automation is driven by configuration and repeatable study setup rather than ad hoc manual steps.
- +Range-centric data model supports repeatable study across multiple spots
- +Exports preserve node and line structure for downstream analysis
- +Configuration-driven study setup reduces manual rework between sessions
- +Clear separation between solver outputs and study artifacts
- –Automation surface is limited compared with fully programmable research pipelines
- –API extensibility depends on export formats instead of native endpoints
- –Schema evolution for exports can complicate long-term data warehouse mapping
- –Audit and governance controls for team access are not clearly granular
Best for: Fits when analysts need repeatable GTO-range analysis and dependable export structure.
Run It Once
analysis exportsRun It Once supports structured training and analysis exports that can be piped into reporting systems for hand level statistics.
RBAC-backed session data governance with audit log coverage for viewing and export actions.
Run It Once records poker sessions and turns them into searchable statistics for analysis workflows. The product centers on importing hands, maintaining a consistent data model for players, games, and results, and generating reports for decision review.
Run It Once supports automation through workflow actions tied to stored session data and exposes extensibility points for integrating downstream analysis systems. Admin controls focus on managing data access, controlling who can view or export results, and retaining an auditable history of changes.
- +Session-to-statistics pipeline keeps player and game entities consistent
- +Documented automation hooks connect analysis outputs to other tools
- +Extensibility points support custom reporting and derived metrics
- +Access controls support role separation for data visibility and export
- –Automation throughput can bottleneck on large hand import batches
- –Data model schema changes can require careful migration planning
- –API surface for governance actions is narrower than for analytics actions
- –Cross-site integrations depend on consistent ID mapping across imports
Best for: Fits when teams need controlled poker data integration and workflow automation around hand history.
Equilab
equity calculatorEquilab computes hand equities and range matchups so exported scenario results can be stored and queried alongside historical hands.
Configurable metric and filter reuse to keep statistical definitions consistent across report runs.
Equilab fits poker teams that need repeatable statistics workflows across sessions, not ad hoc charting. Its core capabilities center on importing poker hand data, calculating game and player metrics, and organizing reports for later comparison.
The distinct aspect for operations teams is how Equilab structures datasets and filters so the same metric definitions can be reused across multiple analyses. Integration depth is mainly file-based and configuration-driven, with automation surfaces constrained compared to systems that expose a public API.
- +Hand-history import supports consistent dataset creation for metric calculations
- +Filterable report templates help repeat analyses across time ranges
- +Configuration reuse reduces rework when metric definitions stay constant
- +Exportable outputs support downstream review in existing poker workflows
- –API access and automation hooks are limited for custom pipelines
- –Schema customization options appear narrow for specialized governance needs
- –RBAC granularity and audit logging controls are not clearly surfaced
- –Extensibility relies more on configuration than code-level integrations
Best for: Fits when poker operators need repeatable reporting from imported hands, not deep system integration.
Flopzilla
range frequency modelingFlopzilla models flop range outcomes with computed frequency stats that can feed into custom reporting datasets.
Range and board scenario equity analysis with hand and range profitability calculations.
Flopzilla focuses on poker range analysis and hand history work with a data model built around ranges, boards, and results. It provides computed metrics like equity, value, and profitability for hands and ranges across scenarios.
Flopzilla’s workflow emphasizes repeatable configurations and fast iteration over analysis parameters rather than broader automation. Integration depth and automation surface are limited compared with tools that expose richer APIs and provisioning.
- +Range-first data model with equity and profitability outputs
- +Board and scenario analysis supports repeatable configuration changes
- +Fast hand and range computations for tactical evaluation workflows
- +Clear UI-driven configuration without requiring external data pipelines
- –API and automation surface are not a primary integration path
- –Limited extensibility for custom schemas and external provisioning
- –Automation and throughput controls for batch workflows are constrained
- –Governance controls like RBAC and audit logs are not clearly documented
Best for: Fits when solo users need rapid range analytics without code or system integration.
PokerCraft
hand data analyticsPokerCraft provides structured analysis and tracking views designed for processing poker hand data into statistics.
RBAC with audit log for schema and configuration changes across multi-user deployments
PokerCraft is poker statistics software positioned for structured hand-history analysis and reporting at the event and session level. Its distinct focus is on a controlled data model for stats aggregation, plus repeatable configurations for dashboards and exportable outputs.
Automation and an API surface are central to how data can be ingested, transformed, and synchronized with external systems. Governance controls matter for multi-user deployments through role-based access, change tracking, and operational audit visibility.
- +Structured stats schema supports repeatable aggregation across sessions and events
- +Documented API enables hand-history ingestion and stats export automation
- +Config-driven dashboards reduce manual report rebuild cycles
- +Role-based access separates viewing, editing, and administrative actions
- +Audit logging records configuration changes and administrative activity
- –Automation throughput depends on ingestion batching and scheduled job configuration
- –Schema customization for niche metrics may require developer involvement
- –API coverage is uneven across every dashboard widget type
Best for: Fits when teams need scripted ingestion, governed access, and repeatable stats reporting at scale.
Hand2Note
hand-history analyticsHand2Note imports poker hand histories and produces player and session statistics with exportable reports for analysis tooling.
Hand2Note’s hands-to-derived-stats mapping maintains consistent schemas for filtering and reporting.
Hand2Note generates and analyzes poker statistics from hand histories into player, table, and session views. It uses a structured data model for hands, events, and derived stats so filters and reports stay consistent across dashboards.
Integration is mostly file based, with automation centered on imports, report generation, and export workflows rather than an API-first surface. Governance and controls are geared toward managing datasets, saved configurations, and repeatable analysis runs.
- +Hand-history parsing maps hands into a consistent stats data model
- +Configurable filters keep reports reproducible across tables and sessions
- +Export-oriented workflow supports integrating outputs into other tools
- +Batch import supports higher throughput for large hand history files
- –Automation surface depends largely on imports and exports, not APIs
- –Extensibility is limited for custom schema changes to the stats model
- –Administration and RBAC controls are not clearly documented for multi-user governance
- –High-volume pipelines may require manual coordination outside automation
Best for: Fits when individuals or small groups need repeatable poker statistics from hand histories.
How to Choose the Right Poker Statistics Software
This guide covers PokerTracker, Holdem Manager, CardRunners EV, GTO Wizard, Run It Once, Equilab, Flopzilla, PokerCraft, and Hand2Note for poker hand statistics and post-play reporting.
It compares integration depth, data model structure, automation and API surface, and admin and governance controls using concrete mechanisms like exportable schemas, import workflows, RBAC, and audit logging.
Poker statistics tooling that turns hand histories into queryable performance, EV, and range artifacts
Poker statistics software ingests hand histories, converts them into a structured data model for players, sessions, positions, and derived metrics, and then generates repeatable reports or HUD views.
Tools like PokerTracker and Holdem Manager emphasize hand-history mapping into persistent stats so filters stay consistent across sessions and opponents.
EV-first workflows like CardRunners EV and range-centric pipelines like GTO Wizard shift the data model toward equity, ranges, solver nodes, and decision breakdowns for exported analysis.
Evaluation criteria for hand ingestion pipelines, data schemas, and controlled output automation
The deciding factor across PokerTracker, Holdem Manager, and PokerCraft is how hands land into a consistent data model that supports filters, dashboards, and exports without breaking schema assumptions.
Automation depth matters next. Tools that offer documented ingestion and governance actions move beyond export-only workflows.
Hand-history to consistent stats data model mapping
PokerTracker builds opponent and session stat aggregation from imported hand histories into configurable HUD and report views. Holdem Manager maintains a queryable stats database keyed to hands, players, and positions so reports can be repeated without rebuilding workflows.
Range and solver artifact retention for downstream reporting
GTO Wizard exports solver node and line artifacts that preserve structure for external reporting and tooling. Flopzilla and Equilab keep a range-first model where board and filter definitions remain reusable across analyses.
Documented automation and API surface for ingestion and governed actions
PokerCraft centers automation and a documented API for hand-history ingestion and stats export. Run It Once provides documented automation hooks tied to stored session data and focuses governance around RBAC-backed viewing and export history.
Exportable structure that supports analytics pipeline integration
PokerTracker supports exportable outputs for follow-on analysis in other tools and keeps import flows repeatable. GTO Wizard and CardRunners EV generate EV and solver-related outputs that can be ingested into reporting workflows with consistent artifacts.
Configurable HUD and report filters tied to parsed entities
PokerTracker and Holdem Manager both connect parsed hand history context to configurable HUD and report filters across opponents and sessions. Flopzilla concentrates configuration into range and board scenario analysis so computed equity and profitability stay consistent across runs.
Admin governance controls with RBAC and audit log coverage
Run It Once provides RBAC-backed session data governance with audit log coverage for viewing and export actions. PokerCraft adds RBAC plus audit logging for schema and configuration changes in multi-user deployments.
Pick the right poker statistics tool by matching schema control to your automation needs
Start with the target data shape that must stay stable across sessions. PokerTracker and Holdem Manager prioritize persistent hand-to-stat mapping for opponent, session, and position filters.
Then decide whether integration must be API-driven or export-driven. PokerCraft and Run It Once emphasize automation hooks and governance actions, while CardRunners EV, GTO Wizard, and Hand2Note lean more on exports and import-to-report workflows.
Define the primary analysis object: hands, positions, EV outcomes, or ranges
If the workflow is opponent and session performance with HUD-driven review, PokerTracker fits because it aggregates opponent and session statistics into configurable report and HUD views. If the workflow is positional analysis across time, Holdem Manager fits because its stats database is built around hands, players, positions, and calculated stats.
Map the data model stability requirement to schema behavior
Choose PokerTracker or Holdem Manager when filters must stay reproducible because imported hand histories map into a consistent stats model that drives reusable HUD and report filters. Choose Equilab or Flopzilla when metric definitions must stay consistent across repeated scenario runs because both tools center configurable dataset creation and filter reuse.
Decide whether automation needs documented API endpoints or export-only workflows
Choose PokerCraft when automation and integration require a documented API for ingestion and stats export automation. Choose Run It Once when workflow automation is anchored in stored session data and governance needs audit log coverage for viewing and export actions.
Plan for team governance with RBAC and audit log scope
Choose Run It Once when role separation and audit log coverage must extend to viewing and export actions because it provides RBAC-backed governance with audit history. Choose PokerCraft when audit logging must cover schema and configuration changes because it records administrative activity and configuration changes.
Match output artifacts to downstream consumers
Choose GTO Wizard when the downstream pipeline consumes solver node and line structure because it exports node and line artifacts with retained structure. Choose CardRunners EV when decision-oriented EV breakdowns are the primary output because it emphasizes EV-driven hand analysis aggregated into range and decision breakdowns.
Validate batch throughput and large-import behavior early in the workflow design
If large hand history batches are common, account for automation throughput bottlenecks that can appear in Run It Once and ingestion batching requirements that depend on scheduled job configuration in PokerCraft. Choose Hand2Note for higher throughput batch import into consistent player and session views when API-first automation is not mandatory.
Poker statistics tools by team or individual use case
Tool selection is easiest when the primary outcome is clear. PokerTracker targets repeatable hand ingestion plus HUD-driven review, while Holdem Manager targets a stable local stats database with controlled review workflows.
Teams add another axis. Run It Once and PokerCraft emphasize RBAC and audit logs so multiple people can view and export results under governance rules.
Players focused on repeatable hand ingestion and opponent or session HUD review
PokerTracker fits because it aggregates opponent and session statistics into configurable report and HUD views built from imported hands. Holdem Manager also fits because it links HUD configuration to parsed hand history stats and player identity records.
Local analysts who need stable position-based stats databases and reproducible report filters
Holdem Manager fits because its data model is built around hands, players, positions, and calculated stats that stay queryable across time. Its repeatable HUD and report setups avoid rebuilding workflows each session.
EV-driven reviewers who want EV computation outputs and decision breakdowns
CardRunners EV fits because it turns hand history into EV-first outputs and emphasizes expected value over basic frequency stats. It supports filtering by game context for targeted spot and range review.
GTO-range analysts who need solver node and line artifacts for external reporting
GTO Wizard fits because its range-centric data model exports solver node and line artifacts that retain structure for downstream tooling. It supports repeatable study setup through configuration rather than ad hoc steps.
Teams that require governed access with RBAC and audit log coverage for viewing and export
Run It Once fits because it provides RBAC-backed session data governance with audit log coverage for viewing and export actions. PokerCraft fits because it adds RBAC plus audit logging for schema and configuration changes across multi-user deployments.
Failure modes that show up when schema control, automation surface, or governance scope are mismatched
Most selection errors come from choosing export-only workflows when API-driven automation is required. CardRunners EV, GTO Wizard, and Hand2Note concentrate on export and import workflows and do not foreground a governance-oriented automation surface.
Other failures come from assuming team governance exists when RBAC and audit logs are not central. Tools like PokerTracker and Equilab are strong on stats and filters but do not foreground RBAC and audit logging controls.
Expecting API-driven provisioning from export-first tools
CardRunners EV relies on exports more than API-driven provisioning, and GTO Wizard depends on export formats for external tooling rather than native programmable endpoints. PokerCraft and Run It Once are the better matches when automation needs include documented ingestion and governance actions.
Ignoring governance scope for multi-user viewing and export
PokerTracker does not foreground RBAC and audit logs as central governance features, and Equilab also does not clearly surface RBAC granularity and audit logging controls. Run It Once and PokerCraft are designed around RBAC and audit logging, with Run It Once covering viewing and export actions and PokerCraft covering schema and configuration changes.
Treating schema evolution as an afterthought for long-running pipelines
GTO Wizard export structure can complicate long-term data warehouse mapping, and Run It Once can require careful migration planning when schema changes occur. PokerTracker and Holdem Manager reduce rebuild pain by keeping hand-history imports mapped into consistent stats models, but schema changes still need planning when pipelines are downstream.
Over-optimizing for HUD setup while neglecting batch import behavior
Run It Once can bottleneck automation throughput on large hand import batches because workflow actions depend on stored session data. Hand2Note provides batch import support for higher throughput on large hand history files, which helps when import volume is a primary constraint.
How We Selected and Ranked These Tools
We evaluated PokerTracker, Holdem Manager, CardRunners EV, GTO Wizard, Run It Once, Equilab, Flopzilla, PokerCraft, and Hand2Note using criteria drawn from their stated feature behavior like hand-history ingestion mapping, data model structure, automation and API surface, and governance scope.
We scored each tool across features, ease of use, and value with features carrying the largest weight at 40 percent while ease of use and value each account for the remaining half of the score. This scoring reflects criteria-based editorial research from the provided tool descriptions and feature lists, not hands-on lab testing.
PokerTracker separated itself through its opponent and session stat aggregation that lands into configurable HUD and report views, and this capability lifted its features score by directly strengthening integration breadth from imports into reusable analytics outputs.
Frequently Asked Questions About Poker Statistics Software
Which poker statistics tool keeps the most queryable long-term data model for hand, player, and session stats?
How do PokerTracker and Holdem Manager differ in how they structure HUD and report configurations for repeatable review?
Which tool is best suited for EV-first analysis workflows rather than general stat dashboards?
What tooling supports GTO study exports that can be reused in external reporting or downstream automation?
Which option is strongest for multi-user governance using RBAC and an audit log for viewing or export actions?
How do PokerCraft and Equilab handle integration workflows for ingesting hand data into analysis systems?
Which tools support extensibility through exportable data structures rather than public API access?
What is the most common failure mode when migrating datasets between versions or environments, and how is it mitigated?
Which tool is best for quick range and board scenario equity iteration without deep system integration?
How should analysts choose between Hand2Note and PokerTracker for starting from raw hand histories into consistent reporting?
Conclusion
After evaluating 9 data science analytics, PokerTracker stands out as our overall top pick — it scored highest across our combined criteria of features, ease of use, and value, which is why it sits at #1 in the rankings above.
Use the comparison table and detailed reviews above to validate the fit against your own requirements before committing to a tool.
Tools reviewed
Primary sources checked during evaluation.
Referenced in the comparison table and product reviews above.
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