ǥj\dZddlZdZdZdZdZdZdZd Zddd eefd Z d Z ddZ ddZ dS)a]Model: strength-based Poisson for football 1X2 predictions. lambda_home = HOME_BASE * att(home) * def(away) lambda_away = AWAY_BASE * att(away) * def(home) att = clamp(ppg / league_avg_ppg), def = 2 - att Constants fit 2024-26 Bundesliga calibration; same family as Dixon-Coles (minus the low-score correlation correction, which we can add later). N333333?gffffff?)g?r cbtj| ||zztj|z S)N)mathexp factorial)lmbdaks //root/.hermes/scripts/sports-predictor/model.py poisson_pmfr s, 8UF  eQh &):): ::c,t|d}t|d}dx}}ttD]Q}ttD]:}t||t||z}||kr||z }/||kr||z };R||d|z |z fS)zBReturns (p_home, p_draw, p_away) over an independent Poisson grid.皙??)maxrange MAX_GOALSr ) lambda_home lambda_awaylhlaphpdhaps r match_probsrs [$  B [$  BMB 9  y!!  AB""[Q%7%77A1uuaaa   r38b=  r cht\}}|dkr!t|t|||z ndS)Nrr) ATT_CLAMPrmin)ppgavg_ppglohis r att_coefr&$s6 FB.5kk3r3r3=)) * * *sBr g$@c&fd}|||}|||}t|} t|} || zd| z z} || zd| z z} t| | \} }}td| fd|fd|ffd\}}| | | ||||dS) u!Returns dict: lambda_home, lambda_away, ph, pd, pa, pick, pick_prob. Shrinkage: with home_n/away_n games played, ppg is regressed toward the league average (prior strength shrink=6 games) — tames early-season noise where 3 games can make PSG look like a mid-table side. c:||dkr|S||zzz|zz SN)r"nr#shrinks r shrink_ppgzpredict..shrink_ppg1s2 9AJa'F**q6z::r g@1X2c|dSr)r+)xs r zpredict..=s adr )key)rrrrpapick pick_prob)r&rr)home_ppgaway_ppgr#home_naway_nr- home_base away_baser.att_hatt_arrrrr6r7probs ` ` r predictrB)s;;;;;; z(F++Hz(F++H Xw ' 'E Xw ' 'E U cEk *B U cEk *BR$$JBBsBi#rS"I6NNKKKJD$Bb"t - --r c i}dD]d}||}||}|r|dkr(||zdz }|dkr||dz z nd}|tdtd|d||<e|S)zE(outcome, decimal_odds, model_prob) -> EV per 1u, Kelly stake cap 5%.)r/r0r1rrr)evkelly)getrr!) decimal_odds model_probsoutoutcomeorrDrEs r ev_1x2rLBs C"GG   W % %   AHH  US[$%GGC   3sCe4D4D+E+EFFG Jr ct|dt|d}}dx}}d}t|D]Z}t|D]H} t||t|| z} || kr|| z }n || kr|| z }|| zdkr|| z }I[dtj| z dtj| z z} ||d|z |z |d|z | dS)a(Convert Poisson expectations into binary prediction-market prices. Returns {home_win, away_win, draw, over_2_5, under_2_5, btts} as probabilities (0-1). 'Win' markets resolve NO on a draw in regulation. Used for yes/no markets (World.xyz, Polymarket) where price == probability. rrr)home_windrawaway_winover_2_5 under_2_5btts)rrr rr) rrmaxgrrrrover25rrrp_bttss r binary_marketsrYPsd # #Sd%;%;BMB F 4[[t  AB""[Q%7%77A1uuaaa1uzz!  DHbSMM!cDHbSMM&9 :FBC"HrMS6\6 K KKr {Gz?rc|dddS||z |z }d|z d|z z |z }||kr d|||z |z dS||kr d|||z|zd Sd||d S) aDecision rule for a yes/no market given model prob and quoted price. World's dealer spread is baked into the quoted price (~2-3%), so the edge must clear model_p - price > edge_min + spread. Returns dict with side, edge, and action ('BUY YES' / 'BUY NO' / 'PASS'). NPASSzno price)actionreasonrzBUY YES)r]edge price_at_mostzBUY NO)r]r_price_at_least)r]edge_yesedge_nor+)model_p market_pricespreadedge_minrbrcs r world_verdictrhhs J777%.HW}|!34v=G8#XRZHZ]cHcddd("G")H"4v"=?? ?(w G GGr )rM)rZr) __doc__r HOME_BASE AWAY_BASEr rr rr&rBrLrYrhr+r r rls    ;;; ! ! !CCC 15T9 ----2   KKKK0HHHHHHr