diff --git a/tf/chunkparser.py b/tf/chunkparser.py
index 981aed1e..53d552e7 100644
--- a/tf/chunkparser.py
+++ b/tf/chunkparser.py
@@ -131,6 +131,7 @@ def __init__(self,
                  buffer_size=1,
                  batch_size=256,
                  value_focus_min=1,
+                 value_focus_max=1,
                  value_focus_slope=0,
                  workers=None):
         """
@@ -168,6 +169,7 @@ def __init__(self,
         self.sample = sample
         # set the min and slope for value focus, defaults accept all positions
         self.value_focus_min = value_focus_min
+        self.value_focus_max = value_focus_max
         self.value_focus_slope = value_focus_slope
         # set the mini-batch size
         self.batch_size = batch_size
@@ -443,7 +445,7 @@ def sample_record(self, chunkdata):
                 # if orig_q is NaN, accept, else accept based on value focus
                 if not np.isnan(orig_q):
                     diff_q = abs(best_q - orig_q)
-                    thresh_p = self.value_focus_min + self.value_focus_slope * diff_q
+                    thresh_p = min(self.value_focus_max, self.value_focus_min + self.value_focus_slope * diff_q)
                     if thresh_p < 1.0 and random.random() > thresh_p:
                         continue
 
diff --git a/tf/train.py b/tf/train.py
index a3b7fcdb..8686f0c9 100644
--- a/tf/train.py
+++ b/tf/train.py
@@ -412,6 +412,7 @@ def main(cmd):
     ChunkParser.BATCH_SIZE = split_batch_size
 
     value_focus_min = cfg['training'].get('value_focus_min', 1)
+    value_focus_max = cfg['training'].get('value_focus_max', 1)
     value_focus_slope = cfg['training'].get('value_focus_slope', 0)
 
     root_dir = os.path.join(cfg['training']['path'], cfg['name'])
@@ -422,7 +423,7 @@ def main(cmd):
     extractor = select_extractor(tfprocess.INPUT_MODE)
 
     if experimental_parser and (value_focus_min != 1
-                                or value_focus_slope != 0):
+              or value_focus_max != 1 or value_focus_slope != 0):
         raise ValueError(
             'Experimental parser does not support non-default value \
                           focus parameters.')
@@ -447,6 +448,7 @@ def read(x):
                                    sample=SKIP,
                                    batch_size=ChunkParser.BATCH_SIZE,
                                    value_focus_min=value_focus_min,
+                                   value_focus_max=value_focus_max,
                                    value_focus_slope=value_focus_slope,
                                    workers=train_workers)
         train_dataset = tf.data.Dataset.from_generator(