  Systemic and idiosyncratic patterns in pitching mechanics of 24 top starting
pitchers in Major League Baseball (MLB) are extracted and discovered from
PITCHf/x database. These evolving patterns across different pitchers or seasons
are represented through three exclusively developed graphic displays.
Understanding on such patterned evolutions will be beneficial for pitchers'
wellbeing in signaling potential injury, and will be critical for expert
knowledge in comparing pitchers. Based on data-driven computing, a universal
composition of patterns is identified on all pitchers' mutual conditional
entropy matrices. The first graphic display reveals that this universality
accommodates physical laws as well as systemic characteristics of pitching
mechanics. Such visible characters point to large scale factors for
differentiating between distinct clusters of pitchers, and simultaneously lead
to detailed factors for comparing individual pitchers. The second graphic
display shows choices of features that are able to express a pitcher's
season-by-season pitching contents via a series of 3(+2)D point-cloud
geometries. The third graphic display exhibits exquisitely a pitcher's
idiosyncratic pattern-information of pitching across seasons by demonstrating
all his pitch-subtype evolutions. These heatmap-based graphic displays are
platforms for visualizing and understanding pitching mechanics.
