RONAVEMI

Windows desktop application · version 4.5a

Review the match.
Train the pattern.

RONAVEMI turns evidence from a player’s own completed League of Legends matches into understandable reviews, several preparation options, and focused five-game training priorities.

See the v4.5a interface Request private reviewer access

Private pre-release. No public download. No Riot approval or endorsement is claimed.

CURRENT STATUS Private prototype
4.5aVersion
WindowsPlatform
EUWInitial region
FreeMonetization
  • Completed-match analysis
  • Player-controlled decisions
  • Local-first data handling
  • Private Riot review build on request

What RONAVEMI does

Coaching after the game, preparation before the next one.

RONAVEMI is designed for self-analysis across a player’s own match history. It connects performance evidence to a manageable training focus without automating play or dictating a single decision.

01

Performance dashboard

Aggregated trends across completed matches, roles, and champions make longer-term patterns easier to see.

02

Match review

Death Coach and Fight Cluster views connect post-game situations to evidence and learning priorities.

03

Training blocks

Findings become reviewable five-game priorities instead of an endless list of generic tips.

04

Preparation options

Champion-pool and draft-preparation views present several static or aggregate options with context and risks.

Real v4.5a interface

A reviewer can inspect the complete product flow here.

Every image below was captured from the accepted RONAVEMI v4.5a Tk desktop interface at commit ce725389085f3252cb68207bafb46801929ca890. The isolated reviewer profile and all 45 matches are synthetic. No real Riot ID, PUUID, API credential, local path, or player data is shown.

Review evidence, not a public release. The production candidate remains private. There is no public executable or production key on this website. Full-resolution images open in a new tab.
RONAVEMI v4.5a dashboard using a synthetic reviewer profile
01 · DashboardRecent and historical personal performance, role evidence, champion pool and a single training focus.
RONAVEMI local profile management using a synthetic reviewer identity
02 · Local profilesSeparate local histories, explicit private-test status and user-controlled privacy actions.
RONAVEMI role analysis screen
03 · Role analysisRole sample sizes, comparative performance and clearly scoped evidence.
RONAVEMI champion pool analysis screen
04 · Champion poolPersonal champion history, role context, sample sizes and confidence.
RONAVEMI Quick Pick screen comparing a Taliyah and Viego matchup
05 · Quick PickPlayer-controlled selection with alternatives, matchup plans, risks and visible evidence limits.
RONAVEMI manual Draft Assistant screen
06 · Draft AssistantOnly visible champions are entered manually. The app compares options; it does not automate champion select.
RONAVEMI completed match analysis with synthetic player names
07 · Completed-match analysisRetrospective teams, timeline evidence and post-game review using synthetic player labels.
RONAVEMI coaching development screen
08 · CoachEvidence-backed development signals keep uncertainty and non-causal boundaries visible.
RONAVEMI five-game training plan
09 · Training planA measurable five-game block with a stored baseline and explicit re-evaluation.
RONAVEMI data and knowledge provenance screen
10 · Data & KnowledgeCompleteness, patch freshness and knowledge provenance are inspectable in the product.
RONAVEMI About and Legal disclosure dialog
11 · About & LegalIndependent-product status, local-first summary, source disclosure and legal links.

User flow

A deliberate, player-controlled workflow.

The current build is a private pre-release prototype. A controlled test profile and redacted demonstration package can be supplied to Riot through an agreed secure channel.

  1. 01

    Create a local profile

    The player enters their own Riot ID, platform, and region.

  2. 02

    Load permitted data

    The player deliberately retrieves account, rank, completed-match, and timeline data through documented Riot API flows.

  3. 03

    Review evidence

    Dashboard, match review, and coaching views explain supported patterns; unclear evidence remains labelled as unclear.

  4. 04

    Choose a training focus

    RONAVEMI suggests reviewable priorities and several preparation options. The player makes the final decision.

  5. 05

    Control local data

    The player can inspect source and freshness information, export profile data, reset derived coaching data, and delete local match or profile data.

Game integrity

Clear boundaries by design.

RONAVEMI supports

  • Post-game learning from completed matches
  • Longitudinal self-analysis
  • Static and aggregate preparation context
  • Multiple evidence-backed options

RONAVEMI does not

  • Automate gameplay or champion select
  • Reveal hidden players or unknown session data
  • Calculate an alternative MMR or ELO
  • Dictate one mandatory player decision

Data and sources

Local-first, transparent, and gated.

Version 4.5a has no RONAVEMI cloud account, cloud synchronization, telemetry, advertising, or tracking. Profiles, Riot identifiers, completed-match data, timelines, training history, and derived analytics are stored under the user’s Windows account.

Riot data

The private prototype uses Riot Account-v1, Match-v5, League-v4, a Summoner-v4 compatibility fallback, and Riot Data Dragon. Active requests use HTTPS.

API-key handling

A development key entered for private testing is held in process memory for that session and is not intentionally persisted. A production secret will not be embedded in the desktop client.

OP.GG gate

The private development build can consume labelled, aggregated OP.GG metadata. Written permission for public use has been requested from OP.GG and is pending. The integration will be replaced or removed before public distribution if that permission is not obtained.

Privacy noticeRead → Terms of useRead → Operator informationRead →

Contact

Reviewer or privacy question?

RONAVEMI is operated by Joel Standhaft, an individual developer in Germany. Missing postal operator details remain subject to legal review and have not been invented.

joelst01@yahoo.de