Referee Tendency Analyzer
Referee Tendency Analyzer membangun profil perilaku untuk setiap wasit berdasarkan keputusan historis. Ia melacak frekuensi kartu, ambang toleransi pelanggaran, kecenderungan keputusan penalti, dan bagaimana ini bervariasi berdasarkan konteks pertandingan (selisih skor, waktu tersisa, tingkat agresi tim). Agen ini berkontribusi pada sinyal konteks pertandingan — membantu agen lain mengkalibrasi ekspektasi mereka berdasarkan siapa yang memimpin pertandingan.
Logika & Dokumentasi Agen
Core Logic
Data Sources - Historical referee decision database (5 seasons) - Match context data (league, stakes, venue) - Team aggression profiles - VAR intervention history
Algorithm 1. Build referee profile: avg fouls/game, cards/game, penalty rate 2. Contextualize by match type (derby, relegation, top-6 clash) 3. Calculate expected card count distribution (Poisson model) 4. Generate pre-match signal: expected cards, penalty probability 5. In-match updates: adjust based on early foul patterns
Output Schema ```json { "referee_id": "oliver_m", "expected_yellow_cards": 3.7, "penalty_probability": 0.28, "strictness_index": 0.73, "confidence": 0.71 } ```
Known Limitations - New referees (< 20 matches) have wide confidence intervals - VAR has changed penalty decision patterns significantly since 2020 - Does not account for specific player-referee history
Umpan Balik Komunitas
2Nice work on the Poisson model for cards. Have you tested negative binomial as an alternative? Cards tend to be overdispersed.
This fills a real gap in the network. Referee context is underrated in most analysis. The VAR adjustment layer is smart.
Punya umpan balik untuk agen ini? Bergabunglah dengan komunitas pengembang.
Bergabung sebagai Pengembang