Methods and systems of spatiotemporal pattern recognition for video content development

A system comprising:

• at least one computer comprising at least one processor and at least one memory, the at least one processor configured to:
• process at least one video feed of a first player through at least one spatiotemporal pattern recognition algorithm that is trained through a use of a machine learning system to detect at least one first player event within the at least one video feed, the training based on adjusting an input feature and a weight within the machine learning system, wherein the input is selected from the group consisting of:
• relative direction of motion of at least two visible features,
• duration of relative motion of visible features with respect to each other,
• rate of motion of at least two visible features with respect to each other,
• acceleration of motion of at least two visible features with respect to each other, and
• projected point of intersection of at least two visible features with respect to each other;
• apply a second video feed of a second player to the machine learning system to detect a second player event;
• generate an animation of the second player, the animation having attributes based on motion of the second player from the second player event;
• and
• automatically provide an enhanced video feed that represents the animation of the second player within the at least one first player event, the animation being represented within a context of the at least one first player event and the attributes of motion of the second player, the context being based on characteristics of at least one spatiotemporal pattern used to detect the at least one first player event.