Rookie system WIP: added seasons_played sync, career stat storage, and leaderboard fixes

analysis/player_identity_registry.py

@@ -3,52 +3,91 @@ 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": {}}
+            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."""
+    # Resolve UUID → canonical ID (and create if needed)
+    # ---------------------------------------------------------
+    def resolve(self, uuid, season=None):
         uuid = str(uuid)
+
+        # Known UUID
         if uuid in self.data["uuid_to_canonical"]:
-            return self.data["uuid_to_canonical"][uuid]
+            cid = self.data["uuid_to_canonical"][uuid]
+            entry = self.data["canonical"][cid]
+            if season is not None:
+                entry["last_season"] = season
+            return cid
 
-        # Create new canonical ID
+        # New UUID → new canonical ID
-        canonical = f"player_{len(self.data['canonical'])+1}"
+        cid = f"player_{len(self.data['canonical']) + 1}"
-        self.data["uuid_to_canonical"][uuid] = canonical
+        self.data["uuid_to_canonical"][uuid] = cid
-        self.data["canonical"][canonical] = {"uuids": [uuid], "names": []}
+        self.data["canonical"][cid] = {
+            "uuids": [uuid],
+            "names": [],
+            "team_history": [],
+            "first_season": season,
+            "last_season": season,
+        }
         self.save()
-        return canonical
+        return cid
 
-    def add_name(self, canonical, name):
+    # ---------------------------------------------------------
-        entry = self.data["canonical"].setdefault(canonical, {"uuids": [], "names": []})
+    # Track name changes
-        if name not in entry["names"]:
+    # ---------------------------------------------------------
+    def update_name(self, canonical_id, name):
+        entry = self.data["canonical"].get(canonical_id)
+        if not entry:
+            return
+
+        if name and 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."""
+    # Track team history
-        ca = self.resolve(uuid_a)
+    # ---------------------------------------------------------
-        cb = self.resolve(uuid_b)
+    def update_team(self, canonical_id, team):
-        if ca == cb:
+        entry = self.data["canonical"].get(canonical_id)
-            return ca
+        if not entry:
+            return
 
-        # Merge cb into ca
+        if team and (not entry["team_history"] or entry["team_history"][-1] != team):
-        self.data["canonical"][ca]["uuids"].extend(self.data["canonical"][cb]["uuids"])
+            entry["team_history"].append(team)
-        self.data["canonical"][ca]["names"].extend(self.data["canonical"][cb]["names"])
+            self.save()
             
-        # Update uuid_to_canonical
+    # ---------------------------------------------------------
-        for u in self.data["canonical"][cb]["uuids"]:
+    # Backwards compatibility: old method name
-            self.data["uuid_to_canonical"][u] = ca
+    # ---------------------------------------------------------
+    def add_name(self, canonical_id, name):
+        """Legacy alias for update_name()."""
+        self.update_name(canonical_id, name)
 
-        del self.data["canonical"][cb]
+    def add_team(self, canonical_id, team):
-        self.save()
+        """Legacy alias for update_team()."""
-        return ca
+        self.update_team(canonical_id, team)        
+            
+            
+
+    # ---------------------------------------------------------
+    # Rookie detection
+    # ---------------------------------------------------------
+    def get_first_season(self, canonical_id):
+        entry = self.data["canonical"].get(canonical_id)
+        if not entry:
+            return None
+        return entry.get("first_season")

analysis/rookie_leaderboard.py

@@ -1,24 +1,98 @@
-def compute_rookie_leaderboard(career_db, tag="slayer", limit=10):
+import os
-    rookies = []
+import json
 
-    for cid, pdata in career_db["players"].items():
+PROJECT_ROOT = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
-        maps = pdata["career"].get("maps", 0)
+CAREER_DB_PATH = os.path.join(PROJECT_ROOT, "career_stats.json")
-        if maps >= 10:
-            continue  # not a rookie
 
-        tag_data = pdata.get(tag, {})
+
-        rookies.append({
+# ---------------------------------------------------------
-            "canonical_id": cid,
+# Load DB
-            "name": pdata["name"],
+# ---------------------------------------------------------
-            "team": pdata.get("team", ""),
+
-            "maps": maps,
+def load_career_db():
-            "kd": pdata["career"]["KD"],
+    if not os.path.exists(CAREER_DB_PATH):
-            "kills": pdata["career"]["kills"],
+        return None
-            "score": pdata["career"]["damage"],  # or actual score if available
+    with open(CAREER_DB_PATH, "r", encoding="utf-8") as f:
-            "tag_raw": tag_data.get("raw", 0.0),
+        return json.load(f)
-            "tag_pct": tag_data.get("pct", 0.0),
+
-            "tag_tier": tag_data.get("tier", "D"),
+
+# ---------------------------------------------------------
+# Identify rookies
+# ---------------------------------------------------------
+
+def get_rookies(db, season):
+    rookies = {}
+
+    for pid, p in db.get("players", {}).items():
+        seasons_played = p.get("seasons_played") or ""
+        season_list = [int(s) for s in seasons_played.split(",") if s.isdigit()]
+
+        # True rookie = only played this season
+        if len(season_list) == 1 and season_list[0] == season:
+            rookies[pid] = p
+
+    return rookies
+
+
+# ---------------------------------------------------------
+# Rank rookies by a selected tag
+# ---------------------------------------------------------
+
+def rank_rookies_by_tag(season, tag_name, limit=10):
+    """
+    Rank rookies using REAL career stats.
+    """
+
+    db = load_career_db()
+    if db is None:
+        return []
+
+    rookies = get_rookies(db, season)
+
+    rows = []
+    for pid, p in rookies.items():
+
+        # Pull stats from career DB (correct source)
+        kills = p.get("kills", 0)
+        deaths = p.get("deaths", 0)
+        score = p.get("score", 0)
+
+        # KD
+        if deaths > 0:
+            kd = kills / deaths
+        else:
+            kd = kills
+
+        # Raw score = KD (for now)
+        raw = kd
+
+        # Percentile placeholder (we can compute real percentiles later)
+        pct = raw
+
+        # Team
+        team = "Unknown"
+        if p.get("team_history"):
+            team = p["team_history"][-1]
+
+        rows.append({
+            "id": pid,
+            "name": p.get("name", "Unknown"),
+            "team": team,
+            "pct": pct,
+            "tier": "C",   # placeholder until rookie tiers are added
+            "raw": raw,
+            "kd": kd,
+            "kills": kills,
+            "deaths": deaths,
+            "score": score,
+            "summary": "",
         })
 
-    rookies.sort(key=lambda r: r["tag_pct"], reverse=True)
+    # Sort by raw score
-    return rookies[:limit]
+    rows.sort(key=lambda x: x["raw"], reverse=True)
+
+    # Assign ranks
+    for i, r in enumerate(rows, start=1):
+        r["rank"] = i
+
+    return rows[:limit]

analysis/storylines.py

@@ -39,9 +39,15 @@ def summarize_team_tags(team_players):
             pcts.append(safe_pct(tag_data.get("pct")))
             tiers.append(safe_tier(tag_data.get("tier")))
 
+        # -----------------------------
+        # FIX: safe top-tier calculation
+        # -----------------------------
+        valid_tiers = [t for t in tiers if t in "SABCD"]
+        top_tier = max(valid_tiers, key=lambda t: "SABCD".index(t)) if valid_tiers else "-"
+
         summary[tag] = {
             "avg_pct": safe_avg(pcts),
-            "top_tier": max(tiers, key=lambda t: "SABCD".index(t)),
+            "top_tier": top_tier,
             "count_S": tiers.count("S"),
             "count_A": tiers.count("A"),
             "count_B": tiers.count("B"),

dashleague_cast_tool.py

@@ -26,6 +26,7 @@ from rankings import (
 from analysis.team_identity_v2 import generate_team_identity_block
 from analysis.storylines import generate_storyline, matchup_storyline
 from analysis.predictions_v2 import generate_prediction
+from analysis.rookie_leaderboard import rank_rookies_by_tag
 
 
 # OBS export
@@ -50,6 +51,8 @@ from match_engine import (
     rank_match_players_clutch,
     compute_slayer_prediction,
     rank_match_players_consistency_career,
+    load_career_db, 
+    attach_career_tags_to_match_player,
 )
 
 from data.tag_framework import percentile_rank, tier_from_percentile
@@ -235,12 +238,15 @@ class DashLeagueGUI:
         self.rankings_button = ttk.Button(top_frame, text="Rankings", command=self.on_rankings)
         self.rankings_button.grid(row=0, column=5, padx=(0, 10))
         
+        self.rookie_button = ttk.Button(top_frame, text="Rookie Leaderboard", command=self.on_rookie_leaderboard)
+        self.rookie_button.grid(row=0, column=6, padx=(0, 10))
+        
         self.output_folder_button = ttk.Button(
             top_frame,
             text="Select Output Folder",
             command=self.choose_output_folder
         )
-        self.output_folder_button.grid(row=0, column=6, padx=(0, 10))
+        self.output_folder_button.grid(row=0, column=7, padx=(0, 10))
         
         self.map_var = tk.StringVar()
         self.map_var.set("Payload")  # default
@@ -315,51 +321,144 @@ class DashLeagueGUI:
             with open(career_path, "r", encoding="utf-8") as f:
                 career_db = json.load(f)
 
+            players_db = career_db.setdefault("players", {})
+
             # ---------------------------------------------------------
-            # Rebuild stats_by_id keyed by canonical ID
+            # BUILD stats_by_id (canonical → enriched player object)
             # ---------------------------------------------------------
             new_stats_by_id = {}
 
             for p in stats:
-                raw_id = p["id"]
+                raw_id = p.get("id")
-                canonical = pir.resolve(raw_id)
+                if not raw_id:
+                    continue
 
-                # Start with API stats
+                # Resolve canonical + stamp seasons
-                merged = dict(p)
+                canonical = pir.resolve(raw_id, season=self.current_season)
+                if not canonical:
+                    continue
 
-                # 🔥 Normalize team field BEFORE anything else
+                # Ensure first_season is set if missing
-                team = merged.get("team")
+                entry = pir.data["canonical"].get(canonical)
-                if team is None:
+                #if entry is not None and entry.get("first_season") is None:
-                    merged["team"] = ""
+                #    entry["first_season"] = self.current_season
+
+                # Normalize DOM fields from API (for DomObj)
+                p["DOM_Captures"] = p.get("DOM_captures", p.get("DOM_Captures", 0))
+                p["DOM_Counters"] = p.get("DOM_counters", p.get("DOM_Counters", 0))
+
+                merged = {
+                    "canonical": canonical,
+                    "name": p.get("name"),
+                    "team": (p.get("team") or "").strip(),
+                    "id": raw_id,
+                    "kills": p.get("kills", 0),
+                    "deaths": p.get("deaths", 0),
+                    "damage": p.get("damage", 0),
+                    "shots": p.get("shots", 0),
+                    "shots_hit": p.get("shots_hit", 0),
+                    "match_stats": p,
+                    "seasons_played": p.get("seasons_played") or p.get("seasons") or "",
+                }
+
+                # Ensure player exists in career DB (so rookies are present)
+                if canonical not in players_db:
+                    players_db[canonical] = {
+                        "name": merged["name"],
+                        "team_history": [merged["team"]] if merged["team"] else [],
+                        "seasons_played": merged.get("seasons_played"),
+                        "slayer": {},
+                        "sharpshooter": {},
+                        "objective_payload": {},
+                        "objective_domination": {},
+                        "consistency": {},
+                        "clutch": {},
+                        "anchor": {},
+                        "breaker": {},
+                    }
+
+                pdata = players_db.get(canonical, {})
+                
+                
+                # Store basic stats into career DB so rookies have real data
+                pdata["kills"] = merged.get("kills", 0)
+                pdata["deaths"] = merged.get("deaths", 0)
+                pdata["damage"] = merged.get("damage", 0)
+                pdata["shots"] = merged.get("shots", 0)
+                pdata["shots_hit"] = merged.get("shots_hit", 0)
+
+                # Score is inside match_stats
+                ms = merged.get("match_stats", {})
+                pdata["score"] = ms.get("score", 0)
+
+                # KD
+                if pdata["deaths"] > 0:
+                    pdata["kd"] = pdata["kills"] / pdata["deaths"]
                 else:
-                    merged["team"] = str(team).strip()
+                    pdata["kd"] = pdata["kills"]
                 
-                # Attach canonical ID
+                # Keep seasons_played updated
-                merged["canonical_id"] = canonical
+                #if merged.get("seasons_played"):
+                #    pdata["seasons_played"] = merged["seasons_played"]
+                    
+                pdata["seasons_played"] = merged.get("seasons_played")
 
                 # Attach career tags
-                pdata = career_db["players"].get(canonical)
+                for tag in (
-                if pdata:
+                    "slayer",
-                    merged["slayer"] = pdata.get("slayer", {})
+                    "sharpshooter",
-                    merged["sharpshooter"] = pdata.get("sharpshooter", {})
+                    "objective_payload",
-                    merged["objective_payload"] = pdata.get("objective_payload", {})
+                    "objective_domination",
-                    merged["objective_domination"] = pdata.get("objective_domination", {})
+                    "consistency",
-                    merged["consistency"] = pdata.get("consistency", {})
+                    "clutch",
-                    merged["clutch"] = pdata.get("clutch", {})
+                    "anchor",
-                    merged["anchor"] = pdata.get("anchor", {})
+                    "breaker",
-                    merged["breaker"] = pdata.get("breaker", {})
+                ):
+                    merged[tag] = pdata.get(tag, {})
 
                 new_stats_by_id[canonical] = merged
                 
-            # 🔥 Now safe to assign
+                # Write merged stats into career DB
+                players_db[canonical]["kills"] = merged["kills"]
+                players_db[canonical]["deaths"] = merged["deaths"]
+                players_db[canonical]["damage"] = merged["damage"]
+                players_db[canonical]["shots"] = merged["shots"]
+                players_db[canonical]["shots_hit"] = merged["shots_hit"]
+                players_db[canonical]["match_stats"] = merged["match_stats"]
+                players_db[canonical]["seasons_played"] = merged["seasons_played"]
+
+                # Compute KD
+                d = merged["deaths"]
+                players_db[canonical]["kd"] = merged["kills"] / d if d > 0 else merged["kills"]
+
+                # Score (inside match_stats)
+                players_db[canonical]["score"] = merged["match_stats"].get("score", 0)
+
+            # ---------------------------------------------------------
+            # Save updated career DB (rookies now included)
+            # ---------------------------------------------------------
+            with open(career_path, "w", encoding="utf-8") as f:
+                json.dump(career_db, f, indent=2)
+
+            # ---------------------------------------------------------
+            # Save PIR (first_season now persisted)
+            # ---------------------------------------------------------
+            pir.save()
+
+            # ---------------------------------------------------------
+            # Replace stats_by_id with enriched version
+            # ---------------------------------------------------------
             self.stats_by_id = new_stats_by_id
 
-            # 🔥 Now safe to inspect teams
+            # ---------------------------------------------------------
+            # Debug: show teams detected
+            # ---------------------------------------------------------
             teams_in_api = sorted({p["team"] for p in new_stats_by_id.values()})
             print("TEAMS IN API:", teams_in_api)
 
             self.set_status("Stats synced.")
             messagebox.showinfo("Success", f"Synced {len(stats)} player stats.")
+
         except Exception as e:
             messagebox.showerror("Error", f"Failed to sync stats:\n{e}")
             self.set_status("Sync failed.")
@@ -449,13 +548,41 @@ class DashLeagueGUI:
             selected_b = selected_b[:5]
             all_players = selected_a + selected_b
             
+            print("=== DEBUG MATCH_STATS SAMPLE ===")
+            print(all_players[0].get("match_stats", {}))
+
             # ---------------------------------------------------------
             # 2. Normalize stat keys BEFORE attaching tags
             # ---------------------------------------------------------
+
             for p in all_players:
-                p["CP_Captures"] = p.get("CP_captures", 0)
+                ms = p.get("match_stats", {})
-                p["DOM_Captures"] = p.get("DOM_captures", 0)
+
-                p["DOM_Counters"] = p.get("DOM_counters", 0)
+                # CP
+                p["CP_Captures"] = (
+                    p.get("CP_Captures")
+                    or p.get("CP_captures")
+                    or ms.get("CP_Captures")
+                    or ms.get("CP_captures")
+                    or 0
+                )
+
+                # DOM
+                p["DOM_Captures"] = (
+                    p.get("DOM_Captures")
+                    or p.get("DOM_captures")
+                    or ms.get("DOM_Captures")
+                    or ms.get("DOM_captures")
+                    or 0
+                )
+
+                p["DOM_Counters"] = (
+                    p.get("DOM_Counters")
+                    or p.get("DOM_counters")
+                    or ms.get("DOM_Counters")
+                    or ms.get("DOM_counters")
+                    or 0
+                )
 
             # ---------------------------------------------------------
             # 3. Resolve canonical IDs AND normalize player ID
@@ -471,14 +598,14 @@ class DashLeagueGUI:
                     or p.get("uuid")
                 )
                 if raw_uuid:
-                    p["canonical_id"] = pir.resolve(raw_uuid)
+                    p["canonical"] = pir.resolve(raw_uuid, season=self.current_season)
 
                 # Normalize ID (AFTER canonical resolution)
                 pid = (
                     p.get("id")
                     or p.get("PlayerUUID")
                     or p.get("uuid")
-                    or p.get("canonical_id")
+                    or p.get("canonical")
                     or p.get("name")
                 )
                 p["id"] = pid
@@ -502,6 +629,13 @@ class DashLeagueGUI:
             # ---------------------------------------------------------
             # 6. Compute match-based Consistency (raw only)
             # ---------------------------------------------------------
+            
+            print("\n=== DEBUG: Player objects BEFORE consistency ===")
+            for p in all_players:
+                print(p.get("name"), "| id:", p.get("id"), "| uuid:", p.get("uuid"), "| PlayerUUID:", p.get("PlayerUUID"), "| canonical:", p.get("canonical_id"))
+                        
+            
+            
             consistency_rows = rank_match_players_consistency_career(all_players)
             consistency_map = {row["id"]: row["score_raw"] for row in consistency_rows}
 
@@ -533,7 +667,7 @@ class DashLeagueGUI:
             # ---------------------------------------------------------
             if career_db is not None:
                 for p in all_players:
-                    cid = p.get("canonical_id")
+                    cid = p.get("canonical")
                     if not cid:
                         continue
 
@@ -546,10 +680,10 @@ class DashLeagueGUI:
                     p["objective_payload"] = pdata.get("objective_payload", {})
                     p["clutch"] = pdata.get("clutch", {})
                     p["anchor"] = pdata.get("anchor", {})
-                    p["breaker_career"] = pdata.get("breaker", {})
+                    p["breaker"] = pdata.get("breaker", {})
 
                     # Do NOT overwrite match-based DomObj
-                    if "objective_domination" not in p:
+                    if "objective_domination" not in p or not p["objective_domination"]:
                         p["objective_domination"] = pdata.get("objective_domination", {})
 
             # ---------------------------------------------------------
@@ -561,17 +695,20 @@ class DashLeagueGUI:
                 counters = dom.get("counters", 0)
                 dom_score = caps * 0.4 + counters * 0.6
 
-                p["objective_domination_components"] = {
+                print("DOM DEBUG:", p["name"], "caps=", caps, "counters=", counters)
+
+                p["objective_domination"] = {
                     "raw": dom_score,
+                    "pct": dom_score,      # <- match panel can now read this
+                    "tier": "-",           # <- neutral tier for single-match view
                     "captures": caps,
                     "counters": counters,
+                    "summary": "",         # optional, keeps shape consistent
                 }
 
-            # ---------------------------------------------------------
+            # 11. Ensure stats_by_id contains all enriched tags
-            # 11. Merge enriched tag data into raw match players
-            # ---------------------------------------------------------
             for p in all_players:
-                cid = p.get("canonical_id")
+                cid = p.get("canonical")
                 if not cid:
                     continue
 
@@ -579,17 +716,10 @@ class DashLeagueGUI:
                 if not enriched:
                     continue
 
-                for key in (
+                # Copy match fields into stats_by_id
-                    "slayer",
+                enriched["team"] = p.get("team")
-                    "sharpshooter",
+                enriched["name"] = p.get("name")
-                    "objective_payload",
+                enriched["id"] = p.get("id")
-                    "objective_domination",
-                    "clutch",
-                    "anchor",
-                    "breaker",
-                ):
-                    if key in enriched:
-                        p[key] = enriched[key]
 
             # ---------------------------------------------------------
             # 12. Update current_match_players
@@ -825,13 +955,24 @@ Consistency Summary:
             return
 
         # ---------------------------------------------------------
-        # Extract players for each team (correct filtering)
+        # 1. Attach career tags to ALL match players (CRITICAL)
+        # ---------------------------------------------------------
+        from match_engine import load_career_db, attach_career_tags_to_match_player
+        career_db = load_career_db()
+
+        # self.stats_by_id keys ARE canonical IDs
+        for cid, p in self.stats_by_id.items():
+            if cid in career_db["players"]:
+                attach_career_tags_to_match_player(p, career_db["players"][cid])
+
+        # ---------------------------------------------------------
+        # 2. Extract players for each team (using enriched objects)
         # ---------------------------------------------------------
         teamA_players = []
         teamB_players = []
 
         for p in self.current_match_players:
-            cid = p.get("canonical_id")
+            cid = p.get("canonical")   # <-- correct key
             if not cid:
                 continue
 
@@ -844,19 +985,15 @@ Consistency Summary:
             elif enriched.get("team") == team_b:
                 teamB_players.append(enriched)
 
-        #print("TEAM A SAMPLE:", teamA_players[0])
-        #print("TEAM B SAMPLE:", teamB_players[0])
-
         if not teamA_players or not teamB_players:
             messagebox.showerror("Error", "No players selected for one or both teams.")
             return
 
-        # -----------------------------------------
+        # ---------------------------------------------------------
-        # 1. Generate storyline + identity block
+        # 3. Generate storyline + identity blocks
-        # -----------------------------------------
+        # ---------------------------------------------------------
         storyline_text = matchup_storyline(teamA_players, teamB_players)
 
-        # Team identity block (per team, using modern dict + formatter)
         identity_data_a = generate_team_identity_block(teamA_players, team_a)
         identity_text_a = format_team_identity(identity_data_a)
 
@@ -871,9 +1008,9 @@ Consistency Summary:
             + identity_text_b
         )
 
-        # -----------------------------------------
+        # ---------------------------------------------------------
-        # 2. Popup window
+        # 4. Popup window
-        # -----------------------------------------
+        # ---------------------------------------------------------
         win = tk.Toplevel(self.root)
         win.title("Match Storyline")
         win.geometry("600x700")
@@ -882,9 +1019,9 @@ Consistency Summary:
         output.pack(expand=True, fill="both", padx=10, pady=10)
         output.insert(tk.END, full_story)
 
-        # -----------------------------------------
+        # ---------------------------------------------------------
-        # 3. Export to OBS
+        # 5. Export to OBS
-        # -----------------------------------------
+        # ---------------------------------------------------------
         def export():
             content = output.get("1.0", tk.END).strip()
             if not content:
@@ -925,7 +1062,6 @@ Consistency Summary:
             "Clutch",
             "Anchor",
             "Breaker",
-            "Rookie",
         ]
 
         ttk.Label(win, text="Select Tag:").pack(anchor="w", padx=10, pady=5)
@@ -1167,6 +1303,38 @@ Consistency Summary:
         ttk.Button(win, text="Show Rankings", command=show).pack(pady=5)
    
 
+    def on_rookie_leaderboard(self):
+        from analysis.rookie_leaderboard import rank_rookies_by_tag
+
+        season = self.current_season
+        tag = "slayer"   # default tag for rookie leaderboard
+
+        rookies = rank_rookies_by_tag(season, tag)
+
+        # Build text output
+        lines = []
+        lines.append(f"ROOKIE LEADERBOARD — {tag.upper()} — Season {season}")
+        lines.append("")
+        lines.append(f"{'Rank':<5} {'Name':<18} {'Team':<8} {'Tier':<6} {'Pct':<6} {'Raw':<6}")
+        lines.append("-" * 60)
+
+        for r in rookies:
+            pct = f"{r['pct']:.0f}%" if r["pct"] is not None else "-"
+            raw = f"{r['raw']:.2f}"
+            lines.append(f"{r['rank']:<5} {r['name']:<18} {r['team']:<8} {r['tier']:<6} {pct:<6} {raw:<6}")
+
+        text = "\n".join(lines)
+
+        # Popup window
+        win = tk.Toplevel(self.root)
+        win.title("Rookie Leaderboard")
+        win.geometry("600x500")
+
+        output = tk.Text(win, wrap="word")
+        output.pack(expand=True, fill="both", padx=10, pady=10)
+        output.insert(tk.END, text)
+
+        
     def export_all_obs_files(self):
         """
         Unified export function that writes all OBS text files

data/career_db.py

@@ -52,15 +52,18 @@ def build_career_database(output_path):
         raw_uuid = str(row["PlayerUUID"])
         name = row["PlayerGameName"] or "Unknown"
 
-        # Resolve canonical identity
+        # Get this player's full match history
-        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
 
+        # Infer "season" from earliest CycleID (or whatever you treat as season)
+        first_cycle = min(m.get("CycleID", 0) for m in matches) or 0
+
+        # Resolve canonical identity AND stamp first_season
+        canonical_id = pir.resolve(raw_uuid, season=first_cycle)
+        pir.add_name(canonical_id, name)
+
         # Use CANONICAL ID as the key in the career DB
         pid = canonical_id
             
@@ -215,131 +218,50 @@ def build_career_database(output_path):
     # ---------------------------------------------------------
     for pid, pdata in final_db["players"].items():
 
+        # -----------------------------------------------------
         # Slayer
+        # -----------------------------------------------------
         pdata["slayer"] = compute_slayer_for_career_player(
             pdata,
             league_averages,
             distributions["slayer"]
         )
 
+        # -----------------------------------------------------
         # Sharpshooter
+        # -----------------------------------------------------
         pdata["sharpshooter"] = compute_sharpshooter_for_career_player(
             pdata["career"],
             league_averages,
             distributions["sharpshooter"]
         )
 
+        # -----------------------------------------------------
         # Payload Objective Specialist
+        # -----------------------------------------------------
         pdata["objective_payload"] = compute_payload_tag(
             pdata,
             league_averages,
             distributions["payload"]
         )
 
+        # -----------------------------------------------------
         # Domination Objective Specialist
+        # -----------------------------------------------------
         pdata["objective_domination"] = compute_dom_objective_for_career_player(
             pdata,
             league_averages,
             distributions["domination"]
         )
 
-        # Consistency (legacy adapter)
-        consistency_result = build_consistency_tag(
-            floor_current=pdata.get("floor_current"),
-            floor_career=pdata.get("floor_career"),
-            floor_league=league_averages.get("consistency_floor", 0.0),
-            stability_current=pdata.get("stability_current"),
-            stability_career=pdata.get("stability_career"),
-            stability_league=league_averages.get("consistency_stability", 0.0),
-            average_current=pdata.get("average_current"),
-            average_career=pdata.get("average_career"),
-            average_league=league_averages.get("consistency_average", 0.0),
-            matches_played_current=pdata["career"].get("maps", 0),
-            percentile=None
-        )
-        pdata["consistency"] = {
-            "raw": consistency_result.normalized_score,
-            "summary": consistency_result.summary_short
-        }
-        
-        # ---------------------------------------------------------
-        # Consistency Percentile + Tier (NEW)
-        # ---------------------------------------------------------
-        raw_cons = pdata["consistency"]["raw"]
-
-        # Build distribution if missing
-        if "consistency" not in distributions:
-            distributions["consistency"] = [
-                p["consistency"]["raw"]
-                for p in all_players
-                if "consistency" in p and isinstance(p["consistency"], dict)
-            ]
-
-        # Percentile lookup
-        pct = percentile_rank(raw_cons, distributions["consistency"])
-        tier = tier_from_percentile(pct)
-
-        pdata["consistency"]["pct"] = pct
-        pdata["consistency"]["tier"] = tier
-        pdata["consistency"]["summary"] = (
-            f"{tier} Tier Consistency ({pct:.1f} percentile)"
-        )
-        
-        
-        # 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,
-            league_averages,
-            clutch_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)
         # ---------------------------------------------------------
-
         matches = pdata["matches"]
         maps_played = pdata["career"].get("maps", 0)
 
-        # ---------------------------------------------------------
-        # Extract per-match performance components
-        # ---------------------------------------------------------
-        # NOTE:
-        # If you later add per-match slayer/objective/accuracy scores,
-        # this block will automatically support them.
-        # For now, we compute a simple per-match performance score
-        # using the same formula as the legacy system.
-        # ---------------------------------------------------------
-
         per_match_scores = []
         for m in matches:
-            # Slayer-like component
             dmg = m.get("Damage", 0)
             kills = m.get("Kills", 0)
             deaths = m.get("Deaths", 0)
@@ -351,7 +273,6 @@ def build_career_database(output_path):
                 (kd / 5) * 0.20
             )
 
-            # Objective-like component
             push = m.get("PAY_PushTime", 0)
             caps = m.get("DOM_Captures", 0)
             counters = m.get("DOM_Counters", 0)
@@ -362,25 +283,18 @@ def build_career_database(output_path):
                 (counters / 20) * 0.30
             )
 
-            # Accuracy-like component
             shots = m.get("Shots", 0)
             shots_hit = m.get("ShotsHit", 0)
             accuracy = (shots_hit / shots) if shots > 0 else 0.0
-
             accuracy_component = accuracy * 0.20
 
-            # Final per-match performance score
             perf = slayer_component + objective_component + accuracy_component
             per_match_scores.append(perf)
 
-        # ---------------------------------------------------------
-        # Compute floor, stability, average
-        # ---------------------------------------------------------
         if per_match_scores:
             floor_value = min(per_match_scores)
             avg_value = sum(per_match_scores) / len(per_match_scores)
 
-            # Variance adjusted for match count
             mean = avg_value
             variance = sum((x - mean) ** 2 for x in per_match_scores) / len(per_match_scores)
             adjusted_variance = variance * (1 + 1 / max(1, len(per_match_scores)))
@@ -390,12 +304,9 @@ def build_career_database(output_path):
             avg_value = 0.0
             stability_value = 0.0
 
-        # ---------------------------------------------------------
-        # Build hybrid consistency tag
-        # ---------------------------------------------------------
         consistency_result = build_consistency_tag(
             floor_current=floor_value,
-            floor_career=floor_value,      # career = all matches
+            floor_career=floor_value,
             floor_league=league_averages.get("consistency_floor", 0.0),
 
             stability_current=stability_value,
@@ -410,12 +321,9 @@ def build_career_database(output_path):
             percentile=None
         )
 
-        # ---------------------------------------------------------
-        # Store in DB (GUI + Rankings + Spotlight compatible)
-        # ---------------------------------------------------------
         pdata["consistency"] = {
             "raw": consistency_result.normalized_score,
-            "pct": consistency_result.percentile,
+            "pct": None,
             "tier": consistency_result.tier,
             "summary": consistency_result.summary_short,
             "components": {
@@ -426,13 +334,62 @@ def build_career_database(output_path):
             "extras": consistency_result.extras,
         }
         
-        # Clutch (FINAL TAG)
+        # ---------------------------------------------------------
+        # Career Consistency Percentile + Tier (NEW)
+        # ---------------------------------------------------------
+        raw_cons = pdata["consistency"]["raw"]
+        cons_dist = distributions.get("consistency", [])
+
+        pct = percentile_rank(raw_cons, cons_dist)
+        tier = tier_from_percentile(pct)
+
+        pdata["consistency"]["pct"] = pct
+        pdata["consistency"]["tier"] = tier
+        pdata["consistency"]["summary"] = (
+            f"{tier} Tier Consistency ({pct:.1f} percentile)"
+        )
+
+        # ---------------------------------------------------------
+        # Anchor (requires consistency)
+        # ---------------------------------------------------------
+        consistency_norm = pdata["consistency"]["raw"]
+        pdata["anchor"] = compute_anchor_for_career_player(
+            pdata,
+            league_averages,
+            distributions["anchor"],
+            consistency_norm
+        )
+
+        # ---------------------------------------------------------
+        # Clutch
+        # ---------------------------------------------------------
         pdata["clutch"] = compute_clutch(
             pdata,
             league_averages,
             clutch_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)
+        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)"
+        }
+        
+    # Save PIR with first_season stamped for all canonical IDs
+    pir.save()    
+
     # ---------------------------------------------------------
     # 6. Save DB
     # ---------------------------------------------------------

match_engine.py

@@ -210,6 +210,7 @@ def rank_match_players_consistency_career(match_players):
     for i, p in enumerate(ranked, 1):
         out.append({
             "rank": i,
+            "id": p["id"],
             "name": p["name"],
             "team": p.get("team", "Unknown"),
             "score_raw": p["raw"],

rankings.py

@@ -58,7 +58,7 @@ def top_players_by_tag(tag_name, limit=20):
 
 
 # ---------------------------------------------------------
-# Match-Based Consistency Ranking (Still Used in UI)
+# Match-Based Consistency Ranking (Modernized)
 # ---------------------------------------------------------
 
 def rank_match_players_consistency(players):
@@ -66,13 +66,17 @@ def rank_match_players_consistency(players):
 
     for p in players:
         tag = p.get("consistency", {})
-        score = tag.get("raw", 0.0)
+        raw = tag.get("raw", 0.0)
+        pct = tag.get("pct", None)
+        tier = tag.get("tier", None)
 
         ranked.append({
             "name": p.get("name", "Unknown"),
             "team": p.get("team", ""),
-            "score_raw": score,
+            "score_raw": raw,
-            "score_display": f"{score:.2f}",
+            "score_display": f"{raw:.2f}",
+            "pct": pct,
+            "tier": tier,
         })
 
     ranked.sort(key=lambda x: x["score_raw"], reverse=True)
@@ -84,7 +88,7 @@ def rank_match_players_consistency(players):
 
 
 # ---------------------------------------------------------
-# Match-Based Clutch Ranking (Still Used in UI)
+# Match-Based Clutch Ranking (Modernized)
 # ---------------------------------------------------------
 
 def rank_match_players_clutch(players):
@@ -92,13 +96,17 @@ def rank_match_players_clutch(players):
 
     for p in players:
         tag = p.get("clutch", {})
-        score = tag.get("raw", 0.0)
+        raw = tag.get("raw", 0.0)
+        pct = tag.get("pct", None)
+        tier = tag.get("tier", None)
 
         ranked.append({
             "name": p.get("name", "Unknown"),
             "team": p.get("team", ""),
-            "score_raw": score,
+            "score_raw": raw,
-            "score_display": f"{score:.2f}",
+            "score_display": f"{raw:.2f}",
+            "pct": pct,
+            "tier": tier,
         })
 
     ranked.sort(key=lambda x: x["score_raw"], reverse=True)
@@ -109,7 +117,6 @@ def rank_match_players_clutch(players):
     return ranked
 
 
-    
 # ---------------------------------------------------------
 # Generic Match Tag Ranking (Modern Tag System)
 # ---------------------------------------------------------
@@ -118,14 +125,18 @@ def rank_match_players_by_tag(players, tag):
     rows = []
 
     for p in players:
-        tag_data = p.get(tag) or {}   # <‑‑‑ FIX HERE
+        tag_data = p.get(tag) or {}
-        raw = tag_data.get("raw", 0)
+        raw = tag_data.get("raw", 0.0)
+        pct = tag_data.get("pct", None)
+        tier = tag_data.get("tier", None)
 
         rows.append({
             "name": p.get("name", "Unknown"),
             "team": p.get("team", ""),
             "score_raw": raw,
             "score_display": f"{raw:.2f}",
+            "pct": pct,
+            "tier": tier,
         })
 
     rows.sort(key=lambda x: x["score_raw"], reverse=True)
@@ -136,11 +147,11 @@ def rank_match_players_by_tag(players, tag):
     return rows
 
 
+# ---------------------------------------------------------
+# Split into two columns for UI
+# ---------------------------------------------------------
+
 def split_two_columns(ranked, team_a, team_b):
-    """
-    ranked: list of rows returned by rank_match_players_* functions.
-    Returns two lists: left (team_a) and right (team_b).
-    """
     left = [r for r in ranked if r.get("team") == team_a]
     right = [r for r in ranked if r.get("team") == team_b]
     return left, right