def expected_value(bet_amount, multiplier, prob): return (bet_amount * multiplier * prob) - (bet_amount * (1 - prob)) class BloxflipPredictor: def __init__(self, history): self.history = history self.streak = StreakAnalyzer(history) def predict_crash(self): suggestion = self.streak.suggest_next() # Add pseudo-random "prediction" with confidence score import random confidence = random.uniform(0.4, 0.7) # Never 100% - realistic return { "predicted_outcome": suggestion["action"], "confidence": f"{confidence:.0%}", "reasoning": suggestion["reason"], "recommended_stop_loss": 100, "recommended_bet_percent": 0.02 # 2% of bankroll } Part 5: Complete Source Code (Python Script) Here's a fully functional (though non-predictive) Bloxflip assistant:
from sklearn.ensemble import RandomForestClassifier import numpy as np def create_features(history): features = [] labels = [] # 1 = crash > 2x, 0 = crash < 2x for i in range(10, len(history)-1): window = history[i-10:i] feat = [ np.mean(window), np.std(window), window[-1], window[-2], len([x for x in window[-5:] if x < 2.0]) # low crash count ] features.append(feat) label = 1 if history[i+1] > 2.0 else 0 labels.append(label) return features, labels How to make Bloxflip Predictor -Source Code-
def get_crash_history(self, limit=100): # Public endpoint for recent crash points url = f"{self.base_url}/games/crash/recent" params = {"limit": limit} response = requests.get(url, headers=self.headers, params=params) if response.status_code == 200: return response.json() # Returns list of crash multipliers else: print(f"Error: {response.status_code}") return [] 0 = crash <
def calculate_next_bet(self): trend = self.analyze_trend() streak = self.get_current_streak() # Simple strategy: bet against long streaks if streak >= 3: # After 3 low crashes, bet on high (but with low stake) bet_amount = self.bankroll * 0.01 multiplier_target = 2.5 action = f"Bet {bet_amount:.2f} to cash out at {multiplier_target}x" confidence = 0.55 elif trend == "high_trend": bet_amount = self.bankroll * 0.02 multiplier_target = 1.8 action = f"Bet {bet_amount:.2f} to cash out at {multiplier_target}x" confidence = 0.60 else: bet_amount = self.bankroll * 0.005 multiplier_target = 1.5 action = f"Small bet {bet_amount:.2f} to cash out at {multiplier_target}x" confidence = 0.45 return { "action": action, "confidence": f"{confidence:.0%}", "trend": trend, "streak_count": streak } 2x for i in range(10
def fetch_recent_games(self): headers = {} if self.api_key: headers["x-auth-token"] = self.api_key try: response = requests.get("https://api.bloxflip.com/games/crash/recent?limit=50", headers=headers) if response.status_code == 200: data = response.json() for game in data: self.history.append(game['crashPoint']) else: print("API unavailable, using simulated data") for _ in range(20): self.history.append(round(random.uniform(1.0, 10.0), 2)) except: print("Generating demo history") for _ in range(100): self.history.append(round(random.uniform(1.0, 10.0), 2))