Ever since last year, the WNBA website has provided additional statistical information besides the traditional categories. Courtney Williams and Seimone Augustus, the mid-range experts of their generations, scored more than half of their points from mid-range. Sugar Rodgers scored 80% of her points from beyond the arc with Shekinna Stricklen and Julie Allemand each exceeding 70%. Diamond DeShields and Shatori Walker-Kimbrough each scored more than 20% of their points from the fast break. 6 players score more than 30% of their points from the free throw line led by Tierra Ruffin-Pratt. Paris Kea was remarkably only assisted on 6.7% of her made two-pointers while Brianna Turner and Mercedes Russell were helped on more than 87% of their makes. Kea also took matters into her own hands beyond the arc, only being assisted on 30.8% of her makes there while a third of Chennedy Carter’s long-range makes came without an assist.
Usage:
15 players terminated at least a quarter of their team’s possessions when they were on the court. It is no surprise that Chennedy Carter and Arike Ogunbowale top the list given their roles. Phoenix’s absences mean that their usage mix will continue to change for the postseason. There are usually a few unexpected names on this list because the metric does a good job of capturing players who look for the their shot off the bench or in limited minutes. Paris Kea does stand out as a player who signed with her team late, but made sure that she showed what she could do once she arrived.
Effective Field Goal Percentage:
Using effective field goal percentage allows for better comparison of field goal percentage by taking into account the extra point from a made three-pointer so that post players are not the only ones at the top of the ranking. 9 players exceeded 60% using this measure and it was a good mix as Ruthy Hebard was expected to do most of her damage close to the basket, while Alysha Clark uses shots from all over the court, and Julie Allemand shoots about 70% of her shots from beyond the arc.
Rebounding Percentage:
Separating rebounding by end of the court is always useful because different teams place different levels of emphasis on offensive rebounding. 15 players grabbed at least 8% of their own team’s misses when they were on the court and 15 players grabbed at least 20% of the other team’s misses when they were on the court. Connecticut is one of the top offensive rebounding teams and Beatrice Mompremier was the individual leader while also doing a good job at the other end. Teaira McCowan, Natasha Howard, Monique Billings, Brianna Turner are on both lists with the last two being the exact same rank on each. Amanda Zahui B is the clear leader on the defensive end, but only grabs 2.8% of New York’s misses so the separation of the statistics better measures her impact. Candace Parker also does not crash the glass as much on the offensive end as Los Angeles had the lowest offensive rebounding percentage in the league.
On/Off Rating:
121 players played more than 10 minutes for their team including Essence Carson and Shey Peddy for two teams. Napheesa Collier played 85.5% of Minnesota’s minutes with Arike Ogunbowale following at 84.0% and Betnijah Laney, DeWanna Bonner, Julie Allemand, and Kelsey Mitchell also playing over 80.0% of available minutes. Let’s look at how the teams played with those players on the court compared to when they were on the bench.
Offense:
16 players had their teams average at least 107 points per 100 possessions when they were on the court. Seattle’s offense was great, but it was particularly efficient when Sue Bird was available. In a playoff scenario, Las Vegas will be hoping that limiting Angel McCoughtry’s minutes to half of the available minutes will leave her fresh for the big moments. Chicago was certainly happy to have Stefanie Dolson available again and Minnesota also benefits from having Odyssey Sims. Erica McCall’s inclusion may be surprising, but she joined the Lynx at the right time as their offense hummed about equally with or without her on the court since her signing. That is the weakness of only using this figure as players who play on great offensive teams get a boost regardless of their individual impact.
Measuring the difference in offensive rating between when a player is on or off the court instead, provides a different picture of how players impact their teams. When Chicago has Courtney Vandersloot on the court, they play like the best offense in the league, but when she is on the bench, they are more than 5 points worse per 100 possessions than the worst offense in the league or a 29 points per 100 possessions difference. 16 players have their teams play 10 points per 100 possessions better on offense when they are on the court, including Napheesa Collier at 25.4 points and Myisha Hines-Allen at 23.5 points. Using this metric is important for players on the worse offensive teams as 7 players on this list were on bottom half offenses and improving on offense includes figuring out the right combinations going forward.
Defense:
17 players had their teams give up fewer than 94 points per 100 possessions when they were on the court. Half of them play for Seattle, which had the best defense overall, but there are other interesting results. Connecticut played better defense since Briann January was available and Kiki Herbert-Harrigan also stands out as a player whose team performed well defensively in her limited minutes. Remarkably, Shey Peddy made the list for her minutes on both of her teams.
17 players had their team give up at least 7 fewer points per 100 possessions when they were on the court than when they were on the bench as Shey Peddy again makes the list twice. Given how dreadful Indiana was on defense, they may want to examine why they performed so much better as Lauren Cox got minutes later in the season as Kathleen Doyle was the next person on the list and Tiffany Mitchell’s absence for part of the season did not help.
Net:
Simply using the raw net rating for on court time obviously is biased towards the players on the top teams as Seattle and Las Vegas account for 15 of the 19 players whose teams outscored by their opponents by at least 10 points per 100 possessions when they were on the court. The 4 players who are not are of particular interest given that all of them have missed portions of the season due to injury.
Using the difference in net rating between on and off court time is more instructive as 20 players had their teams perform more than 10 points per 100 possessions better when they were on the court when they were on the bench. Courtney Vandersloot tops the list with her impact on the offensive end as her team is outscored by almost 19 points per 100 possessions when she is on the bench. Behind her, Seattle is actually outscored when Alysha Clark is not on the court. Using this metric can provide helpful information for struggling teams as Indiana outscored their opposition when Lauren Cox was on the court and New York was particularly outgunned when Leaonna Odom and Amanda Zahui B, who just missed this list, were not on the court.
Lineups:
24 different full lineups played at least 66 minutes. Unfortunately, the one with the highest net rating is no longer viable due to injuries for Washington. Las Vegas’s bench heavy lineup of Danielle Robinson, Sugar Rodgers, Jackie Young, Dearica Hamby, and A’ja Wilson is the surprise next most effective due to their success on defense. Connecticut relied on their starters heavily last year and if they can get their preferred lineup on the court for the playoffs could be dangerous as they were strong as well. Phoenix is missing players, but they can still field a strong lineup of Skylar Diggins-Smith, Diana Taurasi, Shatori Walker-Kimbrough, Brianna Turner, and Kia Vaughn, which has had the best offensive output of currently possible lineups. Seattle will also looking to get their preferred starters back to playing as many minutes as possible as they were the second most played unit behind Washington’s current lineup, although their lineup with Jordin Canada replacing Sue Bird was the third most common combination.