The use of statistics to compare lacrosse players is a complex issue, raising questions about opponent strength and positional roles. While statistics offer a quantifiable measure of performance, there are inherent challenges in using them for head-to-head comparisons. Different schedules, varying opponent quality, and the nuances of individual positions all contribute to this complexity.
Accounting for Opponent Strength
Comparing players across teams with vastly different schedules is a significant hurdle. A team’s efficiency or shooting percentage can be adjusted based on opponent strength, but applying this to individual players is less straightforward. What metric should be used: total production or individual efficiency? Additionally, some teams may focus on shutting down a specific player, skewing their individual stats. While a player-specific opponent-adjustment model is theoretically possible, it’s likely to be less precise than team-level models, potentially limiting its usefulness.
The Impact of Positional Roles
Different positions demand different skill sets and contributions. Using raw statistics without considering positional context can lead to misleading comparisons. While roster designations provide a starting point, they don’t always reflect a player’s true role on the field. Deriving roles from statistical profiles is also imperfect, especially for players with limited playing time.
Analyzing shot and assist percentages reveals stark differences between attackers, midfielders, and defenders. Median attackers take 9.4% of their team’s shots and generate 11% of assists, while median midfielders take 5.6% of shots and generate 3.4% of assists. Defenders, primarily focused on defense, average only 0.4% of shots and 0.9 caused turnovers per game. These discrepancies highlight the importance of positional context. Interestingly, if defensive midfielders were excluded, attackers and midfielders might show closer parity in shots. Caused turnovers further underscore the positional divide: defenders average 0.9, midfielders 0.51, and attackers 0.24 per game. This illustrates how statistics can reveal distinct positional contributions.
Offensive Defenders: Bucking the Trend
Examining players who defy positional norms provides further insight. East Carolina’s Payton Barr exemplifies an “offensive defender,” scoring 16 goals on 49 shots (10.1% of team shots) and adding two assists.
Other top offensive defenders include: Brinley Anderson (High Point), Layton Nass (Syracuse), Christine Fiore (Richmond), and Casey Sullivan (Boston College). While most rely on goal scoring, some contribute significantly through assists, demonstrating the diverse ways players can impact the game.
Conclusion: Beyond the Numbers
While statistics are essential for evaluating lacrosse players, they shouldn’t be the sole determinant. Opponent strength and positional roles must be considered to provide a more accurate assessment. Further research into player-specific opponent adjustments and more nuanced positional metrics could enhance the comparative power of statistics. Ultimately, a comprehensive evaluation should combine statistical analysis with qualitative observations, acknowledging the multifaceted nature of player performance.
