Stat leaders

Traditional Advanced Scoring Play contexts On/Off Clutch High Leverage Lineups

Play contexts

Transition frequency Transition efficiency Transition turnover %Early offense frequency Early offense efficiency Early offense turnover %Putbacks frequency Putbacks efficiency Putbacks turnover %Half court frequency Half court efficiency Half court turnover %Mid clock frequency Mid clock efficiency Mid clock turnover %Late clock frequency Late clock efficiency Late clock turnover %

Early offense frequency

First 8 seconds of a dead-ball possession Learn more

#		Eff	Plays	Pts	TO%	Frequency
1	Lexie Hull IND	83.3	12	10	8.3%	8.6%
2	Jordin Canada ATL	104.3	23	24	8.7%	8.5%
3	Charlisse Leger-Walker CON	64.7	17	11	35.3%	8.4%
4	Pauline Astier NYL	150.0	16	24	25.0%	8.0%
5	Kelsey Mitchell IND	123.5	34	42	14.7%	7.7%
6	Sonia Citron WAS	145.5	22	32	9.1%	7.4%
7	Natasha Cloud CHI	73.3	15	11	33.3%	7.1%
8	Erica Wheeler LAS	93.3	15	14	20.0%	7.1%
9	Caitlin Clark IND	129.6	27	35	18.5%	6.7%
10	Sydney Taylor CHI	73.3	15	11	20.0%	6.7%
11	Jade Melbourne SEA	78.6	14	11	14.3%	6.6%
12	Skylar Diggins CHI	110.5	19	21	15.8%	6.5%
13	Saniya Rivers CON	76.9	13	10	23.1%	6.2%
14	Ariel Atkins LAS	0.0	11	0	36.4%	5.6%
15	Kahleah Copper PHX	92.3	26	24	19.2%	5.5%
16	Kaitlyn Chen GSV	25.0	8	2	50.0%	5.2%
17	Jewell Loyd LVA	66.7	9	6	33.3%	5.1%
18	Natisha Hiedeman SEA	84.2	19	16	21.1%	5.1%
19	Aziaha James DAL	75.0	8	6	12.5%	5.1%
20	Rachel Banham CHI	60.0	5	3	20.0%	5.0%
21	Raven Johnson IND	33.3	6	2	33.3%	5.0%
22	Rhyne Howard ATL	172.2	18	31	11.1%	4.9%
23	Marina Mabrey TOR	100.0	20	20	25.0%	4.7%
24	Nia Coffey MIN	62.5	8	5	62.5%	4.5%
25	Tiffany Hayes GSV	85.7	7	6	42.9%	4.4%
26	Allisha Gray ATL	133.3	18	24	5.6%	4.4%
27	Carla Leite PDX	100.0	14	14	35.7%	4.3%
28	Nell Angloma CON	25.0	4	1	25.0%	4.3%
29	Bridget Carleton PDX	116.7	12	14	16.7%	4.2%
30	Aaliyah Edwards CON	57.1	7	4	57.1%	4.2%
31	Chelsea Gray LVA	116.7	12	14	16.7%	4.0%
32	Rae Burrell LAS	80.0	10	8	40.0%	3.9%
33	Sophie Cunningham IND	83.3	6	5	0.0%	3.8%
34	Kennedy Burke CON	50.0	8	4	50.0%	3.8%
35	Veronica Burton GSV	33.3	12	4	8.3%	3.8%
36	Diamond Miller CON	100.0	9	9	11.1%	3.8%
37	Olivia Miles MIN	100.0	14	14	14.3%	3.8%
38	Kayla McBride MIN	116.7	12	14	0.0%	3.6%
39	Jackie Young LVA	84.6	13	11	23.1%	3.6%
40	Aliyah Boston IND	83.3	12	10	25.0%	3.6%
41	Gabby Williams GSV	133.3	12	16	16.7%	3.3%
42	Courtney Williams MIN	58.3	12	7	8.3%	3.2%
43	Maria Conde TOR	28.6	7	2	28.6%	3.2%
44	Azzi Fudd DAL	88.9	9	8	0.0%	3.2%
45	Emily Engstler PDX	14.3	7	1	71.4%	3.1%
46	Jordan Horston SEA	75.0	4	3	25.0%	3.1%
47	Gabriela Jaquez CHI	0.0	5	0	60.0%	3.1%
48	Monique Billings IND	125.0	4	5	25.0%	3.0%
49	Elizabeth Williams CHI	25.0	4	1	50.0%	2.9%
50	Angel Reese ATL	41.7	12	5	33.3%	2.9%

Top early offense frequency leaders

The current 2026 Season WNBA leaders in play context early offense frequency are Lexie Hull (8.6%, IND), Jordin Canada (8.5%, ATL), Charlisse Leger-Walker (8.4%, CON), Pauline Astier (8.0%, NYL), and Kelsey Mitchell (7.7%, IND).

Stat leaders

Play contexts

Early offense frequency

NBA

WNBA

Methodology