diff --git a/templates/partials/sparkline.html b/templates/partials/sparkline.html
index 6aab777..68e813d 100644
--- a/templates/partials/sparkline.html
+++ b/templates/partials/sparkline.html
@@ -19,8 +19,8 @@
 
 {% macro path_band(lower_points, upper_points, vb_height) %}
 {% if lower_points and upper_points %}
-M{% for value, position in lower_points %}{{ (position * vb_width)+margin | int }} {{ (vb_height - value)+margin | int }}{% if not loop.last %} L{% endif %}{% endfor %}
-{% for value, position in upper_points|reverse %} L{{ (position * vb_width)+margin | int }} {{ (vb_height - value)+margin | int }}{% endfor %} Z
+M{% for value, position in lower_points %}{{ (((position * vb_width) + margin) | int) }} {{ (((vb_height - value) + margin) | int) }}{% if not loop.last %} L{% endif %}{% endfor %}
+{% for value, position in upper_points|reverse %} L{{ (((position * vb_width) + margin) | int) }} {{ (((vb_height - value) + margin) | int) }}{% endfor %} Z
 {% endif %}
 {% endmacro %}
 
@@ -30,7 +30,16 @@ M{% for value, position in lower_points %}{{ (position * vb_width)+margin | int
 {% set y = (vb_height - value)+margin %}
 <circle cx="{{ x | int }}" cy="{{ y | int }}" r="1"></circle>
 {% endfor %}
-{% endmacro %}
+{% endmacro %}
+
+{% macro forecast_circles(data_points, labels, color) %}
+{% for value, position in data_points %}
+{% set x = (position * vb_width)+margin %}
+{% set y = (vb_height - value)+margin %}
+<circle cx="{{ x | int }}" cy="{{ y | int }}" r="1.6" fill="{{ color }}" stroke="{{ color }}"
+    class="pnt-{{ unique_id }}" data-msg="{{ labels[loop.index0][1] }}"></circle>
+{% endfor %}
+{% endmacro %}
 
 {% macro plot_line(points, color) %}
 <path d="{{ path(points, vb_height) }}" stroke="{{ color }}" fill="none" />
@@ -224,10 +233,10 @@ M{% for value, position in lower_points %}{{ (position * vb_width)+margin | int
     {% endif %}
     <svg viewBox="0 0 {{ (vb_width + 2*margin) | int }} {{ (vb_height + 2*margin) | int }}" preserveAspectRatio="none">
         {% if forecast_enabled and forecast.available %}
-        <path d="{{ path_band(forecast_band_lower, forecast_band_upper, vb_height) }}" fill="#10b981" fill-opacity="0.14" stroke="none"></path>
-        <path d="{{ path(forecast_points, vb_height) }}" stroke="#059669" stroke-width="1.5" stroke-dasharray="4,3" fill="none"></path>
-        {{ circles(forecast_points, '#059669') }}
-        <line x1="{{ (forecast_start_position * vb_width)+margin | int }}" y1="{{ margin }}" x2="{{ (forecast_start_position * vb_width)+margin | int }}" y2="{{ vb_height + margin }}" stroke="#059669" stroke-width="0.8" stroke-dasharray="2,2" stroke-opacity="0.7"></line>
+        <path d="{{ path_band(forecast_band_lower, forecast_band_upper, vb_height) }}" fill="#10b981" fill-opacity="0.10" stroke="none"></path>
+        <path d="{{ path(forecast_points, vb_height) }}" stroke="#059669" stroke-width="2" stroke-dasharray="5,3" fill="none"></path>
+        {{ forecast_circles(forecast_points, forecast_labels, '#059669') }}
+        <line x1="{{ ((forecast_start_position * vb_width) + margin) | int }}" y1="{{ margin }}" x2="{{ ((forecast_start_position * vb_width) + margin) | int }}" y2="{{ vb_height + margin }}" stroke="#059669" stroke-width="0.8" stroke-dasharray="2,2" stroke-opacity="0.5"></line>
         {% endif %}
         {% for plot in plots %}
         <g class="{{ plot.label }}" style="fill: {{ plot.color }}; stroke: {{ plot.color }};">
@@ -236,15 +245,22 @@ M{% for value, position in lower_points %}{{ (position * vb_width)+margin | int
         {% endfor %}
 
         <g style="fill-opacity: 0%">
-            {% for pos, message in plot_labels %}
+            {% for pos, message in plot_labels %}
             {% set x = (pos * vb_width) - (stroke_width/2) + margin %}
             {% set y = 0 %}
             {% set width = stroke_width %}
             {% set height = vb_height + margin %}
             <rect x="{{ x | int }}" y="{{ y | int }}" width="{{ width | int }}" height="{{ height | int }}"
-                class="pnt-{{ unique_id }}" data-msg="{{ message }}"></rect>
-            {% endfor %}
-        </g>
+                class="pnt-{{ unique_id }}" data-msg="{{ message }}"></rect>
+            {% endfor %}
+            {% if forecast_enabled and forecast.available %}
+            {% for pos, message in forecast_labels %}
+            {% set x = (pos * vb_width) - (stroke_width/2) + margin %}
+            <rect x="{{ x | int }}" y="0" width="{{ stroke_width | int }}" height="{{ (vb_height + margin) | int }}"
+                class="pnt-{{ unique_id }}" data-msg="{{ message }}"></rect>
+            {% endfor %}
+            {% endif %}
+        </g>
 
         <path d="{{ path_best_fit(best_fit_points, vb_height) }}" stroke="gray" stroke-dasharray="2,1" fill="none"
             stroke-opacity="60%" />
diff --git a/utils.py b/utils.py
index 7dfef02..8469c0c 100644
--- a/utils.py
+++ b/utils.py
@@ -84,10 +84,14 @@ def build_forecast(values, dates, horizon_weeks=8, metric='E1RM'):
     horizon_days = horizon_weeks * 7
     future_x = np.arange(0, horizon_days + 1, 7, dtype=float) + x[-1]
     future_dates = [last_date + timedelta(days=int(day - x[-1])) for day in future_x]
-    future_values = intercept + slope * future_x
+    # Anchor the projection to the most recent observed value.  A pure
+    # regression line can sit noticeably above or below the latest workout,
+    # which makes the forecast appear to jump when it starts.
+    future_values = observed_values[-1] + slope * (future_x - x[-1])
 
-    # A 95% prediction band, widened for points further from the observations.
-    prediction_error = 1.96 * residual_std * np.sqrt(
+    # A restrained 90% prediction band, widened for points further from the
+    # observations so the uncertainty remains readable on the small chart.
+    prediction_error = 1.645 * residual_std * np.sqrt(
         1 + (1 / len(observed_values)) + ((future_x - mean_x) ** 2 / sum_squared_x)
     )
     lower_values = np.maximum(future_values - prediction_error, 0)
@@ -212,6 +216,7 @@ def get_exercise_graph_model(title, estimated_1rm, repetitions, weight, start_da
     forecast_points = []
     forecast_band_lower = []
     forecast_band_upper = []
+    forecast_labels = []
     forecast_start_position = None
     if forecast.get('available'):
         forecast_start_position = round((observed_max_date - observed_min_date).days / total_span, 3)
@@ -220,6 +225,11 @@ def get_exercise_graph_model(title, estimated_1rm, repetitions, weight, start_da
             forecast_points.append((round(((point['value'] - min_e1rm) / e1rm_range) * vb_height, 1), position))
             forecast_band_lower.append((round(((point['lower'] - min_e1rm) / e1rm_range) * vb_height, 1), position))
             forecast_band_upper.append((round(((point['upper'] - min_e1rm) / e1rm_range) * vb_height, 1), position))
+            forecast_labels.append((
+                position,
+                f"{point['date'].strftime('%d %b %y')} · Projected E1RM: {point['value']}kg "
+                f"(range {point['lower']}–{point['upper']}kg)"
+            ))
 
     # Return exercise data with SVG dimensions and data points
     return {
@@ -243,6 +253,7 @@ def get_exercise_graph_model(title, estimated_1rm, repetitions, weight, start_da
         'forecast_points': forecast_points,
         'forecast_band_lower': forecast_band_lower,
         'forecast_band_upper': forecast_band_upper,
+        'forecast_labels': forecast_labels,
         'forecast_start_position': forecast_start_position
     }