  The NFL collects detailed tracking data capturing the location of all players
and the ball during each play. Although the raw form of this data is not
publicly available, the NFL releases a set of aggregated statistics via their
Next Gen Stats (NGS) platform. They also provide charts showing the locations
of pass attempts and outcomes for individual quarterbacks. Our work aims to
partially close the gap between what data is available privately (to NFL teams)
and publicly, and our contribution is twofold. First, we introduce an image
processing tool designed specifically for extracting the raw data from the NGS
pass charts. We extract the pass outcome, coordinates, and other metadata.
Second, we analyze the resulting dataset, examining the spatial tendencies and
performances of individual quarterbacks and defenses. We use a generalized
additive model for completion percentages by field location. We introduce a
Naive Bayes approach for estimating the 2-D completion percentage surfaces of
individual teams and quarterbacks, and we provide a one-number summary,
completion percentage above expectation (CPAE), for evaluating quarterbacks and
team defenses. We find that our pass location data closely matches the NFL's
tracking data, and that our CPAE metric closely matches the NFL's proprietary
CPAE metric.
