Milestone: Career DB rebuilt, canonical-ID sync stable, storyline tags correct. Pending: match ranking anchor/breaker.

analysis/player_identity_registry.py

@@ -0,0 +1,54 @@
+import json
+import os
+
+PIR_PATH = os.path.join(os.path.dirname(__file__), "player_identity_registry.json")
+
+class PlayerIdentityRegistry:
+    def __init__(self):
+        if os.path.exists(PIR_PATH):
+            with open(PIR_PATH, "r", encoding="utf-8") as f:
+                self.data = json.load(f)
+        else:
+            self.data = {"uuid_to_canonical": {}, "canonical": {}}
+
+    def save(self):
+        with open(PIR_PATH, "w", encoding="utf-8") as f:
+            json.dump(self.data, f, indent=2)
+
+    def resolve(self, uuid):
+        """Return canonical ID for a UUID, or create one."""
+        uuid = str(uuid)
+        if uuid in self.data["uuid_to_canonical"]:
+            return self.data["uuid_to_canonical"][uuid]
+
+        # Create new canonical ID
+        canonical = f"player_{len(self.data['canonical'])+1}"
+        self.data["uuid_to_canonical"][uuid] = canonical
+        self.data["canonical"][canonical] = {"uuids": [uuid], "names": []}
+        self.save()
+        return canonical
+
+    def add_name(self, canonical, name):
+        entry = self.data["canonical"].setdefault(canonical, {"uuids": [], "names": []})
+        if name not in entry["names"]:
+            entry["names"].append(name)
+            self.save()
+
+    def merge(self, uuid_a, uuid_b):
+        """Merge two UUIDs into one canonical identity."""
+        ca = self.resolve(uuid_a)
+        cb = self.resolve(uuid_b)
+        if ca == cb:
+            return ca
+
+        # Merge cb into ca
+        self.data["canonical"][ca]["uuids"].extend(self.data["canonical"][cb]["uuids"])
+        self.data["canonical"][ca]["names"].extend(self.data["canonical"][cb]["names"])
+
+        # Update uuid_to_canonical
+        for u in self.data["canonical"][cb]["uuids"]:
+            self.data["uuid_to_canonical"][u] = ca
+
+        del self.data["canonical"][cb]
+        self.save()
+        return ca

analysis/player_summary_v2.py

@@ -7,7 +7,6 @@ def build_player_summary(player):
         - Sharpshooter
         - Consistency
         - Clutch
-        - Support Specialist
     """
 
     def safe_pct(value):
@@ -26,7 +25,6 @@ def build_player_summary(player):
     sharp = player.get("sharpshooter", {})
     consistency = player.get("consistency", {})
     clutch = player.get("clutch", {})
-    support = player.get("support_specialist", {})
 
     lines = []
     lines.append(f"{name}\n")
@@ -51,8 +49,8 @@ def build_player_summary(player):
     lines.append(f"\nClutch: {safe_tier(clutch.get('tier'))} ({safe_pct(clutch.get('pct')):.1f}%)")
     lines.append(f"  {clutch.get('summary', '')}")
     
-    # Support Specialist
-    lines.append(f"\nSupport Specialist: {safe_tier(support.get('tier'))} ({safe_pct(support.get('pct')):.1f}%)")
-    lines.append(f"  {support.get('summary', '')}")
+    # Breaker
+    lines.append(f"\nBreaker: {safe_tier(breaker.get('tier'))} ({safe_pct(breaker.get('pct')):.1f}%)")
+    lines.append(f"  {breaker.get('summary', '')}")
 
     return "\n".join(lines)

analysis/rookie_leaderboard.py

@@ -0,0 +1,24 @@
+def compute_rookie_leaderboard(career_db, tag="slayer", limit=10):
+    rookies = []
+
+    for cid, pdata in career_db["players"].items():
+        maps = pdata["career"].get("maps", 0)
+        if maps >= 10:
+            continue  # not a rookie
+
+        tag_data = pdata.get(tag, {})
+        rookies.append({
+            "canonical_id": cid,
+            "name": pdata["name"],
+            "team": pdata.get("team", ""),
+            "maps": maps,
+            "kd": pdata["career"]["KD"],
+            "kills": pdata["career"]["kills"],
+            "score": pdata["career"]["damage"],  # or actual score if available
+            "tag_raw": tag_data.get("raw", 0.0),
+            "tag_pct": tag_data.get("pct", 0.0),
+            "tag_tier": tag_data.get("tier", "D"),
+        })
+
+    rookies.sort(key=lambda r: r["tag_pct"], reverse=True)
+    return rookies[:limit]

analysis/storylines.py

@@ -24,6 +24,8 @@ def summarize_team_tags(team_players):
         "sharpshooter",
         "consistency",
         "clutch",
+        "anchor",
+        "breaker",
     ]
 
     summary = {}
@@ -68,6 +70,8 @@ def compare_team_strengths(teamA, teamB, team_a_name, team_b_name):
         "sharpshooter": "Sharpshooter (Accuracy)",
         "consistency": "Consistency (Stability)",
         "clutch": "Clutch (High-Pressure Performance)",
+        "anchor": "Anchor (Defensive Stability)",
+        "breaker": "Breaker (Offensive Disruption)",
     }
 
     for tag, label in tags.items():
@@ -76,6 +80,18 @@ def compare_team_strengths(teamA, teamB, team_a_name, team_b_name):
 
         diff = a - b
         
+        
+        # Custom storyline for Anchor
+        if tag == "anchor":
+            if abs(diff) < 5:
+                storyline.append("Both teams are evenly matched in defensive stability.")
+            elif diff > 0:
+                storyline.append(f"{team_a_name} have stronger defensive stability, surviving longer and preventing collapses.")
+            else:
+                storyline.append(f"{team_b_name} have stronger defensive stability, giving them an edge in long fights.")
+            continue 
+            
+        # Generic storyline for all other tags
         if abs(diff) < 5:
             storyline.append(f"Both teams are evenly matched in {label}.")
         elif diff > 0:

analysis/team_identity_v2.py

@@ -1,10 +1,17 @@
-
 from utils.safe_tag import safe_pct, safe_tier, safe_avg
 
+# Caster‑friendly display names
+DISPLAY_NAMES = {
+    "slayer": "Slayer",
+    "objective_payload": "Payload Specialist",
+    "sharpshooter": "Sharpshooter",
+    "consistency": "Consistency",
+    "clutch": "Clutch",
+    "anchor": "Anchor Specialist",
+    "breaker": "Breaker",
+}
 
 
-from utils.safe_tag import safe_pct, safe_tier, safe_avg
-
 def summarize_team_tags(team_players):
     """
     Aggregates tag tiers + percentiles for a team.
@@ -14,7 +21,9 @@ def summarize_team_tags(team_players):
         - tier counts
     """
 
-    tags = ["slayer", "objective_payload", "sharpshooter", "consistency", "clutch"]
+    tags = ["slayer", "objective_payload", "sharpshooter",
+            "consistency", "clutch", "anchor", "breaker"]
+
     summary = {}
 
     for tag in tags:
@@ -24,10 +33,10 @@ def summarize_team_tags(team_players):
         for p in team_players:
             tag_data = p.get(tag, {})
             pcts.append(safe_pct(tag_data.get("pct")))
-            tiers.append(safe_tier(tag_data.get("tier")))
+            tiers.append(safe_tier(tag_data.get("tier")))  # guaranteed valid tier
 
         summary[tag] = {
-            "avg_pct": safe_avg(pcts),
+            "avg_pct": safe_avg(pcts),  # guaranteed numeric
             "top_tier": max(tiers, key=lambda t: "SABCD".index(t)),
             "count_S": tiers.count("S"),
             "count_A": tiers.count("A"),
@@ -49,8 +58,9 @@ def classify_team_style(summary):
     sharpshooter = summary["sharpshooter"]["avg_pct"]
     consistency = summary["consistency"]["avg_pct"]
     clutch = summary["clutch"]["avg_pct"]
+    anchor = summary["anchor"]["avg_pct"]
 
-    # Identify primary style
+    # Primary style selection
     primary = max(
         {
             "Slayer-heavy": slayer,
@@ -58,11 +68,12 @@ def classify_team_style(summary):
             "Precision/Sharpshooter": sharpshooter,
             "Stable/Consistent": consistency,
             "High-pressure/Clutch": clutch,
+            "Anchor/Support": anchor,
         }.items(),
         key=lambda x: x[1]
     )[0]
 
-    # Identify weaknesses
+    # Weakness detection
     weaknesses = []
     if slayer < 40:
         weaknesses.append("low elimination pressure")
@@ -74,6 +85,8 @@ def classify_team_style(summary):
         weaknesses.append("inconsistent match-to-match output")
     if clutch < 40:
         weaknesses.append("poor high-pressure performance")
+    if anchor < 40:
+        weaknesses.append("weak defensive backbone / low anchor stability")
 
     return primary, weaknesses
 
@@ -87,15 +100,16 @@ def generate_team_identity_block(team_players, team_name="Team"):
     summary = summarize_team_tags(team_players)
     primary_style, weaknesses = classify_team_style(summary)
 
-    # Build strengths list
+    # Strengths list
     strengths = []
     for tag, data in summary.items():
         if data["avg_pct"] >= 60:
+            display = DISPLAY_NAMES.get(tag, tag.replace("_", " ").title())
             strengths.append(
-                f"Strong {tag.replace('_', ' ').title()} ({data['top_tier']} Tier)"
+                f"Strong {display} ({data['top_tier']} Tier)"
             )
 
-    # Build tag breakdown
+    # Tag breakdown
     tag_block = {}
     for tag, data in summary.items():
         tag_block[tag] = {
@@ -103,7 +117,6 @@ def generate_team_identity_block(team_players, team_name="Team"):
             "tier": data["top_tier"],
         }
 
-    # Return a dict (NOT a string)
     return {
         "team_name": team_name,
         "team_style": primary_style,
@@ -112,6 +125,7 @@ def generate_team_identity_block(team_players, team_name="Team"):
         "tags": tag_block,
     }
 
+
 def format_team_identity(identity_data):
     """
     Converts the identity block dict into a readable text block.
@@ -125,30 +139,30 @@ def format_team_identity(identity_data):
     lines.append("")
 
     # Strengths
+    lines.append("Strengths:")
     if identity_data["strengths"]:
-        lines.append("Strengths:")
         for s in identity_data["strengths"]:
             lines.append(f"  - {s}")
     else:
-        lines.append("Strengths:")
         lines.append("  - None identified")
 
     lines.append("")
 
     # Weaknesses
+    lines.append("Weaknesses:")
     if identity_data["weaknesses"]:
-        lines.append("Weaknesses:")
         for w in identity_data["weaknesses"]:
             lines.append(f"  - {w}")
     else:
-        lines.append("Weaknesses:")
         lines.append("  - None identified")
 
     lines.append("")
     lines.append("Tag Breakdown:")
 
     for tag, data in identity_data["tags"].items():
-        tag_name = tag.replace("_", " ").title()
-        lines.append(f"  - {tag_name}: {data['tier']} Tier (avg {data['avg_pct']:.1f} percentile)")
+        name = DISPLAY_NAMES.get(tag, tag.replace("_", " ").title())
+        lines.append(
+            f"  - {name}: {data['tier']} Tier (avg {data['avg_pct']:.1f} percentile)"
+        )
 
     return "\n".join(lines)

dashleague_cast_tool.py

@@ -33,7 +33,8 @@ from match_engine import (
     split_two_columns,
     compute_slayer_prediction,
     rank_match_players_consistency_career,
-    rank_match_players_support_specialist,
+    rank_match_players_by_tag,
+    _add_score_fields,
 )
 
 # ---------------------------------------------------------
@@ -42,6 +43,9 @@ from match_engine import (
 
 BASE_DIR = os.path.dirname(os.path.abspath(__file__))
 CONFIG_PATH = os.path.join(BASE_DIR, "config.json")
+SCREENS_DIR = os.path.join(BASE_DIR, "screens")  
+
+
 
 # Load config (or default)
 if os.path.exists(CONFIG_PATH):
@@ -253,7 +257,46 @@ class DashLeagueGUI:
             url = f"{API_BASE}/stats?season={self.current_season}"
             data = fetch_json(url)
             stats = data.get("data", [])
-            self.stats_by_id = {p["id"]: p for p in stats}
+            
+            # ---------------------------------------------------------
+            # Load PIR + Career DB
+            # ---------------------------------------------------------
+            from analysis.player_identity_registry import PlayerIdentityRegistry
+            pir = PlayerIdentityRegistry()
+
+            career_path = os.path.join(BASE_DIR, "career_stats.json")
+            with open(career_path, "r", encoding="utf-8") as f:
+                career_db = json.load(f)
+
+            # ---------------------------------------------------------
+            # Rebuild stats_by_id keyed by canonical ID
+            # ---------------------------------------------------------
+            new_stats_by_id = {}
+
+            for p in stats:
+                raw_id = p["id"]
+
+                # Always resolve canonical FIRST
+                canonical = pir.resolve(raw_id)
+                p["canonical_id"] = canonical
+
+                # Attach career tags if available
+                pdata = career_db["players"].get(canonical)
+                if pdata:
+                    p["slayer"] = pdata.get("slayer", {})
+                    p["sharpshooter"] = pdata.get("sharpshooter", {})
+                    p["objective_payload"] = pdata.get("objective_payload", {})
+                    p["objective_domination"] = pdata.get("objective_domination", {})
+                    p["consistency"] = pdata.get("consistency", {})
+                    p["clutch"] = pdata.get("clutch", {})
+                    p["anchor"] = pdata.get("anchor", {})
+                    p["breaker"] = pdata.get("breaker", {})
+
+                # Store under canonical ID
+                new_stats_by_id[canonical] = p
+
+            self.stats_by_id = new_stats_by_id
+            
             self.set_status("Stats synced.")
             messagebox.showinfo("Success", f"Synced {len(stats)} player stats.")
         except Exception as e:
@@ -276,7 +319,10 @@ class DashLeagueGUI:
             
     def on_team_select(self, side):
         team_name = self.team_a_var.get() if side == "A" else self.team_b_var.get()
-        team_players = [p for p in self.stats_by_id.values() if p.get("team") == team_name]
+        team_players = [
+            p for p in self.stats_by_id.values()
+            if p.get("team") == team_name
+        ]
 
         if side == "A":
             self.team_a_players = team_players
@@ -346,6 +392,7 @@ class DashLeagueGUI:
             # Debug
             if self.current_match_players:
                 print("DEBUG MATCH PLAYER:", self.current_match_players[0])
+                print("DEBUG PLAYER KEYS:", list(self.current_match_players[0].keys()))
             else:
                 print("DEBUG MATCH PLAYER: EMPTY LIST")
 
@@ -358,34 +405,51 @@ class DashLeagueGUI:
                 with open(career_path, "r", encoding="utf-8") as f:
                     career_db = json.load(f)
 
+
+            # ---------------------------------------------------------
+            # Resolve canonical IDs for all match players
+            # ---------------------------------------------------------
+            from analysis.player_identity_registry import PlayerIdentityRegistry
+            pir = PlayerIdentityRegistry()
+
+            for p in all_players:
+                raw_uuid = (
+                    p.get("id")
+                    or p.get("PlayerUUID")
+                    or p.get("uuid")
+                )
+                if raw_uuid:
+                    canonical = pir.resolve(raw_uuid)
+                    p["canonical_id"] = canonical
+
+
             # -----------------------------
             # 4. Attach modern career tags
             # -----------------------------
             if career_db is not None:
                 for p in all_players:
-                    pid = (
-                        p.get("id")
-                        or p.get("PlayerUUID")
-                        or p.get("uuid")
-                    )
+                    canonical = p.get("canonical_id")
+                    if not canonical:
+                        continue
 
-                    if pid and pid in career_db["players"]:
-                        pdata = career_db["players"][pid]
+                    pdata = career_db["players"].get(canonical)
+                    if not pdata:
+                        continue
 
-                        # Attach modern tags directly
-                        p["slayer"] = pdata.get("slayer", {})
-                        p["sharpshooter"] = pdata.get("sharpshooter", {})
-                        p["objective_payload"] = pdata.get("objective_payload", {})
+                    # Core tags
+                    p["slayer"] = pdata.get("slayer", {})
+                    p["sharpshooter"] = pdata.get("sharpshooter", {})
+                    p["objective_payload"] = pdata.get("objective_payload", {})
 
-                        # DO NOT overwrite match-based DomObj
-                        if "objective_domination" not in p:
-                            p["objective_domination"] = pdata.get("objective_domination", {})
+                    # Do NOT overwrite match-based DomObj
+                    if "objective_domination" not in p:
+                        p["objective_domination"] = pdata.get("objective_domination", {})
 
-                        p["consistency"] = pdata.get("consistency", {})
-                        p["clutch"] = pdata.get("clutch", {})
-
-                        # Support Specialist
-                        p["support_specialist"] = pdata.get("support_specialist", {})
+                    # Career-based tags
+                    p["consistency"] = pdata.get("consistency", {})
+                    p["clutch"] = pdata.get("clutch", {})
+                    p["anchor"] = pdata.get("anchor", {})
+                    p["breaker"] = pdata.get("breaker", {})
                 
 
             # -----------------------------
@@ -425,6 +489,35 @@ class DashLeagueGUI:
                 write_text(os.path.join(slot_dir, "Captures.txt"), p.get("DOM_Captures", ""))
                 write_text(os.path.join(slot_dir, "Counters.txt"), p.get("DOM_Counters", ""))
 
+
+            # -----------------------------
+            # 6. Export Rookie Leaderboard
+            # -----------------------------
+            from analysis.rookie_leaderboard import compute_rookie_leaderboard
+
+            rookies = compute_rookie_leaderboard(career_db, tag="slayer")  # default tag
+
+            rookie_dir = os.path.join(SCREENS_DIR, "rookies")
+            os.makedirs(rookie_dir, exist_ok=True)
+
+            # Full table
+            table_lines = []
+            for i, r in enumerate(rookies):
+                table_lines.append(
+                    f"{i+1}. {r['name']} — {r['tag_tier']} Tier ({r['tag_pct']:.1f}%) "
+                    f"KD {r['kd']:.2f} — {r['kills']} Kills — {r['score']} Score"
+                )
+            write_text(os.path.join(rookie_dir, "table.txt"), "\n".join(table_lines))
+
+            # Individual rows
+            for i, r in enumerate(rookies):
+                row = (
+                    f"{i+1}. {r['name']} — {r['tag_tier']} Tier ({r['tag_pct']:.1f}%)\n"
+                    f"KD {r['kd']:.2f} — {r['kills']} Kills — {r['score']} Score"
+                )
+                write_text(os.path.join(rookie_dir, f"p{i}.txt"), row)
+
+
             self.set_status("Player slots generated.")
             messagebox.showinfo("Success", "Player slots generated into p0–p9.")
 
@@ -442,6 +535,8 @@ class DashLeagueGUI:
             output_path = os.path.join(BASE_DIR, "career_stats.json")
 
             build_career_database(output_path)
+            #print("DEBUG CAREER DB KEYS:", career_db.keys())
+            #print("DEBUG PLAYER COUNT:", len(career_db.get("players", {})))
 
             self.set_status("Career database built successfully.")
             messagebox.showinfo("Success", "Career database has been built.")
@@ -592,15 +687,6 @@ Consistency Summary:
             if isinstance(score, (int, float)):
                 tags_out.append(f"Cons {score:.2f}")
 
-        # ---------------------------------------------------------
-        # Support Specialist (career)
-        # ---------------------------------------------------------
-        support = player_entry.get("support_specialist", {})
-        if isinstance(support, dict):
-            score = support.get("raw")
-            if isinstance(score, (int, float)):
-                tags_out.append(f"Supp {score:.2f}")
-
         # ---------------------------------------------------------
         # Payload Objective Specialist (match-based)
         # ---------------------------------------------------------
@@ -636,8 +722,8 @@ Consistency Summary:
             return
 
         # Extract players for each team
-        teamA_players = [self.stats_by_id[p["id"]] for p in self.current_match_players if p.get("team") == team_a]
-        teamB_players = [self.stats_by_id[p["id"]] for p in self.current_match_players if p.get("team") == team_b]
+        teamA_players = [self.stats_by_id[p["canonical_id"]] for p in self.current_match_players]
+        teamB_players = [self.stats_by_id[p["canonical_id"]] for p in self.current_match_players]
         
         #print("TEAM A SAMPLE:", teamA_players[0])
         #print("TEAM B SAMPLE:", teamB_players[0])
@@ -718,7 +804,8 @@ Consistency Summary:
             "Domination Objective Specialist",
             "Consistency",
             "Clutch",
-            "Support Specialist",
+            "Anchor",
+            "Breaker",
         ]
 
         ttk.Label(win, text="Select Tag:").pack(anchor="w", padx=10, pady=5)
@@ -743,23 +830,34 @@ Consistency Summary:
             if tag == "Slayer":
                 ranked = rank_match_players_slayer(self.current_match_players)
 
+            elif tag == "Sharpshooter":
+                ranked = rank_match_players_sharpshooter(self.current_match_players)
+
             elif tag == "Payload Objective Specialist":
                 ranked = rank_match_players_objpl(self.current_match_players)
 
             elif tag == "Domination Objective Specialist":
                 ranked = rank_match_players_objdom(self.current_match_players)
 
-            elif tag == "Clutch":
-                ranked = rank_match_players_clutch(self.current_match_players)         
-
             elif tag == "Consistency":
                 ranked = rank_match_players_consistency_career(self.current_match_players)
 
-            elif tag == "Support Specialist":
-                ranked = rank_match_players_support_specialist(self.current_match_players)    
+            elif tag == "Clutch":
+                ranked = rank_match_players_clutch(self.current_match_players)
 
-            else:  # Sharpshooter
-                ranked = rank_match_players_sharpshooter(self.current_match_players)
+            elif tag == "Anchor":
+                ranked = _add_score_fields(
+                    rank_match_players_by_tag(self.current_match_players, "anchor")
+                )
+
+            elif tag == "Breaker":
+                ranked = _add_score_fields(
+                    rank_match_players_by_tag(self.current_match_players, "breaker")
+                )
+
+            else:
+                messagebox.showerror("Error", f"Unknown tag: {tag}")
+                return
 
             if not ranked:
                 output.delete("1.0", tk.END)
@@ -902,6 +1000,24 @@ Consistency Summary:
                 text += "- Collapse Avoidance = Player's lowest per-map performance score\n"
                 text += "- Conversion Rate = (Accuracy × 0.50) + (Headshot Rate × 0.50)\n" 
 
+            elif tag == "Anchor":
+                text += "\nAnchor Formula:\n"
+                text += "Anchor = (Survivability × 0.45) + (DefensivePresence × 0.30) + (Consistency × 0.25)\n"
+                text += "Where:\n"
+                text += "- Survivability = (LeagueAvgDeathsPerMap / PlayerDeathsPerMap), clamped to [0.25, 1.50] then normalized to 0–1\n"
+                text += "- DefensivePresence = (DamagePerMap / LeagueAvgDamagePerMap), clamped to [0, 1.5] then normalized to 0–1\n"
+                text += "- Consistency = normalized 0–1 stability score from the Consistency tag\n"
+                text += "Survivability reflects how hard the player is to remove; Defensive Presence measures baseline contribution; Consistency rewards stable defensive performance.\n"    
+                
+            elif tag == "Breaker":
+                text += "\nBreaker Formula:\n"
+                text += "Breaker = (DamageNorm × 0.60) + (KillsNorm × 0.40)\n"
+                text += "Where:\n"
+                text += "- DamageNorm = Damage per map normalized against league average\n"
+                text += "- KillsNorm = Kills per map normalized against league average\n"
+                text += "Breaker measures disruptive offensive pressure through high damage output and aggressive fragging.\n"
+                
+
             output.delete("1.0", tk.END)
             output.insert(tk.END, text)
 

data/career_db.py

@@ -9,15 +9,18 @@ from tags.objective_domination import compute_dom_objective_for_career_player
 from tags.sharpshooter import compute_sharpshooter_for_career_player
 from tags.consistency import build_consistency_tag
 from tags.clutch import compute_clutch, compute_clutch_raw
-from tags.support_specialist import build_support_specialist_tag
+from tags.anchor import compute_anchor_for_career_player
+from tags.breaker import compute_breaker_raw
 
 from data.league_metrics import compute_league_metrics, compute_league_clutch_metrics
+from data.tag_framework import percentile_rank, tier_from_percentile
+
     
 
 
 def build_career_database(output_path):
     
-    print("USING DB:", db_access.DB_PATH)
+    #print("USING DB:", db_access.DB_PATH)
 
 
     # ---------------------------------------------------------
@@ -29,6 +32,13 @@ def build_career_database(output_path):
         LEFT JOIN players p ON p.PlayerUUID = s.PlayerUUID;
     """)
 
+    # ---------------------------------------------------------
+    # Load Player Identity Registry (PIR)
+    # ---------------------------------------------------------
+    from analysis.player_identity_registry import PlayerIdentityRegistry
+    pir = PlayerIdentityRegistry()
+
+
     if not player_rows:
         print("No players found in local DB.")
         return False
@@ -39,13 +49,21 @@ def build_career_database(output_path):
     # 2. Build per-player career stats from local DB
     # ---------------------------------------------------------
     for row in player_rows:
-        pid = row["PlayerUUID"]
+        raw_uuid = str(row["PlayerUUID"])
         name = row["PlayerGameName"] or "Unknown"
 
-        matches = db_access.get_player_match_history(pid)
+        # Resolve canonical identity
+        canonical_id = pir.resolve(raw_uuid)
+        pir.add_name(canonical_id, name)
+
+        # Use RAW UUID for DB queries
+        matches = db_access.get_player_match_history(raw_uuid)
         if not matches:
             continue
 
+        # Use CANONICAL ID as the key in the career DB
+        pid = canonical_id
+            
         #print("DEBUG MATCH ROW FOR", pid, ":", matches[0])
         #break
 
@@ -176,18 +194,20 @@ def build_career_database(output_path):
     final_db["league_averages"] = league_averages
     
         
-    from tags.support_specialist import compute_support_specialist  # at top of file if not already
         
     # ---------------------------------------------------------
-    # 4.5 Build Support Specialist distribution
+    # 4.6 Build Breaker distribution
     # ---------------------------------------------------------
-    support_distribution = []
+
+
+    breaker_distribution = []
     for pid, pdata in final_db["players"].items():
-        raw_support = compute_support_specialist(pdata, league_averages)
-        support_distribution.append(raw_support)
+        career = pdata["career"]
+        damage_per_map = career["damage"] / max(1, career["maps"])
+        kills_per_map = career["kills"] / max(1, career["maps"])
 
-        # Write back normalized career block
-        pdata["career"] = career
+        raw_breaker = compute_breaker_raw(damage_per_map, kills_per_map)
+        breaker_distribution.append(raw_breaker)    
 
     
     # ---------------------------------------------------------
@@ -242,6 +262,15 @@ def build_career_database(output_path):
             "summary": consistency_result.summary_short
         }
         
+        # Anchor
+        consistency_norm = pdata["consistency"]["raw"]  # normalized 0–1 score
+        pdata["anchor"] = compute_anchor_for_career_player(
+            pdata,
+            league_averages,
+            distributions["anchor"],
+            consistency_norm
+)
+
         # Clutch
         pdata["clutch"] = compute_clutch(
             pdata,
@@ -249,12 +278,23 @@ def build_career_database(output_path):
             clutch_distribution
         )
         
-        # Support Specialist
-        pdata["support_specialist"] = build_support_specialist_tag(
-            pdata,
-            league_averages,
-            support_distribution
-        )
+        # Breaker
+        career = pdata["career"]
+        damage_per_map = career["damage"] / max(1, career["maps"])
+        kills_per_map = career["kills"] / max(1, career["maps"])
+
+        raw_breaker = compute_breaker_raw(damage_per_map, kills_per_map)
+
+        # Percentile + tier
+        pct = percentile_rank(raw_breaker, breaker_distribution)
+        tier = tier_from_percentile(pct)
+
+        pdata["breaker"] = {
+            "raw": raw_breaker,
+            "pct": pct,
+            "tier": tier,
+            "summary": f"Offensive disruptor ({tier} Tier, {pct:.1f} percentile)"
+        }
 
         # ---------------------------------------------------------
         # Consistency (Hybrid Career Tag - New System)

data/league_metrics.py

@@ -43,7 +43,8 @@ def compute_league_metrics(all_players):
         "payload": [],
         "consistency": [],
         "domination": [],
-        "support_specialist": [],
+        "anchor": [],
+        "breaker": [],
     }
 
     # -----------------------------------------
@@ -89,6 +90,9 @@ def compute_league_metrics(all_players):
         for key, values in acc.items()
     }
     
+    # Alias for clarity: deaths is already per-map
+    league_averages["deaths_per_map"] = league_averages.get("deaths", 0.0)
+
     # Minimum smoothing to avoid divide-by-zero explosions
     league_averages["accuracy"] = max(league_averages["accuracy"], 0.05)
     league_averages["headshot_rate"] = max(league_averages["headshot_rate"], 0.03)
@@ -112,12 +116,17 @@ def compute_league_metrics(all_players):
         # Domination
         dist["domination"].append(compute_dom_raw(p))
         
-        from tags.support_specialist import compute_support_specialist
+        from tags.anchor import compute_anchor_raw
 
-        dist["support_specialist"].append(
-            compute_support_specialist(p, league_averages)
+        # Consistency raw score for distribution building
+        # (You already compute consistency later, but for distributions we only need the raw normalized score)
+        consistency_norm = p.get("consistency", {}).get("raw", 0.5)
+
+        dist["anchor"].append(
+            compute_anchor_raw(p, league_averages, consistency_norm)
         )
         
+
     # -----------------------------------------
     # Sort distributions
     # -----------------------------------------

data/tag_framework.py

@@ -1,7 +1,5 @@
 
-
 import bisect
-from tags.support_specialist import build_support_specialist_tag
 
 
 

match_engine.py

@@ -24,6 +24,20 @@ def _get_player_entry(db, pid):
     return db["players"].get(pid)
     
 
+def attach_career_tags_to_match_player(match_player, career_entry):
+    """
+    Injects career tag blocks into a match_player object so that
+    storylines, predictions, and UI panels can access:
+        - consistency
+        - anchor
+        - clutch
+        - breaker
+    """
+    for tag in ("consistency", "anchor", "clutch", "breaker"):
+        if tag in career_entry:
+            match_player[tag] = career_entry[tag]
+
+
 # ---------------------------------------------------------
 # Universal Match Ranking (Career Tags)
 # ---------------------------------------------------------
@@ -48,6 +62,8 @@ def rank_match_players_by_tag(match_players, tag_name):
         if not entry:
             continue
             
+        attach_career_tags_to_match_player(p, entry)    
+
         tag = entry.get(tag_name, {})
         pct = tag.get("pct", 0)
         raw = tag.get("raw", 0.0)
@@ -234,36 +250,3 @@ def compute_slayer_prediction(team_a_players, team_b_players):
     }
     
     
-def rank_match_players_support_specialist(players):
-    """
-    Ranks players by Support Specialist (career tag) using percentile.
-    """
-
-    ranked = []
-
-    for p in players:
-        tag = p.get("support_specialist", {})
-
-        # Use percentile as the ranking basis
-        pct = tag.get("pct")
-        if pct is None:
-            continue
-
-        ranked.append({
-            "name": p.get("name", "Unknown"),
-            "team": p.get("team", ""),
-            "pct": pct,
-            "tier": tag.get("tier", "D"),
-            "summary": tag.get("summary", ""),
-            "score_raw": pct,                  # used for team totals
-            "score_display": f"{pct:.1f}",     # what you see in the table
-        })
-
-    # Sort descending by percentile
-    ranked.sort(key=lambda x: x["pct"], reverse=True)
-
-    # Assign ranks
-    for i, entry in enumerate(ranked, start=1):
-        entry["rank"] = i
-
-    return ranked

rankings.py

@@ -109,37 +109,32 @@ def rank_match_players_clutch(players):
     return ranked
     
     
-def rank_match_players_support_specialist(players):
-    """
-    Ranks players by Support Specialist (career tag).
-    Uses the already-computed tag stored in each player's data.
-    """
     
+# ---------------------------------------------------------
+# Generic Match Tag Ranking (Modern Tag System)
+# ---------------------------------------------------------
+
+def rank_match_players_by_tag(players, tag_name):
     ranked = []
 
     for p in players:
-        tag = p.get("support_specialist", {})
-        raw = tag.get("raw")
+        tag = p.get(tag_name, {})
 
-        # Skip players with no data
-        if raw is None:
-            continue
+        # Modern tags store raw score under "raw"
+        score = 0.0
+        if isinstance(tag, dict):
+            score = tag.get("raw", 0.0)
 
         ranked.append({
             "name": p.get("name", "Unknown"),
             "team": p.get("team", ""),
-            "raw": raw,
-            "pct": tag.get("pct", 0.0),
-            "tier": tag.get("tier", "D"),
-            "summary": tag.get("summary", ""),
-            "score_display": f"{raw:.2f}",
+            "score_raw": score,
+            "score_display": f"{score:.2f}",
         })
 
-    # Sort descending by raw score
-    ranked.sort(key=lambda x: x["raw"], reverse=True)
+    ranked.sort(key=lambda x: x["score_raw"], reverse=True)
 
-    # Assign ranks
-    for i, entry in enumerate(ranked, start=1):
-        entry["rank"] = i
+    for i, r in enumerate(ranked, start=1):
+        r["rank"] = i
 
     return ranked    

tags/anchor.py

@@ -0,0 +1,115 @@
+# ---------------------------------------------------------
+# Anchor Tag — Defensive Stability & Survivability
+# Mode-agnostic, uses only universal stats
+# ---------------------------------------------------------
+
+from tags.tag_framework import build_tag_output
+
+# ---------------------------------------------------------
+# Anchor Summary (caster-friendly)
+# ---------------------------------------------------------
+
+def anchor_summary(tier, pct):
+    if tier == "S":
+        return f"Elite defensive anchor — top {100 - pct:.0f}% in the league for survivability and stability."
+    if tier == "A":
+        return "High-impact anchor with strong survivability and consistent defensive presence."
+    if tier == "B":
+        return "Above-average anchor who provides reliable defensive value."
+    if tier == "C":
+        return "Below-average anchor; inconsistent survivability or defensive presence."
+    return "Struggles to provide defensive stability."
+
+
+# ---------------------------------------------------------
+# Survivability Normalization
+# ---------------------------------------------------------
+
+def compute_survivability_norm(deaths_per_map, league_avg_deaths):
+    """
+    Survivability = league_avg / player_deaths
+    Clamped to [0.25, 1.50], then normalized to 0–1.
+    """
+    if deaths_per_map <= 0:
+        # Extremely rare, but treat as max survivability
+        return 1.0
+
+    raw = league_avg_deaths / deaths_per_map
+
+    # Clamp to avoid extreme values
+    raw = max(0.25, min(1.50, raw))
+
+    # Normalize to 0–1
+    return (raw - 0.25) / (1.50 - 0.25)
+
+
+# ---------------------------------------------------------
+# Defensive Presence Normalization
+# ---------------------------------------------------------
+
+def compute_defensive_presence_norm(damage_per_map, league_avg_damage):
+    """
+    Defensive presence uses damage as a universal proxy.
+    Normalized to league average, clamped to [0, 1.5], then normalized to 0–1.
+    """
+    if league_avg_damage <= 0:
+        return 0.0
+
+    raw = damage_per_map / league_avg_damage
+
+    # Clamp
+    raw = max(0.0, min(1.5, raw))
+
+    # Normalize to 0–1
+    return raw / 1.5
+
+
+# ---------------------------------------------------------
+# Anchor Raw Score
+# ---------------------------------------------------------
+
+def compute_anchor_raw(pdata, league_averages, consistency_norm):
+    """
+    pdata: player stats dict (career-level)
+    league_averages: dict with league-wide averages
+    consistency_norm: 0–1 normalized consistency score
+    """
+
+    c = pdata["career"]
+
+    deaths = c["deaths"]
+    damage = c["damage"]
+    maps = max(1, c["maps"])
+
+    deaths_per_map = deaths / maps
+    damage_per_map = damage / maps
+
+    league_avg_deaths = league_averages.get("deaths_per_map", 1)
+    league_avg_damage = league_averages.get("damage", 1)
+
+    survivability = compute_survivability_norm(deaths_per_map, league_avg_deaths)
+    defensive_presence = compute_defensive_presence_norm(damage_per_map, league_avg_damage)
+
+    # Weighted anchor score
+    raw = (
+        survivability * 0.45 +
+        defensive_presence * 0.30 +
+        consistency_norm * 0.25
+    )
+
+    return max(0.0, min(1.0, raw))
+
+
+# ---------------------------------------------------------
+# Public API
+# ---------------------------------------------------------
+
+def compute_anchor_for_career_player(pdata, league_averages, anchor_distribution, consistency_norm):
+    """
+    pdata: player stats
+    league_averages: league-wide averages
+    anchor_distribution: distribution of raw anchor scores for percentile mapping
+    consistency_norm: 0–1 normalized consistency score (from consistency tag)
+    """
+    raw = compute_anchor_raw(pdata, league_averages, consistency_norm)
+    return build_tag_output(raw, anchor_distribution, anchor_summary)

tags/breaker.py

@@ -0,0 +1,37 @@
+# ============================================================
+# BREAKER TAG (v1 - Mode Safe)
+# ------------------------------------------------------------
+# Breaker measures offensive disruption using only stats that
+# exist for BOTH Payload and Domination:
+#
+#   - Damage per map
+#   - Kills per map
+#
+# No captures, no counters, no streaks, no timing.
+# ============================================================
+
+def compute_breaker_raw(damage_per_map, kills_per_map):
+    """
+    Computes the raw Breaker score (0–infinity).
+    This is later normalized by league distribution.
+
+    Breaker v1:
+        60% damage pressure
+        40% kill pressure
+    """
+    return (0.60 * damage_per_map) + (0.40 * kills_per_map)
+
+
+def build_breaker_summary(tier, pct):
+    """
+    Returns caster-friendly summary text.
+    """
+    if tier == "S":
+        return "One of the league’s top offensive disruptors."
+    if tier == "A":
+        return "A strong pressure player who cracks open defenses."
+    if tier == "B":
+        return "Provides steady offensive pressure."
+    if tier == "C":
+        return "Occasional pressure but inconsistent impact."
+    return "Low offensive disruption output."

tags/support_specialist.py

@@ -1,77 +0,0 @@
-from utils.safe_tag import safe_raw
-
-# ---------------------------------------------------------
-# RAW SCORE CALCULATION
-# ---------------------------------------------------------
-
-
-def compute_support_specialist(player, league_averages):
-    c = player.get("career", {})
-
-    dmg = safe_raw(c.get("damage"))
-    deaths = safe_raw(c.get("deaths"))
-    push_time = safe_raw(c.get("push_time"))
-    dom_caps = safe_raw(c.get("captures"))
-    dom_counters = safe_raw(c.get("counters"))
-
-    # League anchors
-    league_push = max(1.0, league_averages.get("push_time", 1.0))
-    league_dom_actions = max(1.0, league_averages.get("dom_actions", 1.0))
-    league_damage = max(1.0, league_averages.get("damage", 1.0))
-    league_deaths = max(1.0, league_averages.get("deaths", 1.0))
-    league_pressure = max(1e-6, league_averages.get("pressure_eff", 1.0))
-
-    # Objective presence (relative to league, capped)
-    presence_payload = (push_time / league_push)
-    presence_dom = ((dom_caps + dom_counters) / league_dom_actions)
-    objective_presence = max(presence_payload, presence_dom)
-    objective_presence = max(0.0, min(objective_presence, 2.0))
-
-    # Survivability: pressure vs league pressure_eff
-    player_pressure = dmg / max(1.0, deaths)
-    survivability = player_pressure / league_pressure
-    survivability = max(0.0, min(survivability, 2.0))
-
-    # Damage component: relative to league damage
-    damage_component = dmg / league_damage
-    damage_component = max(0.0, min(damage_component, 2.0))
-
-    # Low-death bonus: 1 is good, 0 is bad
-    low_death_bonus = 1.0 - (deaths / league_deaths)
-    low_death_bonus = max(0.0, min(low_death_bonus, 1.0))
-
-    # Weighted sum, then scale back into 0–1
-    raw = (
-        0.35 * objective_presence +
-        0.35 * survivability +
-        0.20 * damage_component +
-        0.10 * low_death_bonus
-    ) / 2.0  # max of the capped components is 2 → divide by 2 to keep ≤ 1
-
-    return raw
-
-# ---------------------------------------------------------
-# TAG BUILDER (RAW → PERCENTILE → TIER → SUMMARY)
-# ---------------------------------------------------------
-
-def build_support_specialist_tag(player, league_averages, distribution):
-    """
-    Converts raw Support Specialist score into full tag output.
-    """
-
-    from tags.tag_framework import build_tag_output
-
-    raw = compute_support_specialist(player, league_averages)
-
-    def summary_fn(tier, pct):
-        if pct >= 85:
-            return "Elite support presence — stabilizes fights and enables strong objective pushes."
-        if pct >= 70:
-            return "Reliable support player with strong survivability and objective presence."
-        if pct >= 50:
-            return "Provides steady support value through survivability and objective actions."
-        if pct >= 30:
-            return "Occasional support impact but inconsistent objective presence."
-        return "Limited support impact — low survivability and minimal objective presence."
-
-    return build_tag_output(raw, distribution, summary_fn)