Florida Gulf Coast University (FGCU) is an NCAA Division I institution competing in the ASUN Conference. During my time with the FGCU Men’s Soccer team, I interned as a Data Analyst, focusing on performance evaluation and tactical evolution. My role involved capturing data to demonstrate data visualizations, analyzing match trends, and providing insights that supported the coaching staff in their decision-making throughout the season.
FGCU vs UNF — ASUN Semifinal Pre-Match Report
This pre-match analytical report was developed ahead of the ASUN Conference semifinals between Florida Gulf Coast University (FGCU) and the University of North Florida (UNF). The analysis focused on identifying UNF’s tactical patterns, key players, and structural tendencies through data visualization and match statistics. Key insights included their left-side attacking bias, vulnerability through central channels in high-xG situations, and second-half performance trends. The report provided the FGCU coaching staff with actionable intelligence to inform match strategy and in-game adjustments.
FGCU vs Lipscomb - Pre-Match Report
These reports were developed during a decisive phase of the 2024 season, when Florida Gulf Coast University (FGCU) faced the University of North Florida (UNF) in the ASUN semifinals and later Lipscomb University. The pre-match analysis against UNF provided tactical insights that helped prepare the team for one of its strongest postseason performances. Leading into the Lipscomb match, the data revealed an interesting paradox — FGCU appeared dominant in possession and ball retention metrics but generated limited offensive threat, ranking among the teams with the fewest progressive or penetrating passes. Identifying this imbalance between control and danger creation became a turning point, helping the staff adjust tactical priorities and sparking a winning streak that changed the team’s trajectory.
FGCU vs Utah Valley — Live Data Match Report
This report was produced in real time during the match against Utah Valley University, using a live data collection system built in Python FC. Data points were manually entered throughout the first and second halves, allowing instant generation of visuals and summaries through pre-coded scripts. The information was shared with the coaching staff both at halftime and immediately after the match to support tactical adjustments.
For the coaching staff at FGCU, special emphasis was placed on pressing zones and entries into Zone 14 — the central attacking area considered key to chance creation. In this match, despite having fewer entries into Zone 14 and fewer total shots, Utah Valley converted their limited opportunities into goals more efficiently. The analysis highlighted the contrast between FGCU’s controlled buildup and the opponent’s clinical execution, providing valuable insights for refining the team’s attacking approach.
