Multitag: invertir colores en defensivo (y en tags negativos)

El borde verde/rojo del z-score indicaba 'arriba/abajo de la media' sin tener
en cuenta si más es mejor o peor. Ahora:
- Paneles DEFENSIVOS: se invierte siempre (z alto = concedés más = rojo).
- Tags negativos en ofensivo (NEGATIVE_TAGS, hoy vacío): se invierten.
Aplica a matplotlib y plotly, multitag y centros. Neutral (|z|<0.5) sin cambios.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>

src/racing_reports/reports/triple_multitag.py

@@ -656,7 +656,17 @@ def _zscore(col: pd.Series, value: float) -> float:
     return float((value - mu) / sd)
 
 
-def _z_color(z: float) -> str:
+# Tags "negativos" en OFENSIVO: más = peor para el equipo (se invierten los colores
+# verde/rojo). Vacío por ahora — casi todos los tags del multitag son recursos ofensivos
+# donde más = más producción. El defensivo se invierte SIEMPRE aparte (ver is_def).
+NEGATIVE_TAGS: set[str] = set()
+
+
+def _z_color(z: float, invert: bool = False) -> str:
+    # invert=True → un z alto es MALO (rojo) y un z bajo es BUENO (verde). Se usa para
+    # los paneles defensivos (lo que concedés) y para tags negativos en ofensivo.
+    if invert:
+        z = -z
     a = abs(z)
     if a < 0.5:
         return "#F2C14E"
@@ -675,7 +685,7 @@ def _legend_handles():
     ]
 
 
-def _draw_panel(ax, side_df, tags, tag_groups, team, rng, *, title="", legend=False) -> None:
+def _draw_panel(ax, side_df, tags, tag_groups, team, rng, *, title="", legend=False, is_def=False) -> None:
     n = len(tags)
     y = np.arange(n)[::-1]
     ax.axvspan(-1, 1, color="#000000", alpha=0.04, zorder=0)
@@ -686,6 +696,7 @@ def _draw_panel(ax, side_df, tags, tag_groups, team, rng, *, title="", legend=Fa
     has_team = team in side_df.index
     for i, tag in enumerate(tags):
         yi = y[i]
+        inv = is_def ^ (tag in NEGATIVE_TAGS)  # defensivo o tag negativo → invertir verde/rojo
         for metric, (marker, unit) in metric_style.items():
             yj = yi + metric_dy[metric]
             col = side_df[(tag, metric)]
@@ -695,7 +706,7 @@ def _draw_panel(ax, side_df, tags, tag_groups, team, rng, *, title="", legend=Fa
             val = float(col.get(team, 0.0)) if has_team else 0.0
             z = _zscore(col, val) if has_team else 0.0
             ax.scatter([z], [yj], marker=marker, s=140, color=METRIC_COLOR[metric],
-                       edgecolors=_z_color(z), linewidths=2.0, zorder=4)
+                       edgecolors=_z_color(z, inv), linewidths=2.0, zorder=4)
             txt = f"{val:.2f} xG" if metric == "xg" else f"{int(round(val))} {unit}"
             ax.annotate(txt, (z, yj), textcoords="offset points", xytext=(9, 0), va="center",
                         fontsize=7, bbox=dict(boxstyle="round,pad=0.18", fc="#FFFFFF",
@@ -720,8 +731,9 @@ def _draw_panel(ax, side_df, tags, tag_groups, team, rng, *, title="", legend=Fa
 def plot_triple(side_df: pd.DataFrame, team: str, side_label: str, title_team: str, seed: int = 7) -> plt.Figure:
     """Figura de z-scores triple multitag (1 panel) para un equipo y un lado."""
     rng = np.random.default_rng(seed)
+    is_def = "defensiv" in side_label.lower()
     fig, ax = plt.subplots(figsize=(11, 0.62 * len(TAGS) + 2.0), facecolor="#FFFFFF")
-    _draw_panel(ax, side_df, TAGS, TAG_GROUPS, team, rng, legend=True)
+    _draw_panel(ax, side_df, TAGS, TAG_GROUPS, team, rng, legend=True, is_def=is_def)
     fig.suptitle(f"Z-Score Multi-Tag — Triple Análisis  |  {side_label}\n{title_team}",
                  fontsize=13, fontweight="bold")
     fig.tight_layout(rect=(0, 0, 1, 0.97))
@@ -742,6 +754,7 @@ def _grouped_centros_df(detail_df: pd.DataFrame) -> pd.DataFrame:
 def plot_centros(detail_df: pd.DataFrame, team: str, side_label: str, title_team: str, seed: int = 7) -> plt.Figure:
     """Figura de z-scores de centros: 2 paneles (detalle por tipo·lado + agrupado)."""
     rng = np.random.default_rng(seed)
+    is_def = "defensiv" in side_label.lower()
     grouped_df = _grouped_centros_df(detail_df)
     grouped_groups = [[g] for g in CENTROS_GROUPED]
     fig, (axd, axg) = plt.subplots(
@@ -749,9 +762,9 @@ def plot_centros(detail_df: pd.DataFrame, team: str, side_label: str, title_team
         gridspec_kw={"width_ratios": [1.15, 1.0]},
     )
     _draw_panel(axd, detail_df, CENTROS_DETAIL, CENTROS_DETAIL_GROUPS, team, rng,
-                title="Desglose por tipo · lado", legend=True)
+                title="Desglose por tipo · lado", legend=True, is_def=is_def)
     _draw_panel(axg, grouped_df, list(CENTROS_GROUPED), grouped_groups, team, rng,
-                title="Vista agrupada")
+                title="Vista agrupada", is_def=is_def)
     fig.suptitle(f"Z-Score Centros — Triple Análisis  |  {side_label}\n{title_team}",
                  fontsize=13, fontweight="bold")
     fig.tight_layout(rect=(0, 0, 1, 0.96))
@@ -786,7 +799,7 @@ def _fmt_val(metric: str, v: float) -> str:
 
 
 def _plotly_panel(fig, side_df: pd.DataFrame, tags: list[str], tag_groups: list[list[str]],
-                  team: str, row: int, col: int, rng, show_legend: bool) -> None:
+                  team: str, row: int, col: int, rng, show_legend: bool, is_def: bool = False) -> None:
     import plotly.graph_objects as go
     n = len(tags)
     ybase = {t: (n - 1 - i) for i, t in enumerate(tags)}
@@ -816,7 +829,7 @@ def _plotly_panel(fig, side_df: pd.DataFrame, tags: list[str], tag_groups: list[
                 zz, vv = z[i], float(c.iloc[i])
                 hx.append(zz); hy.append(ybase[tag] + _METRIC_DY[metric])
                 hcd.append([team, _fmt_val(metric, vv), tag, mlabel])
-                hborder.append(_z_color(zz))   # borde según magnitud/signo del z
+                hborder.append(_z_color(zz, is_def ^ (tag in NEGATIVE_TAGS)))  # verde/rojo (invertido si defensivo o tag negativo)
                 htext.append(_fmt_val(metric, vv))
             fig.add_trace(go.Scatter(
                 x=hx, y=hy, mode="markers+text", legendgroup=mlabel, showlegend=False,
@@ -843,8 +856,9 @@ def _plotly_panel(fig, side_df: pd.DataFrame, tags: list[str], tag_groups: list[
 def plotly_triple(side_df: pd.DataFrame, team: str, side_label: str, title_team: str, seed: int = 7):
     from plotly.subplots import make_subplots
     rng = np.random.default_rng(seed)
+    is_def = "defensiv" in side_label.lower()
     fig = make_subplots(rows=1, cols=1)
-    _plotly_panel(fig, side_df, TAGS, TAG_GROUPS, team, 1, 1, rng, show_legend=True)
+    _plotly_panel(fig, side_df, TAGS, TAG_GROUPS, team, 1, 1, rng, show_legend=True, is_def=is_def)
     fig.update_layout(template="plotly_white", hovermode="closest",
                       height=_ROW_PX * len(TAGS) + 180,
                       font=dict(size=13),
@@ -856,12 +870,13 @@ def plotly_triple(side_df: pd.DataFrame, team: str, side_label: str, title_team:
 def plotly_centros(detail_df: pd.DataFrame, team: str, side_label: str, title_team: str, seed: int = 7):
     from plotly.subplots import make_subplots
     rng = np.random.default_rng(seed)
+    is_def = "defensiv" in side_label.lower()
     grouped_df = _grouped_centros_df(detail_df)
     grouped_groups = [[g] for g in CENTROS_GROUPED]
     fig = make_subplots(rows=1, cols=2, horizontal_spacing=0.18,
                         subplot_titles=("Desglose por tipo · lado", "Vista agrupada"))
-    _plotly_panel(fig, detail_df, CENTROS_DETAIL, CENTROS_DETAIL_GROUPS, team, 1, 1, rng, show_legend=True)
-    _plotly_panel(fig, grouped_df, list(CENTROS_GROUPED), grouped_groups, team, 1, 2, rng, show_legend=False)
+    _plotly_panel(fig, detail_df, CENTROS_DETAIL, CENTROS_DETAIL_GROUPS, team, 1, 1, rng, show_legend=True, is_def=is_def)
+    _plotly_panel(fig, grouped_df, list(CENTROS_GROUPED), grouped_groups, team, 1, 2, rng, show_legend=False, is_def=is_def)
     fig.update_layout(template="plotly_white", hovermode="closest",
                       height=_ROW_PX * len(CENTROS_DETAIL) + 200,
                       font=dict(size=13),