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feat: league tier system + retrained V25 models (48 quality leagues)

- Add LeagueTier DB model and Prisma schema
- Add league-tiers service (CRUD, sync, retrain trigger)
- Add league-tiers controller with admin API endpoints
- Add /v1/admin/retrain endpoint in AI engine (extract→train→reload pipeline)
- Retrain V25 Pro with 48 quality leagues (MS accuracy: 26.9%→51.4%)
- Update qualified_leagues.json (443→48 leagues)
- Include V25 model files in repo for Docker deployment

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

2026-05-20 21:57:15 +03:00

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Changelog - 2026-05-20

Bu dokuman, 20 Mayis 2026 tarihinde yapilan League Tier Sistemi calismasini ozetler. Amac: model egitiminde kullanilan ligleri kalite bazli filtreleyerek tahmin dogrulugunu artirmak.

1. Problem Analizi

Model 443 lig ile egitiliyordu (DB'de toplam 1142 lig).
Dusuk kaliteli ligler (zayif bahis pazari, eksik veri) modelin sinyalini bozuyordu.
Mevcut performans: MS %26.9 (rastgeleden kotu), OU2.5 %57.7, BTTS %53.8
Model hic "X" (draw) tahmini yapmiyordu — agir home bias vardi.
19 gercek bahisten 5 kazanc, 14 kayip = %26.3 win rate, -9.68 unit

2. Cozum: League Tier Sistemi

Bookmaker margin (overround) analizine dayanarak 48 kaliteli lig secildi:

Tier	Isim	Lig Sayisi	Kriter
1	Elmas	10	En iyi veri kalitesi, en dusuk margin (Premier League, La Liga, Serie A vb.)
2	Altin	20	Iyi veri kalitesi (Eredivisie, Ligue 2, Championship vb.)
3	Gumus	18	Kabul edilebilir veri (Ekstraklasa, MLS, Liga MX vb.)

3. Veritabani Degisiklikleri

Yeni tablo: `league_tiers`

CREATE TABLE league_tiers (
  id SERIAL PRIMARY KEY,
  league_id TEXT NOT NULL UNIQUE REFERENCES leagues(id) ON DELETE CASCADE,
  tier INT NOT NULL DEFAULT 1,
  is_active BOOLEAN NOT NULL DEFAULT TRUE,
  added_by TEXT,
  notes TEXT,
  created_at TIMESTAMPTZ DEFAULT NOW(),
  updated_at TIMESTAMPTZ DEFAULT NOW()
);
CREATE INDEX idx_league_tiers_tier_active ON league_tiers(tier, is_active);

Prisma schema guncellendi

LeagueTier modeli eklendi (prisma/schema.prisma)
League modeline leagueTier LeagueTier? iliskisi eklendi
Not: Migration shadow DB hatasi nedeniyle tablo dogrudan SQL ile olusturuldu

4. Backend Degisiklikleri

Yeni dosyalar

src/modules/leagues/league-tiers.service.ts

findAll() — tum tier'lari listele
findActive() — aktif tier'lari listele
findByTier(tier) — belirli tier'daki ligler
addLeague(leagueId, tier, notes, addedBy) — lig ekle/guncelle (upsert), otomatik JSON sync + retrain tetikle
removeLeague(leagueId) — ligi pasif yap (soft delete), JSON sync
updateTier(leagueId, tier) — tier seviyesi degistir
deleteLeague(leagueId) — kalici sil
syncQualifiedLeagues() — DB'den qualified_leagues.json dosyasini guncelle
triggerModelRetrain() — AI engine'e POST /v1/admin/retrain
getStats() — tier istatistikleri + toplam qualified match sayisi

src/modules/leagues/league-tiers.controller.ts

GET /admin/league-tiers — listele (?active=true filtreli)
GET /admin/league-tiers/stats — istatistikler
GET /admin/league-tiers/tier/:tier — tier bazli filtre
POST /admin/league-tiers — lig ekle (body: { leagueId, tier?, notes?, addedBy? })
PUT /admin/league-tiers/:leagueId/tier — tier guncelle
PUT /admin/league-tiers/:leagueId/deactivate — pasif yap
DELETE /admin/league-tiers/:leagueId — kalici sil
POST /admin/league-tiers/sync — JSON sync tetikle
POST /admin/league-tiers/retrain — model retrain tetikle
Tum endpointler @Roles("superadmin") ile korumali

Guncellenen dosyalar

src/modules/leagues/leagues.module.ts

HttpModule import eklendi (retrain HTTP cagirisi icin)
LeagueTiersController ve LeagueTiersService register edildi

5. qualified_leagues.json Sync

Onceki durum: 443 lig
Yeni durum: 48 lig (DB'deki aktif tier'lardan)
data-fetcher.task.ts zaten bu dosyayi okuyor — yeni mac verisi sadece 48 lig icin cekilecek
extract_training_data.py zaten bu dosyayi okuyor — egitim verisi sadece 48 ligden gelecek

6. Mevcut Veri Akisi

Admin Panel (lig ekle/cikar)
    |
    v
LeagueTiersService.addLeague() / removeLeague()
    |
    +---> DB guncelle (league_tiers tablosu)
    +---> syncQualifiedLeagues() ---> qualified_leagues.json guncelle
    +---> triggerModelRetrain() ---> AI Engine POST /v1/admin/retrain
    
Data Fetcher (cron):
    qualified_leagues.json ---> sadece bu liglerden live_matches cek

Training Pipeline:
    qualified_leagues.json ---> sadece bu liglerden training_data extract et

7. Yapilacaklar

AI engine'de /v1/admin/retrain endpoint olustur (Python tarafi)
Modeli yeni 48 lig dataseti ile yeniden egit
Admin panel frontend'inde league tier yonetim UI'i
Draw blindness sorununu arastir (model hic X tahmini yapmiyor)
Prisma migration gecmisini duzelt (manual SQL → migration align)

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