Repertoire Builder - User contributions [en]

Platform Update

2026-04-02T10:59:37Z

HollowLeaf:

The Platform Update page provides an overview of growth, activity, and ongoing trends across the system.
It highlights how users are engaging with the platform over time, how repertoires and libraries are evolving, and how new features continue to shape study and analysis habits.
Each section summarises key statistics and usage patterns drawn from the platform’s live data, offering a snapshot of both overall scale and the depth of user interaction.

This information is intended to give a clear picture of platform development, track long-term progress, and document the continued expansion of user activity across all major areas of the ecosystem.

== April 2026 ==

The following figures represent the latest platform statistics as of April 2026.
This update reflects continued steady growth across all major areas of the platform, with incremental gains in both user acquisition and engagement.
The data indicates a stable and maturing ecosystem, where increased scale is supported by consistent usage patterns and deeper analytical activity.

=== Users ===
The platform has reached a total of '''4,645 registered users''', representing continued growth since January 2026.
User acquisition remains steady, reflecting sustained organic demand and ongoing platform visibility.

Engagement metrics show modest increases across all time horizons.
The platform currently records '''44 daily active users (1-day active)''', '''125 users active within the last 7 days''', '''179 users active within the last 14 days''', and '''414 users active within the last 30 days'''.
This continued expansion across all activity windows highlights stable retention alongside gradual increases in returning users.

The introduction of subscriptions, launched at the end of 2025, is beginning to translate engagement into direct platform support.
The platform currently has '''15 Basic memberships''' and '''3 Pro memberships''', indicating initial conversion from free to supported usage.
Subscriptions are designed to support ongoing development while ensuring that the core platform remains accessible, allowing users to continue benefiting from its features regardless of their level of financial commitment.
While still modest in scale, this reflects early adoption of the platform’s support model within the existing user base.

Taken together, these figures indicate a platform that continues to grow while maintaining consistent engagement across both new and existing users.
=== Repertoires ===
Repertoire building remains the central pillar of activity on the platform.
Across all users, a total of '''13,645 repertoires''' have now been created, containing '''1,895,229 moves''' and spanning '''1,071,598 unique positions'''.
This reflects continued expansion in both scale and depth compared to January 2026.

Analytical engagement continues to evolve, with strong growth in written commentary and annotations.
The slight decrease in total engine-analyzed moves suggests a shift toward more selective analysis rather than purely volume-driven usage.

{| class="wikitable" style="width:100%; text-align:left;"
! Category !! April 2026 !! Change since January 2026 !! Description
|-
| Total Repertoires || '''13,645''' || '''▲ 2,833 (26.2%)''' || Total repertoires created across all users.
|-
| Total Moves || '''1,895,229''' || '''▲ 399,300 (26.7%)''' || Total recorded repertoire moves.
|-
| Unique Positions (FENs) || '''1,071,598''' || '''▲ 275,741 (34.6%)''' || Distinct positions represented across all repertoires.
|-
| Moves Analyzed with Stockfish || '''159,156''' || '''▲ 31,711 (24.5%)''' || Moves that include engine analysis results from Stockfish.
|-
| Moves with Comments || '''94,816''' || '''▲ 41,504 (77.8%)''' || Moves containing written commentary or notes.
|-
| Moves with Annotations || '''29,092''' || '''▲ 5,564 (23.6%)''' || Moves marked with symbolic annotations.
|}

At an individual level, the platform continues to demonstrate strong stability under heavy usage.
The largest single user repertoire now contains '''93,322 moves''', illustrating the system’s ability to support highly detailed and large-scale individual datasets without degradation in performance.

=== User Library ===
The user library has continued to expand significantly since January 2026.
It now contains '''155,895 games''', comprising '''10,810,580 moves''' and '''7,897,627 unique positions'''.
This sustained increase reflects both onboarding-driven data growth and continued user engagement with practical game analysis.

Analytical usage within the library remains consistent, with steady increases in comments and annotations alongside stable levels of engine analysis.
This indicates a continued balance between automated evaluation and manual review.

{| class="wikitable" style="width:100%; text-align:left;"
! Category !! April 2026 !! Change since January 2026 !! Description
|-
| Total Games || '''155,895''' || '''▲ 50,620 (48.1%)''' || Distinct games stored in the database.
|-
| Total Moves || '''10,810,580''' || '''▲ 3,355,827 (45.0%)''' || Individual moves recorded across all games.
|-
| Unique Positions (FENs) || '''7,897,627''' || '''▲ 1,818,377 (29.9%)''' || Unique board positions appearing in all games.
|-
| Moves Analyzed with Stockfish || '''12,777''' || '''▲ 613 (5.0%)''' || Moves that include engine analysis results from Stockfish.
|-
| Moves with Comments || '''56,602''' || '''▲ 3,608 (6.8%)''' || Moves containing written commentary or notes.
|-
| Moves with Annotations || '''34,174''' || '''▲ 2,173 (6.8%)''' || Moves marked with symbolic annotations.
|}

=== Summary ===
April 2026 reflects continued steady expansion across the platform.
User growth remains consistent, while engagement metrics show incremental improvements across all activity windows.

Repertoire development continues to expand in both scale and analytical depth, with increasing use of commentary and annotations alongside more targeted engine analysis.
The user library has also grown significantly, reinforcing its role as a central component of the platform’s analytical ecosystem.

At the same time, early subscription adoption marks the beginning of monetization, while large individual datasets demonstrate the platform’s technical stability and scalability.

Together, these trends reflect a system that continues to grow in a controlled and sustainable manner, balancing acquisition, engagement, analytical depth, and early revenue generation.

== January 2026 ==

The following figures represent the latest platform statistics as of January 2026.
This update highlights a period of accelerated growth, driven by continued user acquisition, improved onboarding, and deeper engagement across both repertoire building and practical game analysis.
Together, these metrics illustrate the platform’s transition from steady organic expansion toward a more scalable, data-driven foundation suitable for long-term growth and monetization.

=== Users ===
The platform has reached a total of '''4,210 registered users''', reflecting continued organic growth and sustained interest in structured chess study tools.
User acquisition remains consistent, averaging approximately '''6 new registered users per day''', indicating stable inbound demand without reliance on large-scale marketing campaigns.

Engagement metrics demonstrate a healthy and active user base across multiple time horizons.
The platform currently records '''40 daily active users (1-day active)''', '''120 users active within the last 7 days''', '''172 users active within the last 14 days''', and '''347 users active within the last 30 days'''.
This layered activity profile highlights strong short-term retention alongside a growing cohort of regularly returning users.

Taken together, these figures indicate a platform that is not only expanding its user base but also maintaining meaningful engagement over time.
The balance between steady acquisition and repeat usage provides a solid foundation for future feature expansion, monetization strategies, and retention-led growth.

=== Repertoires ===
Repertoire building continues to serve as the central pillar of activity on the platform.
Across all users, a total of '''10,812 repertoires''' have now been created, containing nearly '''1.5 million moves''' and spanning '''795,857 unique positions'''.
This represents substantial growth in both breadth and depth compared to October 2025, reflecting increased adoption alongside deeper individual study.

Analytical engagement within repertoires has also expanded meaningfully.
The volume of Stockfish-analyzed moves, written commentary, and symbolic annotations has risen across all categories, indicating a clear shift toward more structured and insight-driven preparation.

{| class="wikitable" style="width:100%; text-align:left;"
! Category !! January 2026 !! Change since October 2025 !! Description
|-
| Total Repertoires || '''10,812''' || '''▲ 3,233 (42.7%)''' || Total repertoires created across all users.
|-
| Total Moves || '''1,495,929''' || '''▲ 555,913 (59.1%)''' || Total recorded repertoire moves.
|-
| Unique Positions (FENs) || '''795,857''' || '''▲ 409,885 (106.2%)''' || Distinct positions represented across all repertoires.
|-
| Moves Analyzed with Stockfish || '''163,281''' || '''▲ 35,836 (28.1%)''' || Moves that include engine analysis results from Stockfish.
|-
| Moves with Comments || '''53,312''' || '''▲ 10,988 (26.0%)''' || Moves containing written commentary or notes.
|-
| Moves with Annotations || '''23,528''' || '''▲ 18,456 (363.8%)''' || Moves marked with symbolic annotations.
|}

=== User Library ===
The user library has experienced a significant expansion since October 2025, driven primarily by improvements to the onboarding process for new users.
As part of this workflow, newly registered users now import a curated set of approximately '''200 games''' into their personal library, enabling the platform to generate higher-quality template repertoires and provide immediate analytical context from the outset.

As a result, the library now contains more than '''105,000 games''', comprising over '''7.45 million moves''' and more than '''6.07 million unique positions'''.
This increase reflects a deliberate design decision to front-load practical game data in order to accelerate meaningful engagement rather than passive accumulation.

Alongside the increase in raw volume, analytical usage within the library continues to deepen.
The growing number of moves with Stockfish analysis, comments, and symbolic annotations reinforces the library’s role as an active workspace for post-game review, pattern recognition, and long-term performance tracking.

{| class="wikitable" style="width:100%; text-align:left;"
! Category !! January 2026 !! Change since October 2025 !! Description
|-
| Total Games || '''105,275''' || '''▲ 60,663 (136.0%)''' || Distinct games stored in the database.
|-
| Total Moves || '''7,454,753''' || '''▲ 4,320,165 (137.8%)''' || Individual moves recorded across all games.
|-
| Unique Positions (FENs) || '''6,079,250''' || '''▲ 4,522,636 (290.5%)''' || Unique board positions appearing in all games.
|-
| Moves Analyzed with Stockfish || '''12,164''' || '''▲ 5,570 (84.4%)''' || Moves that include engine analysis results from Stockfish.
|-
| Moves with Comments || '''52,994''' || '''▲ 15,288 (40.6%)''' || Moves containing written commentary or notes.
|-
| Moves with Annotations || '''32,001''' || '''▲ 16,008 (100.0%)''' || Moves marked with symbolic annotations.
|}

=== Summary ===
January 2026 marks a clear inflection point in the platform’s development.
User growth has remained steady, while engagement metrics demonstrate consistent retention across short-, medium-, and longer-term activity windows.
At the same time, improvements to onboarding have materially increased early user activation, directly contributing to a sharp rise in user library volume and practical game data.

Repertoire building continues to anchor platform engagement, with both the number of repertoires and their analytical depth expanding significantly since October 2025.
The combination of richer onboarding data, deeper repertoire analysis, and sustained user activity positions the platform for scalable growth, stronger personalization, and future monetization opportunities.

Together, these trends reflect a maturing ecosystem that balances acquisition, engagement, and analytical depth, laying a robust foundation for long-term product evolution and investor confidence.

== October 2025 ==

The following figures represent the latest platform statistics as of October 2025.
They capture the overall size, scope, and engagement of the user base, along with detailed summaries of repertoire activity and user-library growth.
Together, these numbers reflect steady and balanced progress across both study and practical play.

=== Users ===
The platform now includes a total of '''3,611 registered users''', who have collectively built '''7,579 repertoires''' and added over '''46,000 games''' to their personal libraries.
Together, users have created more than '''4.07 million moves''' across all areas of the platform.

Engagement remains consistently strong, with users combining structured repertoire study with practical game analysis.
The sustained growth in both activity and content creation highlights the platform’s evolution into a comprehensive environment for preparation, training, and long-term improvement.

=== Repertoires ===
Repertoire building continues to form the core of user engagement on the platform.
Across all users, a total of '''7,579 repertoires''' have been created, containing more than '''940,000 moves''' and covering '''385,972 unique positions'''.
Approximately '''13%''' of all moves have been analyzed with Stockfish, and tens of thousands feature comments, symbolic annotations, or positional assessments.
A smaller but growing portion includes additional observations, highlighting the platform’s increasing focus on structured analysis and understanding.

{| class="wikitable" style="width:100%; text-align:left;"
! Category !! Count !! Description
|-
| Total Repertoires || '''7,579''' || Total repertoires created across all users
|-
| Total Moves || '''940,016''' || Total recorded repertoire moves.
|-
| Unique Positions (FENs) || '''385,972''' || Distinct positions represented in all repertoires.
|-
| Moves Analyzed with Stockfish || '''127,445''' || Moves that include engine analysis results from Stockfish.
|-
| Moves with Comments || '''42,324''' || Moves containing written commentary or notes.
|-
| Moves with Annotations || '''5,072''' || Moves marked with symbolic annotations.
|}

=== User Library ===
The user library covers imported games, personal analyses, and reviewed material, serving as a major archive of practical play.
It now contains more than '''44,000 games''', comprising over '''3.13 million moves''' and '''1.56 million unique positions'''.
Although most moves remain unannotated, the number that include Stockfish analysis, comments, or structured observations continues to grow.
The library has become a central reference point for users studying their own games and tracking long-term progress.

{| class="wikitable" style="width:100%; text-align:left;"
! Category !! Count !! Description
|-
| Total Games || '''44,612''' || Distinct games stored in the database.
|-
| Total Moves || '''3,134,588''' || Individual moves recorded across all games.
|-
| Unique Positions (FENs) || '''1,556,614''' || Unique board positions appearing in all games.
|-
| Moves Analyzed with Stockfish || '''6,594''' || Moves that include engine analysis results from Stockfish.
|-
| Moves with Comments || '''37,706''' || Moves containing written commentary or notes.
|-
| Moves with Annotations || '''15,993''' || Moves marked with symbolic annotations.
|}

=== Summary ===
Overall platform activity continues to show steady and balanced growth.
User numbers have expanded consistently, with strong participation across both repertoire development and game analysis.
The total volume of moves created now exceeds '''4 million''', reflecting an active and engaged user base that is deeply invested in structured study and practical improvement.
Repertoire building remains at the heart of platform engagement, while the expanding user library demonstrates an increasing focus on post-game review and analytical depth.
These trends highlight the platform’s continued evolution into a comprehensive environment for long-term chess study, preparation, and performance tracking.

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MediaWiki:Sidebar

2026-02-05T01:24:07Z

HollowLeaf:

WikiBooks

2026-02-05T01:03:32Z

HollowLeaf:

'''Available in:''' Builder, Library
[[File:AnalyticsCards-WikiBooks.png|thumb|380px]]
The '''WikiBooks''' card displays community-written opening theory from Wikibooks.org for the current position on the board. Each entry provides strategic explanations, typical plans, and historical context for the opening, helping you understand the ideas behind the moves rather than just memorizing variations. You can '''read''' the theory directly within the card to understand the positional goals and common continuations for your current position.

This feature helps you:

<ul style="list-style:none; padding-left:1.5em; margin:0;">
<li style="text-indent:-1.1em; padding-left:1.1em;">
+
Understand the strategic ideas and plans behind opening positions
</li>
<li style="text-indent:-1.1em; padding-left:1.1em;">
+
Learn opening theory with context and explanations, not just moves
</li>
<li style="text-indent:-1.1em; padding-left:1.1em;">
+
Access free, open-source chess theory curated by the chess community
</li>
</ul>

{{Notice|Note|WikiBooks content is sourced from the open-source Wikibooks.org Chess Opening Theory project. Not all positions have written theory available, but coverage is extensive for popular openings and main lines.}}

WikiBooks

2026-02-05T01:02:20Z

HollowLeaf: Created page with "380px '''Available in:''' Builder, Library The '''WikiBooks''' card displays community-written opening theory from Wikibooks.org for the current position on the board. Each entry provides strategic explanations, typical plans, and historical context for the opening, helping you understand the ideas behind the moves rather than just memorizing variations. You can '''read''' the theory directly within the card to understand the..."

[[File:AnalyticsCards-WikiBooks.png|thumb|380px]]

'''Available in:''' Builder, Library

The '''WikiBooks''' card displays community-written opening theory from Wikibooks.org for the current position on the board. Each entry provides strategic explanations, typical plans, and historical context for the opening, helping you understand the ideas behind the moves rather than just memorizing variations. You can '''read''' the theory directly within the card to understand the positional goals and common continuations for your current position.

This feature helps you:

<ul style="list-style:none; padding-left:1.5em; margin:0;">
<li style="text-indent:-1.1em; padding-left:1.1em;">
+
Understand the strategic ideas and plans behind opening positions
</li>
<li style="text-indent:-1.1em; padding-left:1.1em;">
+
Learn opening theory with context and explanations, not just moves
</li>
<li style="text-indent:-1.1em; padding-left:1.1em;">
+
Access free, open-source chess theory curated by the chess community
</li>
</ul>

{{Notice|Note|WikiBooks content is sourced from the open-source Wikibooks.org Chess Opening Theory project. Not all positions have written theory available, but coverage is extensive for popular openings and main lines.}}

2026-02-05T00:53:27Z

HollowLeaf:

File:RepertoireDeviations-Details.png

2026-02-05T00:52:42Z

HollowLeaf:

File:RepertoireDeviations-Summary.png

2026-02-05T00:52:31Z

HollowLeaf:

2026-01-15T15:27:26Z

HollowLeaf:

{{Notice|Subscribers Only|This functionality is available for Basic and higher subscription tiers.}}

[[File:AnalyticsCards-Lc0Engine.png|thumb|380px]]
'''Available in:''' Builder, Library, Practice, Tools

The Leela Chess Zero Engine card provides deep-learning evaluations of the current position using the t1-256x10 distilled neural network.
Unlike classical engines that rely on brute-force search, Lc0 evaluates positions through pattern recognition, long-term planning, and human-like strategic intuition.
This makes it a valuable tool for analysing complex middlegames, quiet improvements, positional sacrifices, and other subtle ideas essential for modern opening preparation and training inside the '''Repertoire Builder'''.

'''Network: t1-256x10'''
Lc0 uses a single fixed neural network in this feature, providing consistent and high-quality deep-learning evaluations.

<ul style="list-style:none; padding-left:1.5em; margin:0;"> <li style="text-indent:-1.1em; padding-left:1.1em;"> ◦ Size: T1-256x10 distilled (swa 2432500) </li> <li style="text-indent:-1.1em; padding-left:1.1em; margin-top:0.3em;"> ◦ Architecture: 256 filters, 10 residual blocks </li> <li style="text-indent:-1.1em; padding-left:1.1em; margin-top:0.3em;"> ◦ File Size: 30–40 MB </li> </ul>

For the current position, this section displays:

<ul style="list-style:none; padding-left:1.5em; margin:0;"> <li style="text-indent:-1.1em; padding-left:1.1em;"> ◦ Move: Lc0's preferred move based on its neural-network evaluation. </li><li style="text-indent:-1.1em; padding-left:1.1em; margin-top:0.3em;"> ◦ Probability: Lc0's predicted likelihood that the chosen move is best. </li> <li style="text-indent:-1.1em; padding-left:1.1em; margin-top:0.3em;"> ◦ WDL: Win, draw, and loss probabilities based on the network's evaluation of the overall position. </li> </ul>

You can '''click''' on any move to add it directly to your opened item, or '''right-click''' to add the move together with its evaluation, probability, and WDL data as a comment for immediate reference.

This feature helps you:

<ul style="list-style:none; padding-left:1.5em; margin:0;"> <li style="text-indent:-1.1em; padding-left:1.1em;"> + Explore strategic ideas derived from deep-learning evaluation instead of brute-force search </li> <li style="text-indent:-1.1em; padding-left:1.1em; margin-top:0.3em;"> + Understand quiet improvements, long-term plans, and subtle positional concepts </li> <li style="text-indent:-1.1em; padding-left:1.1em; margin-top:0.3em;"> + Compare deep-learning suggestions with Stockfish or Maia to gain multiple perspectives on the same position </li> <li style="text-indent:-1.1em; padding-left:1.1em; margin-top:0.3em;"> + Add Lc0-evaluated moves directly into your repertoire or study material </li> </ul>

{{Notice|Note|This feature leverages the open-source Lc0 project: https://github.com/LeelaChessZero/lc0}}

MediaWiki:Sitenotice

2026-01-06T12:11:07Z

HollowLeaf: Replaced content with "-"

2026-01-06T12:06:38Z

HollowLeaf:

MediaWiki:Sitenotice

2026-01-06T12:06:02Z

HollowLeaf: Created page with "Test"

Test

CORR Database

2026-01-05T01:53:51Z

2025-12-31T20:15:53Z

HollowLeaf:

The '''Tools''' in the '''Repertoire Builder''' provides you with powerful ways to analyze, explore, and improve your chess.
They connect to online services like '''Lichess''' and '''Chess.com''', import your own games and PGNs, and deliver focused insights into your play.
From building reference trees and scouting players to tracking time usage and opening priorities, these tools help you study smarter and target what matters most.

{| class="wikitable" style="width:100%; text-align:left; border:1px solid #ccc; border-collapse:collapse;"
! style="width:25%; background-color:#f5f5f5;" | '''Tool'''
! style="background-color:#f5f5f5;" | '''Why Use This Tool'''
|-
| [[Reference Tree Builder|'''Reference Tree''']]
| Create a reference database from '''Lichess''', '''Chess.com''', or PGN files. Compare your lines with theory, manage imports and exports, and use it throughout the Repertoire Builder.
|-
| [[User Scout|'''User Scout''']]
| Analyze any player’s games. Import from '''Lichess''' or '''Chess.com''' to reveal their favorite openings, performance trends, and habits — or scout yourself for improvement.
|-
| [[Time Usage Analysis|'''Time Usage Analysis''']]
| See where you spend the most time in your games. Identify long thinks, quick moves, and decision patterns to improve your time management.
|-
| [[Opening Priorities|'''Opening Priorities''']]
| Find which openings slow you down. Highlight early-game time sinks to focus your study where it counts most.
|-
| [[Repertoire Generator|'''Repertoire Generator''']]
| Generate repertoires from your own games. Transform real play into engine-approved opening templates for focused study.
|}

{{Notice|Tip|Tools can be combined with your repertoires and libraries to reveal deeper insights into your play and progress.}}

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Analytics Cards Overview

2025-12-31T20:14:46Z

HollowLeaf:

The '''Analytics Cards''' provides you with powerful tools to assess and refine your repertoire.
Each card focuses on a different analytical perspective — from identifying missing moves and engine inaccuracies to comparing your lines with master databases and online play.
Together, they give you deep insight into how complete, strong, and practical your repertoire really is.

In the Builder, you have access to the following analytics cards:

{| class="wikitable" style="width:100%; text-align:left; border:1px solid #ccc; border-collapse:collapse;"
! style="width:25%; background-color:#f5f5f5;" | '''Analytics Card'''
! style="background-color:#f5f5f5;" | '''Why Use This Card'''
|-
| [[Alternative Variations|'''Alternative Variations''']]
| Instantly spot which variations are missing from your repertoire compared to a reference source. A quick way to fill gaps, add alternatives, and ensure complete coverage
|-
| [[Bookmarks|'''Bookmarks''']]
| Keep track of important or tricky positions in your repertoire so you can return to them instantly. Ideal for marking lines you want to review, refine, or practise without losing your place.
|-
| [[ChessDB|'''ChessDB''']]
| Compare your repertoire against a massive engine-evaluated database. See which moves perform best statistically and practically, helping you validate or challenge your existing lines with objective data.
|-
| [[Gap Analysis|'''Gap Analysis''']]
| Analyze your repertoire to uncover missing or underrepresented moves compared to how players at your level actually play. The system scans your existing lines and highlights high-frequency moves you do not yet cover, allowing you to jump directly to the position, add the move instantly, or dismiss it.
|-
| [[K-Maps|'''K-MAPS''']]
| Visualize positional balance through five core metrics — King Safety, Material, Activity, Pawn Structure, and Space — shown as a radar and table comparison for both sides.
|-
| [[Lichess Database|'''Lichess Database''']]
| Learn what real players play online. Spot current trends, discover surprising practical choices, and tailor your repertoire to match modern online metagames.
|-
| [[Masters Database|'''Masters Database''']]
| Study how titled players handle your positions. Use master-level continuations to strengthen your repertoire with proven, high-quality ideas.
|-
| [[My Library Moves|'''My Library Moves''']]
| Turn your own games and analyses into learning material. Discover which moves you’ve trusted most in practice, where you score best, and where improvement is needed.
|-
| [[Position Library|'''Position Library''']]
| Build a personal archive of key positions for study and recall. Perfect for tagging critical structures, tactical motifs, or decision points you want to revisit later.
|-
| [[Position Overview|'''Position Overview''']]
| Get a quick snapshot of the current position — see all candidate moves and how often they appear across your repertoires, library items, and references. A powerful way to gauge your overall coverage.
|-
| [[Reference Tree|'''Reference Tree''']]
| Compare your repertoire against a trusted reference source to find overlaps, gaps, and strong alternatives. Great for aligning your preparation with established theory.
|-
| [[Repertoire Review|'''Repertoire Review''']]
| Identify weaknesses in your repertoire using engine evaluations. Focus your study where the computer finds inaccuracies and turn those weak spots into strengths.
|-
| [[Repertoire Match|'''Repertoire Match''']]
| Check whether your current position appears in other repertoires. Useful for finding shared lines, cross-references, and continuity between different opening collections.
|-
| [[Repertoire Move Notations|'''Repertoire Move Notations''']]
| Lets you instantly see any comments, annotations, or other notes that exist for the current board position within your repertoires.
|-
| [[Space Visualisation|'''Space Visualisation''']]
| See who controls the board at a glance. Visualize space dominance to understand the positional balance and structure of your current position.
|-
| [[Stockfish|'''Stockfish''']]
| Get live, in-depth engine analysis right inside the Builder. Use it to test ideas, evaluate positions, and confirm your strategic plans with concrete data.
|-
| [[Transpositions|'''Transpositions''']]
| Reveal alternative move orders within your repertoire or library that lead to the same position. Essential for mastering flexible opening systems and spotting hidden overlaps.
|-
| [[Repertoire Visualisation|'''Repertoire Visualisation''']]
| See your repertoire come to life. The graphical map highlights move quality by engine evaluation, showing you which branches are solid and which need attention.
|-
| [[Variations in Repertoire|'''Variations in Repertoire''']]
| View all named variations in your repertoire in one place. Compare and organize your lines to maintain clarity and consistency as your repertoire grows.
|}

'''Subscribers''' have access to the following additional cards:

{| class="wikitable" style="width:100%; text-align:left; border:1px solid #ccc; border-collapse:collapse;"
! style="width:25%; background-color:#f5f5f5;" | '''Analytics Card'''
! style="background-color:#f5f5f5;" | '''Why Use This Card'''
|-
| [[CORR Database|'''CORR Database''']]
| Study high-quality correspondence games where players used engine assistance. A great resource for finding precise, well-analyzed continuations grounded in real human decision-making.
|-
| [[Playbook|'''Playbook''']]
| The Playbook card is a reference database of famous players’ repertoires, showing their preferred moves and styles across key openings..
|-
| [[TCEC Database|'''TCEC Database''']]
| Explore moves from top engine-vs-engine games played in the TCEC (Top Chess Engine Championship). Useful for discovering cutting-edge theoretical ideas and deeply optimized computer lines.
|-
| [[Maia Engine|'''Maia Engine''']]
| View human-style move probabilities predicted by the Maia neural-network model, trained on real games across multiple rating levels. Ideal for understanding how players at different strengths actually respond in a position, revealing practical tendencies, mistakes, and natural moves.
|-
| [[Leela Chess Zero Engine|'''Leela Chess Zero Engine''']]
| Analyse positions using deep-learning evaluations from the t1-256x10 network, view move probabilities, centipawn scores, and WDL outcomes, and integrate Lc0’s strategic insights directly into your repertoire and study workflow.
|}

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Repertoire Generator

2025-12-31T20:14:18Z

HollowLeaf: Created page with "'''Location:''' Tools > Repertoire Generator 6000px The '''Repertoire Generator''' allows you to import your games from '''Chess.com''', '''Lichess.org''', and your own '''PGN files''' to automatically generate engine-approved repertoire templates. These templates can then be loaded directly into the '''Repertoire Builder''', allowing you to rapidly create custom repertoires that are grounded in your act..."

'''Location:''' Tools > Repertoire Generator

[[File:RepertoireGenerator.png|class=fullwidth|frameless|border|6000px]]

The '''Repertoire Generator''' allows you to import your games from '''Chess.com''', '''Lichess.org''', and your own '''PGN files''' to automatically generate engine-approved repertoire templates. These templates can then be loaded directly into the '''Repertoire Builder''', allowing you to rapidly create custom repertoires that are grounded in your actual gameplay rather than generic theory.

By analyzing your personal game history and applying configurable engine analysis, the Repertoire Generator transforms your played openings into structured, study-ready repertoires — helping you systematize what you already play and refine it with objective evaluation.

This application allows you to:

<ul style="list-style:none; padding-left:1.5em; margin:0;"> <li style="text-indent:-1.1em; padding-left:1.1em;"> + Import games from Chess.com, Lichess.org, and PGN files simultaneously </li> <li style="text-indent:-1.1em; padding-left:1.1em;"> + Automatically detect and group openings played as White and Black </li> <li style="text-indent:-1.1em; padding-left:1.1em;"> + Generate engine-analyzed repertoire templates ready for the Repertoire Builder </li> </ul>

== Controls ==

This section is used to import your games from supported sources and manage the loading process.

For '''Chess.com''' and '''Lichess.org''', enter your '''username''' and specify the '''number of games''' to load.
Click the settings cog to configure additional filters:

<ul style="list-style:none; padding-left:1.5em; margin:0;"> <li style="text-indent:-1.1em; padding-left:1.1em;"> ◦ Date range </li> <li style="text-indent:-1.1em; padding-left:1.1em;"> ◦ Time controls </li> </ul>

You can also add games by uploading one or more '''PGN files'''.
When uploading PGNs, you will be prompted to enter one or more '''player names'''. These names are used to match you against the PGN metadata so the system can correctly determine which side you were playing.

Once all details are entered, click '''Import Games''' to begin loading.
You may cancel the import at any time, or click '''Clear All''' to remove all imported games and start again.

{{Notice|Note|You can load all three sources at the same time and continue adding more games or PGN files incrementally.}}

== Openings and Repertoires ==

After your games are loaded, the system analyzes them to identify the openings you have played.
The results are split into two lists:

<ul style="list-style:none; padding-left:1.5em; margin:0;"> <li style="text-indent:-1.1em; padding-left:1.1em;"> ◦ Openings played as White </li> <li style="text-indent:-1.1em; padding-left:1.1em;"> ◦ Openings played as Black </li> </ul>

For each side, the top ten openings are selected based on the number of games played.
You can freely '''select or deselect''' openings before generation, allowing you to focus only on the lines you want to include.

Before generating, you can configure the engine settings by clicking the settings cog next to the '''Generate''' button. The following options are available:

<ul style="list-style:none; padding-left:1.5em; margin:0;"> <li style="text-indent:-1.1em; padding-left:1.1em;"> ◦ Principal Variations – how many branches are generated per position </li> <li style="text-indent:-1.1em; padding-left:1.1em;"> ◦ Analysis Depth – the Stockfish depth used for evaluation </li> <li style="text-indent:-1.1em; padding-left:1.1em;"> ◦ Repertoire Depth – how many moves (ply) are generated from each starting position </li> </ul>

{{Notice|warning|Increasing these settings will significantly impact how long it takes to generate repertoire templates.}}

== Preview ==

Once generation is complete, you can preview the generated repertoires before saving them.
The preview allows you to play through the lines, inspect the generated structure, and verify that the results match your expectations.

From here, you can:

<ul style="list-style:none; padding-left:1.5em; margin:0;"> <li style="text-indent:-1.1em; padding-left:1.1em;"> ◦ Save the repertoire directly to your profile </li> <li style="text-indent:-1.1em; padding-left:1.1em;"> ◦ Delete the generated repertoire if you want to regenerate with different settings </li> </ul>

This allows you to iteratively refine your analysis — for example, by increasing engine depth or adjusting variation breadth — until the generated repertoire meets your desired level of detail and quality.

{{DocNav
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Opening Priorities

2025-12-31T20:11:19Z

HollowLeaf: /* Repertoire Finder */

'''Location:''' Tools > Opening Priorities

[[File:OpeningPriorities-Overview.png|class=fullwidth|frameless|border|6000px]]

The '''Opening Priorities''' tool lets you import your games from '''Chess.com''' or '''Lichess''' and analyze how you manage time across different openings.
It highlights which openings cause you to spend the most time in the early moves, helping you identify areas where you struggle and prioritize which lines to study more closely in your repertoire.

This feature enables you to:

<ul style="list-style:none; padding-left:1.5em; margin:0;"> <li style="text-indent:-1.1em; padding-left:1.1em;"> + Detect which openings consistently consume the most time early in your games </li> <li style="text-indent:-1.1em; padding-left:1.1em;"> + Understand whether your time usage patterns correlate with performance or confidence in specific openings </li> <li style="text-indent:-1.1em; padding-left:1.1em;"> + Prioritize which openings to review or reinforce in your repertoire based on time and results </li> </ul>

== Controls ==
[[File:OpeningPriorities-Controls.png|thumb|380px]]

The '''Controls''' section allows you to import games directly from '''Lichess''' or '''Chess.com'''.
Simply click the corresponding icon to toggle the desired platform. Once selected, you can begin loading your games.

<ul style="list-style:none; padding-left:1.5em; margin:0;"> <li style="text-indent:-1.1em; padding-left:1.1em;"> ◦ You can cancel the import process at any time by clicking Cancel. </li> <li style="text-indent:-1.1em; padding-left:1.1em;"> ◦ While the games are loading, the cards are temporarily hidden to speed up processing. </li> <li style="text-indent:-1.1em; padding-left:1.1em;"> ◦ Click '''Show Results''' at any time to view live updates as games are being processed. </li> </ul>

This section provides full control over the data import process, ensuring smooth integration whether you are analyzing a few games or your entire online archive.

== Filters ==
[[File:OpeningPriorities-Filters.png|thumb|380px]]

The '''Filters''' section allows you to focus your analysis on specific types of games or conditions.
You can narrow down your data by any of the following criteria:

<ul style="list-style:none; padding-left:1.5em; margin:0;"> <li style="text-indent:-1.1em; padding-left:1.1em;"> ◦ Player Colour: Show only games as White or Black </li> <li style="text-indent:-1.1em; padding-left:1.1em;"> ◦ Opening Name: Use wildcard search to find openings of interest </li> <li style="text-indent:-1.1em; padding-left:1.1em;"> ◦ Date Range: Select from-to dates to analyze games from a specific period </li> <li style="text-indent:-1.1em; padding-left:1.1em;"> ◦ Time Control: Filter by Classic, Rapid, Blitz, or Custom formats (e.g., 10+0, 45+45) </li> <li style="text-indent:-1.1em; padding-left:1.1em;"> ◦ Result: Restrict analysis to wins, losses, or draws </li> <li style="text-indent:-1.1em; padding-left:1.1em;"> ◦ Ply Range: Focus on a specific segment of moves within each game </li> </ul>

Filters help you target specific study areas — for example, you can compare how your time usage differs in blitz versus classical games, or when playing certain openings.

== Weighting ==
[[File:OpeningPriorities-Weighting.png|thumb|380px]]

The '''Weighting''' card allows you to assign the importance of different aspects in order to fine-tune how your opponent priorities are calculated.
You can adjust the sliders to determine how much influence each factor should have:

<ul style="list-style:none; padding-left:1.5em; margin:0;"> <li style="text-indent:-1.1em; padding-left:1.1em;"> ◦ Average Think Time: Measures how long you usually spend on moves in this opening </li> <li style="text-indent:-1.1em; padding-left:1.1em;"> ◦ Number of Games: Reflects how often you reach this opening in your games </li> <li style="text-indent:-1.1em; padding-left:1.1em;"> ◦ Performance Rating: Compares your results to opponent ratings, rewarding higher performance </li> <li style="text-indent:-1.1em; padding-left:1.1em;"> ◦ Long Think Threshold: Identifies how often you take significantly longer than average on early moves </li> </ul>

The overall '''Priorities Score''' is dynamically calculated from your chosen weights, giving you full control over which factors matter most in evaluating your openings.

{{Notice|Note|This weighting configuration is directly used in the '''Priorities Card''' when you sort by Weighted.}}

== Priorities Card ==
[[File:OpeningPriorities-Priorities.png|thumb|380px]]

The '''Priorities Card''' displays a ranked list of your openings based on your selected weighting configuration.
You can sort openings by any of the following criteria:

<ul style="list-style:none; padding-left:1.5em; margin:0;"> <li style="text-indent:-1.1em; padding-left:1.1em;"> ◦ Weighted: Uses your chosen slider parameters from the Weighting card </li> <li style="text-indent:-1.1em; padding-left:1.1em;"> ◦ Performance: Sorts by your calculated performance rating per opening </li> <li style="text-indent:-1.1em; padding-left:1.1em;"> ◦ First Long Think: Sorts by the first move where you spent more than double your average move time </li> <li style="text-indent:-1.1em; padding-left:1.1em;"> ◦ Number of Games: Sorts by how frequently you’ve reached each opening </li> </ul>

You can switch between ascending and descending order for each category, and use pagination to browse through larger lists.

Each entry in the list includes:

<ul style="list-style:none; padding-left:1.5em; margin:0;"> <li style="text-indent:-1.1em; padding-left:1.1em;"> ◦ Opening Name: The recognized ECO name or your custom label </li> <li style="text-indent:-1.1em; padding-left:1.1em;"> ◦ PGN Line: The representative move sequence for the opening </li> <li style="text-indent:-1.1em; padding-left:1.1em;"> ◦ Thinking Time Chart: Displays average move time by ply, along with minimum and maximum values </li> <li style="text-indent:-1.1em; padding-left:1.1em;"> ◦ Number of Games: Indicates how many total games reached this opening </li> <li style="text-indent:-1.1em; padding-left:1.1em;"> ◦ WDL and Performance Rating: Calculated as follows — a win = opponent rating +200, draw = opponent rating, loss = opponent rating −200 </li> <li style="text-indent:-1.1em; padding-left:1.1em;"> ◦ Avg Time (≤30 ply): Average time in seconds spent during the first 30 ply (the opening phase) </li> <li style="text-indent:-1.1em; padding-left:1.1em;"> ◦ First Long Think: The first move where your think time was more than double the previous average — showing when you first encountered real uncertainty </li> </ul>

{{Notice|Personal Note|I often use this card to find openings where my first long think happens unusually early — that usually means I’m unclear about my move order or struggling to recall my preparation. It’s a great cue for where I should strengthen my repertoire next.}}

== Repertoire Finder ==
[[File:OpeningPriorities-RepertoireFinder.png|thumb|380px]]

When you click on an item in your '''Opening Priorities''' list, the '''Repertoire Finder''' card displays all matching repertoire entries from your personal database.

<ul style="list-style:none; padding-left:1.5em; margin:0;"> <li style="text-indent:-1.1em; padding-left:1.1em;"> ◦ Instantly locate where the selected opening appears within your repertoire </li> <li style="text-indent:-1.1em; padding-left:1.1em;"> ◦ Jump directly to the position on the board for deeper study </li> <li style="text-indent:-1.1em; padding-left:1.1em;"> ◦ Compare your in-game choices against your prepared lines </li> </ul>

This seamless link between analysis and preparation helps you turn insights from time-based statistics directly into actionable repertoire study.

{{DocNav
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}}

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2025-12-31T20:10:55Z

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