In the high-stakes world of professional basketball, the quest for championship glory hinges not just on talent and strategy but on statistical prowess. As the 2024 WNBA season reaches the Olympic break, all eyes have been on the Minnesota Lynx, scrutinizing every dribble, pass, and shot in anticipation of their potential to clinch the ultimate prize.
The Lynx have been the darlings of the 2024 season, outpacing many of the pundits’ expectations heading into the season. Minnesota is 17-8 and tied for the third seed in the league. The Lynx heartbeat is their all-everything forward Napheesa Collier. Of late, the Lynx have fallen on a bit of hard times, coinciding with losing Collier to a left foot plantar fasciitis injury that has not been easy to overcome. Since she left the game on July 4, the Lynx have gone 3-3, including that fateful game. As Phee goes, so go the Lynx, and without her, it’s an equal opportunity offense begging for someone to step up. All season, the team has leaned on its defensive pressure to motivate its offense. If the Lynx want to make hay, they’ll need their All-WNBA leader.
Diving beneath the surface, this article embarks on a meticulous analysis, delving into the numbers that truly define contenders. By comparing the performance metrics of the Lynx against the averages of the past decade’s champions, I aim to unravel whether this season holds the promise of championship success or the bitter realization of unmet expectations.
To do so, I gathered data from 19 statistical categories, ranging from the traditional (points per game (PPG) and assists per game (APG), to the more analytically driven like offensive and defensive rating (ORTG and DRTG) and true shooting percentage (TS%). This also included offensive numbers like field goal percentage (FG%) and rebounding percentage (REB%) but also defensive ones like opponents’ second-chance points and points off turnovers. I believe this gave me a detailed and comprehensive look not only at what a team does overall but whether there were certain statistics that champions excelled at over others. By averaging the data for each statistic, I leveraged that number as the baseline and compared the teams accordingly.
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