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https://github.com/titanscouting/tra-analysis.git
synced 2025-09-06 23:17:22 +00:00
analysis.py v 1.1.12.005
analysis pkg v 1.0.0.002
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@@ -158,49 +158,121 @@ def push_to_database(apikey, competition, results, metrics):
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def metricsloop(tbakey, apikey, competition, timestamp): # listener based metrics update
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elo_N = 400
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elo_K = 24
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matches = d.pull_new_tba_matches(tbakey, competition, timestamp)
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red = load_metrics(apikey, competition, matches, "red")
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blu = load_metrics(apikey, competition, matches, "blue")
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elo_red_total = 0
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elo_blu_total = 0
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gl2_red_total = 0
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gl2_blu_total + 0
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for team in red:
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return
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def load_metrics(apikey, competition, matches, group_name):
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return_vector = {}
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for match in matches:
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for team in match[group_name]:
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red = load_metrics(apikey, competition, match, "red")
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blu = load_metrics(apikey, competition, match, "blue")
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group = {}
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elo_red_total = 0
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elo_blu_total = 0
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db_data = d.get_team_metrics_data(apikey, competition, team)
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gl2_red_score_total = 0
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gl2_blu_score_total = 0
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if d.get_team_metrics_data(apikey, competition, team) == None:
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gl2_red_rd_total = 0
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gl2_blu_rd_total = 0
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elo = {"score": 1500}
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gl2 = {"score": 1500, "rd": 250, "vol": 0.06}
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ts = {"mu": 25, "sigma": 25/3}
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gl2_red_vol_total = 0
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gl2_blu_vol_total = 0
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d.push_team_metrics_data(apikey, competition, team, {"elo":elo, "gliko2":gl2,"trueskill":ts})
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for team in red:
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group[team] = {"elo": elo, "gl2": gl2, "ts": ts}
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elo_red_total += red[team]["elo"]["score"]
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else:
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gl2_red_score_total += red[team]["gl2"]["score"]
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gl2_red_rd_total += red[team]["gl2"]["rd"]
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gl2_red_vol_total += red[team]["gl2"]["vol"]
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metrics = db_data["metrics"]
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elo = metrics["elo"]
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gl2 = metrics["gliko2"]
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ts = metrics["trueskill"]
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for team in blu:
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group[team] = {"elo": elo, "gl2": gl2, "ts": ts}
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elo_blu_total += blu[team]["elo"]["score"]
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gl2_blu_score_total += blu[team]["gl2"]["score"]
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gl2_blu_rd_total += blu[team]["gl2"]["rd"]
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gl2_blu_vol_total += blu[team]["gl2"]["vol"]
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red_elo = {"score": elo_red_total / len(red)}
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blu_elo = {"score": elo_blu_total / len(blu)}
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red_gl2 = {"score": gl2_red_score_total / len(red), "rd": gl2_red_rd_total / len(red), "vol": gl2_red_vol_total / len(red)}
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blu_gl2 = {"score": gl2_blu_score_total / len(blu), "rd": gl2_blu_rd_total / len(blu), "vol": gl2_blu_vol_total / len(blu)}
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if(match["winner"] == "red"):
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observations = {"red": 1, "blue": 0}
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elif(match["winner"] == "blue"):
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observations = {"red": 0, "blue": 1}
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else:
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observations = {"red": 0.5, "blue": 0.5}
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red_elo_delta = an.elo(red_elo["score"], blu_elo["score"], [observations["red"], observations["blue"]], elo_N, elo_K) - red_elo["score"]
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blu_elo_delta = an.elo(blu_elo["score"], red_elo["score"], [observations["blue"], observations["red"]], elo_N, elo_K) - blu_elo["score"]
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new_red_gl2_score, new_red_gl2_rd, new_red_gl2_vol = an.glicko2(red_gl2["score"], red_gl2["rd"], red_gl2["vol"], [blu_gl2["score"]], [blu_gl2["rd"]], [observations["red"], observations["blue"]])
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new_blu_gl2_score, new_blu_gl2_rd, new_blu_gl2_vol = an.glicko2(blu_gl2["score"], blu_gl2["rd"], blu_gl2["vol"], [red_gl2["score"]], [red_gl2["rd"]], [observations["blue"], observations["red"]])
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red_gl2_delta = {"score": new_red_gl2_score - red_gl2["score"], "rd": new_red_gl2_rd - red_gl2["rd"], "vol": new_red_gl2_vol - red_gl2["vol"]}
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blu_gl2_delta = {"score": new_blu_gl2_score - blu_gl2["score"], "rd": new_blu_gl2_rd - blu_gl2["rd"], "vol": new_blu_gl2_vol - blu_gl2["vol"]}
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for team in red:
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red[team]["elo"]["score"] = red[team]["elo"]["score"] + red_elo_delta
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red[team]["gl2"]["score"] = red[team]["gl2"]["score"] + red_gl2_delta["score"]
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red[team]["gl2"]["rd"] = red[team]["gl2"]["rd"] + red_gl2_delta["rd"]
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red[team]["gl2"]["vol"] = red[team]["gl2"]["vol"] + red_gl2_delta["vol"]
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for team in blu:
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blu[team]["elo"]["score"] = blu[team]["elo"]["score"] + blu_elo_delta
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blu[team]["gl2"]["score"] = blu[team]["gl2"]["score"] + blu_gl2_delta["score"]
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blu[team]["gl2"]["rd"] = blu[team]["gl2"]["rd"] + blu_gl2_delta["rd"]
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blu[team]["gl2"]["vol"] = blu[team]["gl2"]["vol"] + blu_gl2_delta["vol"]
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return_vector.update(red)
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return_vector.update(blu)
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return return_vector
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def load_metrics(apikey, competition, match, group_name):
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for team in match[group_name]:
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group = {}
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db_data = d.get_team_metrics_data(apikey, competition, team)
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if d.get_team_metrics_data(apikey, competition, team) == None:
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elo = {"score": 1500}
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gl2 = {"score": 1500, "rd": 250, "vol": 0.06}
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ts = {"mu": 25, "sigma": 25/3}
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d.push_team_metrics_data(apikey, competition, team, {"elo":elo, "gliko2":gl2,"trueskill":ts})
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group[team] = {"elo": elo, "gl2": gl2, "ts": ts}
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else:
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metrics = db_data["metrics"]
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elo = metrics["elo"]
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gl2 = metrics["gliko2"]
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ts = metrics["trueskill"]
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group[team] = {"elo": elo, "gl2": gl2, "ts": ts}
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return group
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