GITNUXSOFTWARE REVIEW
Video Games And ConsolesTop 10 Best Poker Simulation Software of 2026
Top 10 list compares poker simulation software tools, with practical notes for training and strategy work across Equilab, PokerSnowie, and GTO Wizard.
How we ranked these tools
Vendors set the topic, but our editors set the inclusion criteria and the evaluation framework before research starts.
Search agents gather the source set and the review record, including transcriptions of video reviews and podcasts.
Framework: Features 40% · Ease 30% · Value 30%
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Equilab is the best pick for range-driven players who want clean matchup insight because it delivers fast equity distribution graphs showing win and chop frequency across runouts, whereas PokerSnowie is better for structured practice since its opponent-driven debrief loops turn hand mistakes into targeted next drills.
Editor’s top 3 picks
Three quick recommendations before you dive into the full comparison below — each one leads on a different dimension.
Equilab
Equity distribution graphs that show win and chop frequency across runouts for a defined range matchup.
Best for: Fits when range-based equity checks and hand-history review drive preflop decisions.
PokerSnowie
Editor pickOpponent-driven training with action-level debrief loops that convert mistakes into targeted repetition.
Best for: Fits when structured practice and fast post-session debrief matter more than deep solver inspection.
GTO Wizard
Editor pickHand history import paired with decision-tree editing so real hands map to solvable nodes for rapid iteration.
Best for: Fits when analysts want interactive GTO study driven by hand histories and range versus range comparison.
Comparison Table
Equilab
vertical specialistFree poker equity calculator.
Equity distribution graphs that show win and chop frequency across runouts for a defined range matchup.
Equilab’s core workflow centers on selecting a hero hand or hand range, defining one or more villain ranges, and generating equity results across boards. Range vs range analysis and hand matrix views make it practical for comparing scenarios like different open sizes and call ranges before moving into deeper solver work. Equity distribution graphs help interpret how often hands win, lose, or chop across runouts.
A key tradeoff is that it targets enumeration-style equity rather than game-theoretic strategy trees with node locking and counterfactual regret minimization. It fits best when reviewing hand histories and refining range assumptions for exploitative strategy discussions, or when checking simple matchup math before committing to a solver run.
- +Fast range vs range equity calculations with clear visual outputs
- +Hand matrix and equity distribution graphs for quick scenario comparisons
- +Practical range construction workflow for multiple villain hand classes
- +Hand history import to validate assumptions against real lineups
- –Equity-centric outputs do not produce action EV across full decision trees
- –Limited support for multi-street strategy modeling compared with GTO solvers
Tournament players reviewing spots
Validate preflop calls vs opening ranges
Cleaner call or fold decisions
Coaches building training materials
Illustrate matchup effects by range
Repeatable examples for students
Show 1 more scenario
Cash game grinders
Stress-test frequent steal and defend ranges
More accurate range calibration
Use fast enumeration to estimate equity shifts when ranges widen or tighten by position.
Best for: Fits when range-based equity checks and hand-history review drive preflop decisions.
PokerSnowie
vertical specialistNeural network poker coach and analysis tool.
Opponent-driven training with action-level debrief loops that convert mistakes into targeted repetition.
PokerSnowie’s core loop centers on playing against simulated opponents and immediately reviewing the decisions in context of stack depth and board runouts. The tool provides feedback at the level of actions taken, then organizes follow-up study around repeatable mistakes rather than isolated lessons. Hand history import lets users bring real sessions into the same analysis flow.
A key tradeoff versus solver-first tools is that PokerSnowie emphasizes training and coaching-style feedback over transparent solver computations with a user-controlled compute model. It fits best when a daily practice cadence matters more than reproducing a specific GTO output for a custom node or frequency script, especially for fast post-session review.
- +Hand history import feeds the same review workflow as training hands
- +Immediate post-hand feedback ties actions to concrete next-step drills
- +Replay-based practice supports consistent scenario repetition
- +Opponent simulations provide varied lines for patterning decision instincts
- –Solver-style inspectable outputs are not the primary focus
- –Extensive custom node control is limited compared with full solvers
Tournament grinders
Review busting hands after sessions
Fewer repeat errors
Cash game regulars
Drill common stack-depth scenarios
More consistent lines
Show 2 more scenarios
Coaches
Standardize student practice debriefs
Simpler coaching cadence
Imported hands create uniform review sessions that support structured follow-up drills for groups.
Multi-tabling players
Fast playback of key hands
Faster learning cycles
Hand history import enables quick scenario replay and focused review after high-volume sessions.
Best for: Fits when structured practice and fast post-session debrief matter more than deep solver inspection.
GTO Wizard
vertical specialistWeb-based GTO solver and poker strategy simulator with cloud-computed Nash equilibrium solutions.
Hand history import paired with decision-tree editing so real hands map to solvable nodes for rapid iteration.
GTO Wizard computes preflop and postflop GTO solutions and presents them as interactive decision trees that help compare lines for range vs range work. It supports hand history import and parsing, so analysis can be anchored to real hands and not only static inputs. It also includes board and runout analysis for equity and EV inspection across different action paths.
A concrete tradeoff is that the workflow centers on solver-style outputs and decision-tree review rather than building a long-term player database. This setup fits tournament players and coaches when tournament payout pressure changes how shove and call lines should be evaluated. It also fits players who want repeatable scenario review from recurring spots tied to specific hand histories.
- +Interactive node-based exploration for line-by-line what-if analysis
- +Hand history import workflow reduces manual range reconstruction
- +Runout and board texture tooling helps trace EV through streets
- +Range vs range comparisons with clear action outcomes
- –Large solve trees can slow iteration without careful node planning
- –Multiway modeling depth depends on scenario setup discipline
Tournament players and coaches
ICM-aware equity review for shoves
Better tournament decision choices
Poker students
Drill recurring decision nodes
Faster pattern recall
Show 2 more scenarios
Poker coaches
Assign tasks from student hands
More consistent coaching material
Map student hands to reusable nodes and compare solver outputs to create targeted review assignments.
Omaha players and coaches
Analyze all-in equities by street
Clear Omaha line comparisons
Study Omaha ranges, boards, and action trees to compare street-by-street equity outcomes.
Best for: Fits when analysts want interactive GTO study driven by hand histories and range versus range comparison.
PokerTracker 4
vertical specialistPoker tracking, analysis, and HUD software.
Advanced hand history import plus database-backed stat filtering for targeted equity and opponent spot review.
PokerTracker 4 centers on hand history import, then turns parsed data into searchable reports and opponent statistics by position, street, and bet sizing patterns. It can calculate equity breakdowns for filtered hands and generate visual summaries that make it easier to find which situations are driving outcomes. The integration depth comes from how widely compatible its hand history workflows are with common poker clients and how the tool connects imported data to dashboards and filters.
- +Hand history parsing powers fast, repeatable filters for opponent and spot review
- +Opponent stats and reports support both cash game and tournament review workflows
- +Equity and range-oriented analysis tools integrate directly with tracked hands
- +Large database querying makes session debriefs quicker than spreadsheet workflows
- –Stat accuracy depends on clean hand history imports
- –Solver-style node analysis and abstraction controls are not built into the core tool
- –Automation surface for external systems is limited compared with full analysis suites
- –Complex multi-table tagging and aliases can require careful setup discipline
Tournament grinders
Review ICM-sensitive spots by filtered hands
Faster leak identification by scenario
Cash game regulars
Track bet sizing patterns versus players
More consistent exploit adjustments
Show 1 more scenario
Coaching teams
Standardize session review across students
Consistent feedback across matches
Reuse saved filters and reports to generate comparable debrief artifacts by player pool.
Best for: Fits when post-session analysis needs strong database filtering and opponent tendency tracking.
Holdem Manager 3
vertical specialistPoker tracking and analysis software.
Configurable HUD and report stat definitions that stay consistent from live overlay to post-session databases.
Holdem Manager 3 turns captured poker hand histories into an analysis workflow with a HUD, detailed hand reports, and searchable databases. It focuses on tournament and cash tracking, then connects results to player-level stats and leak detection through configurable reports.
- +Automated hand history import and database organization for fast session review
- +Highly configurable HUD stats and report filters for targeted player analysis
- +Detailed hand replayer and stat-linked breakdowns for cause-and-effect review
- +Strong support for multi-table sessions via HUD integration and layout control
- –Requires stat and HUD configuration work before it reflects intended strategy
- –Solver-style tree analysis is not built in for counterfactual regret computations
- –Database performance depends on import completeness and consistent hand history formats
- –Advanced range modeling workflows need external tools for simulation
Serious poker students
Audit decisions against likely ranges
Structured spot validation
Frequent poker players
Measure performance trends by spot
Longitudinal performance visibility
Show 2 more scenarios
Poker coaches
Create weakness-focused review sets
Targeted review materials
Organize filtered hands and reports around student weaknesses for focused coaching discussions.
Online poker players
Identify recurring decision leaks
Prioritized leak list
Filter recent hands and scan reports for repeated mistakes and weak decision patterns.
Best for: Fits when frequent hand history review and HUD-driven player profiling matter more than solver execution.
PokerRanger
vertical specialistPokerRanger calculates poker equities across ranges, board textures, and multiway scenarios.
Hands-to-scenarios workflow that links imported sessions to range comparison outputs for rapid iteration.
PokerRanger is a poker simulation software centered on workflow-driven hand analysis, from importing hands to running solver-style outputs. It supports range vs range review and equity reporting for common decision points in both tournament and cash contexts.
- +Fast loop from hand import to scenario-specific range comparisons
- +Range vs range comparisons with clear equity-focused outputs
- +Tournament oriented workflows that match practical study sessions
- +Board and runout handling geared toward common training use cases
- –Best results depend on clean hand histories and consistent formats
- –Advanced customization can feel limited versus full solver ecosystems
- –Less direct support for multiway edge cases than specialized solvers
- –Requires disciplined range construction to avoid misleading equity reads
Tournament grinders
Iterate range vs range hands
Repeatable review loops
Cash game regulars
Check equity for common decisions
Faster equity spot checks
Show 2 more scenarios
Coaching groups
Standardize analysis outputs per hand
Consistent coaching workflow
Turn multiple sessions into repeatable analysis artifacts for consistent feedback and follow-up.
Players using solver outputs
Refine assumptions across scenarios
Tighter range assumptions
Iterate across hands, boards, and ranges by re-running the analysis outputs for each scenario.
Best for: Fits when frequent hand review needs repeatable scenario simulation without building a full modeling stack.
Flopzilla
vertical specialistFlopzilla evaluates flop textures, hand distributions, equities, and range combinations.
Board texture and equity distribution visualization driven by blockers and range exclusion during flop selection.
Flopzilla is poker simulation software focused on range versus range hand reading using a flop-first workflow and fast equity visualization. It supports interactive range building with blockers and hand exclusion, then maps results onto equity distribution and board texture views.
- +Range versus range workflows stay fast and visual on flop scenarios
- +Hand selection and exclusion features make blocker-driven analysis practical
- +Equity distribution views help validate assumptions about range strength
- +Hand history import supports converting live hands into study targets
- –Depth past flop analysis is limited compared with full postflop solvers
- –Automation and API tooling is minimal for large-scale, programmatic study runs
- –Multiway pot modeling and advanced node locking style analysis are not the focus
- –Setup requires careful range definition discipline to avoid misleading outputs
Self-directed learners
Rebuild ranges from recorded hands
Repeatable mistake review
Poker coaches and study groups
Teach range building with board categories
Concrete range examples
Show 2 more scenarios
Exploit-focused players
Test adjusted opponent range assumptions
Evidence-backed exploit tweaks
Compare realistic and modified opponent ranges against chosen boards and runouts.
Postflop poker students
Assess turn impacts on equity
More consistent turn assumptions
Examine how a turn card shifts equity, hand classes, and combination counts for turn decisions.
Best for: Fits when flop-centric range analysis needs quick equity answers for coaching and study sessions.
RangeConverter
vertical specialistRangeConverter converts and analyzes poker hand ranges for study and equity comparison.
Format-specific range adapters that normalize inputs into solver-consumable structures with batch consistency.
RangeConverter converts poker range inputs into solver-ready representations for downstream analysis pipelines. It supports range normalization and transformation workflows that reduce manual editing when moving between tools that expect different formats.
- +Batch conversion for many villain ranges in one run
- +Deterministic transformations that keep range semantics consistent
- +Format adapters that reduce manual re-entry errors
- +Works well as a preprocessing step before solver ingestion
- –Limited coverage for solver-side tasks like node locking
- –Conversion quality depends on correct input assumptions
- –Automation depth is constrained for custom pipelines
- –No built-in tournament simulation engine for ICM model work
Range-focused analysts
Convert ranges for range vs range study
Fewer manual formatting steps
Study group facilitators
Batch-convert multiple range sets
Consistent study inputs
Show 1 more scenario
Toolchain users
Normalize outputs between applications
Cleaner cross-tool workflows
Reduce editing by converting ranges into formats required by downstream equity and range tools.
Best for: Fits when teams need repeatable range-format conversions feeding solvers and equity calculations.
GTOBase
vertical specialistGTOBase offers a searchable library of poker solutions with range and strategy analysis.
Board-linked equity distribution views that turn precomputed outputs into quick, scenario-specific post-hand review.
GTOBase focuses on making stored solver outputs reusable for day-to-day study and analysis, not on running new solvers inside the UI. The workflow centers on building and inspecting range vs range outputs, then drilling into equity distributions and board-specific outcomes.
- +Range vs range views keep analysis grounded in concrete solver outputs
- +Equity distribution and runout-style inspection speed up decision review
- +Hand history import plus parsing supports repeatable review workflows
- +Board-specific breakdowns reduce manual re-analysis for common scenarios
- –Limited room for custom solver settings compared with full solver environments
- –Deep multiway tuning and advanced node controls are not the main workflow
Daily solver users
Reuse stored range outputs
Faster study sessions
Players reviewing hands
Map hand histories to study models
Hand-to-model alignment
Show 2 more scenarios
Analysis teams
Keep outputs consistent across sessions
Repeatable team study
Use stable precomputed solution views so teams review the same range frameworks over time.
Range vs range learners
Drill equity on specific board textures
Board-aware understanding
Inspect board-specific outcomes to refine how range assumptions hold on different runouts.
Best for: Fits when precomputed GTO study outputs must be replayed against hands with fast inspection.
Simple Poker
vertical specialistSimple Poker provides postflop and preflop solving software for range-based cash game analysis.
Board runout enumeration tied to range inputs produces showdown distributions for quick scenario validation.
Simple Poker targets poker simulation workflows with a focus on preflop-to-showdown calculations that support range-based decision making. The software emphasizes fast scenario iteration, including multiway pot handling and board runout enumeration for equity and outcome checks.
- +Range vs range equity checks work well for rapid study iterations
- +Multiway pot support matches real live-table dynamics more closely
- +Board runout enumeration provides concrete showdown outcome distributions
- +Tournament modeling supports stack depth and structure variations
- –Solver-style CFR work and node locking style controls are not the core workflow
- –Automation and API surface for pipeline integration are limited
- –Hand history import depth is constrained versus specialized HH parsers
- –Advanced exploit research tools like population tendency models are thin
Players reviewing online sessions
Revisit decisions from hand histories
Situation-organized study
Players wanting in-hand guidance
Get recommendations during the hand
Contextual decision support
Show 2 more scenarios
Players tracking progress
Inspect results by opponent and situation
Pattern visibility for follow-up
Use statistical summaries and situation-level views to spot patterns across hands and opponents.
Tournament players
Practice ICM and push-fold spots
Focused tournament preparation
Run tournament-oriented modeling to stress-test decisions across different stack depths and field structures.
Best for: Fits when range-based equity and tournament outcome checks need fast iteration without solver graph management.
Conclusion
After evaluating 10 poker simulation software, Equilab 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.
How to Choose the Right Poker Simulation Software
This buyer's guide covers poker simulation software used for range vs range analysis, hand history driven review, and decision study loops. It focuses on ten tools that include PokerSnowie, Equilab, ICMizer coverage, and PioSOLVER coverage alongside more workflow-specific options.
Coverage starts after each tool review, so the narrative emphasizes how analysis outputs get generated from inputs like ranges, board states, and imported hand histories. The sections below connect those mechanics to integration depth, automation behavior, and operational control signals seen across PokerSnowie, PokerTracker 4, Equilab, and Holdem Manager 3.
Poker Simulation Software for range-based analysis, hand history review, and solver-style decision study
Poker simulation software models poker outcomes by combining range inputs with board and action structure to compute equity distributions, showdown results, and decision-relevant outputs. Tools like Equilab center on equity distribution graphs and runout visualization for defined range matchups and fast preflop scenario checks.
Solver-style workflows use more structured decision trees and line-by-line iteration, so they map hand histories into solvable nodes for what-if changes rather than only producing equity summaries. PokerSnowie targets opponent-driven training loops that turn hand history review into immediate action-level debriefs, while PokerTracker 4 emphasizes database-backed hand history parsing and repeatable opponent and spot filters for follow-up study.
Range-to-decision workflow features that change real analysis output
Poker simulation software matters most at the moment inputs become decision-ready outputs, like mapping hand histories into editable nodes or converting defined ranges into runout distributions. Tools in this set differ by what they compute, how they present it, and how fast a workflow can move from import to scenario inspection.
Hand history import fidelity and downstream review loop
PokerSnowie turns hand history import into immediate action-level debrief loops that drive targeted repetition after each reviewed hand. PokerTracker 4 emphasizes hand history parsing plus database-backed stat filtering for opponent spot review across cash game and tournament workflows.
Solver-style decision-tree iteration from imported hands
GTO Wizard couples hand history import with decision-tree editing so real hands map into solvable nodes for rapid what-if iteration. PokerSnowie supports line-by-line training debriefs, but extensive custom node control is limited compared with full solver-style environments.
Equity visualization for range vs range and runout outcomes
Equilab centers on equity distribution graphs that show win and chop frequency across runouts for a defined range matchup. Equilab also pairs hand matrix views and equity distribution graphs for quick scenario comparisons, while Simple Poker uses board runout enumeration tied to range inputs for showdown distributions.
Multi-street strategy depth versus fast equity checks
GTO Wizard and PokerSnowie support deeper decision study loops through node-based iteration instead of only equity snapshots. Simple Poker and Flopzilla deliver faster flop- or board-centric analysis, but depth past flop and solver-style CFR node controls are limited.
Precomputed output replay versus custom solver setup
GTOBase focuses on board-linked equity distribution views that replay precomputed study outputs into quick, scenario-specific post-hand review. PokerSnowie and GTO Wizard prioritize interactive iteration, while GTOBase leaves fewer options for custom solver settings.
Automation surface for pipeline-style study runs
PokerSnowie and PokerTracker 4 emphasize workflows built around imports and repeatable review logic. Simple Poker and Flopzilla show limited automation and API surface, which constrains pipeline integration for large-scale programmatic study runs.
Choose by the workflow stage that must be fast and decision-ready
The right poker simulation software depends on whether the workflow bottleneck is importing hands, translating ranges into board/runout outcomes, or iterating through decision trees. The options here split into training-first loops, database-first analysis, equity-visualization tools, and solver-style node editing tools.
If hand review needs action-level training drills, prioritize PokerSnowie
Select PokerSnowie when the workflow goal is to convert mistakes into targeted repetition with immediate post-hand feedback tied to concrete next-step drills. This fit comes from its opponent-driven training loop that uses hand history import directly inside the review workflow.
If opponent profiling depends on database filtering, choose PokerTracker 4
Choose PokerTracker 4 when post-session analysis requires repeatable stat filters and opponent tendency tracking built on hand history parsing. This path pairs well with cash game and tournament review workflows where database-backed filtering drives what gets studied next.
If the core output is range vs range equity across runouts, pick Equilab
Pick Equilab when the decision workflow is grounded in equity distribution graphs that show win and chop frequency across runouts. Use its hand matrix and equity distribution outputs for scenario comparisons, especially for preflop range decisions where full decision trees are not the bottleneck.
If solvable nodes must be edited from real hands, choose GTO Wizard
Select GTO Wizard when real hands need mapping into solvable nodes so line-by-line what-if edits can happen quickly. This step is different from equity-only tools because it depends on decision-tree editing and interactive node exploration.
If fast scenario validation beats solver control, use Simple Poker
Choose Simple Poker when range-based equity and tournament outcome checks require quick board runout iteration without managing solver graph complexity. The board runout enumeration tied to range inputs supports multiway pot work, while solver-style CFR and node locking style controls are not the core workflow.
Who benefits from each workflow style
Poker simulation software fits different study habits because each tool emphasizes a different conversion step from inputs into decision outputs. The best match depends on whether the daily work is training debriefs, database-driven opponent review, equity visualization, or node-based solver iteration.
Players who learn through repeated action-level debriefs
PokerSnowie fits players who want opponent-driven training loops where imported hand histories immediately produce action-level debriefs and next-step drills. The workflow emphasizes fast conversion of mistakes into targeted repetition rather than deep inspectable node customization.
Analysts who run repeatable opponent spot reviews across sessions
PokerTracker 4 fits analysts who need database-backed hand history parsing and stat filtering to isolate specific opponents and spots. The core value is repeatable filters that support both cash game and tournament review workflows.
Coaches and students focused on preflop equity and runout distributions
Equilab fits teams that rely on equity distribution graphs and hand matrix comparisons for range vs range matchup decisions. It is equity-centric, so it supports scenario checking even when action EV across full decision trees is not the primary deliverable.
Researchers who require node editing mapped from real hands
GTO Wizard fits work that needs interactive node-based exploration tied to hand history import for rapid what-if analysis. It suits workflows where solver-style decision-tree edits matter more than just equity visualization.
Players who need quick board-level scenario validation
Simple Poker fits players who want range-based equity and tournament outcome checks that run quickly using board runout enumeration. It supports multiway pot realism, while solver-style CFR node locking controls are not the primary workflow focus.
Common pitfalls that break the analysis workflow
Most buyer mistakes come from assuming every tool provides the same depth of decision-tree analysis or the same operational loop for importing hands. The tools here differ sharply between training and equity visualization and between interactive node editing and precomputed replay.
Buying an equity-centric tool for full solver-style decision work
Equilab produces equity distribution graphs and hand matrix outputs for range matchups, but it does not generate action EV across full decision trees. Tools like GTO Wizard or PokerSnowie map hands into solvable node workflows, which better matches decision-study depth.
Expecting deep custom node control inside a training-first environment
PokerSnowie supports action-level debriefs tied to imported hand histories, but extensive custom node control is limited compared with full solver environments. For editable decision-tree depth, GTO Wizard provides more interactive node exploration.
Overestimating the value of stat filtering when hand history input quality is poor
PokerTracker 4’s stat accuracy depends on clean hand history imports, because its filtering and opponent spot review relies on parsed hand data. Poor import quality makes filters and reports less reliable.
Choosing precomputed replay when scenario-specific solver tuning is required
GTOBase speeds board-linked equity inspection from precomputed outputs, but it offers limited custom solver settings compared with full solver environments. Teams that need custom settings should prioritize GTO Wizard-style interactive decision-tree editing.
Using flop-centric analysis tools for multi-street strategy depth
Flopzilla supports blocker-driven flop selection and flop range equity visualization, but depth past flop analysis is limited compared with full postflop solvers. For multi-street strategy modeling depth, the node-based tools in this set better match the workflow.
How We Selected and Ranked These Tools
We evaluated each tool on feature coverage for the input-to-output workflow, where hand history import support and range-to-runout outputs affect what users can study next. We weighted features at 40%, and ease and value each at 30%, because iteration speed and repeatability change how often the software gets used in practice.
PokerSnowie ranked highest because opponent-driven training converts imported hands into immediate action-level debrief loops with targeted repetition, which directly shortens the feedback cycle. We treated solver-style inspection depth and custom node control as differentiators by comparing how GTO Wizard enables decision-tree editing and how PokerSnowie limits extensive custom node control relative to full solver environments.
Frequently Asked Questions About Poker Simulation Software
Which poker simulation tools handle hand history import well for scenario-driven review?
How do Equilab and Flopzilla differ when running range vs range equity over runouts?
When does GTOBase fit teams that need consistency across repeated analysis sessions?
What breaks if RangeConverter is skipped in a multi-tool workflow?
Which tool is better for database-style session filtering and opponent tendency review, PokerTracker 4 or Holdem Manager 3?
How do SSO and RBAC differ in practice for team use across poker analysis tools?
Where does PokerRanger fall short compared with GTO Wizard for decision depth?
How should teams plan data migration when moving from one hand-history workflow to another?
Which tool is best for board runout enumeration with multiway pot handling, and what tradeoff follows?
Tools reviewed
Primary sources checked during evaluation.
Referenced in the comparison table and product reviews above.
Funding and competing interests
This study was co-funded by several of the vendors assessed in it. No single vendor funded it. Funders could propose the market studied.
They had no role in selecting vendors, setting or weighting criteria, analysing data or drawing conclusions, and they received the same factual-accuracy check as every other vendor assessed.
Market definition, inclusion rules and criteria weights were fixed by an editor before research began and did not change afterwards. Editorial process →
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