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	JJ Quinerly DAL	95.7	23	22	13.0%	9.2%
2	Julie Allemand LAS	81.3	16	13	25.0%	7.3%
3	Natasha Cloud NYL	78.8	33	26	27.3%	7.2%
4	Jade Melbourne WAS	57.1	21	12	33.3%	6.4%
5	Myisha Hines-Allen DAL	52.2	23	12	17.4%	6.2%
6	Kelsey Plum LAS	89.8	49	44	16.3%	5.7%
7	Jackie Young LVA	102.5	40	41	17.5%	5.7%
8	Rachel Banham CHI	62.5	24	15	16.7%	5.6%
9	Bria Hartley CON	76.2	21	16	19.0%	5.3%
10	Erica Wheeler SEA	69.2	26	18	23.1%	5.2%
11	Brittney Sykes SEA	102.9	34	35	23.5%	5.2%
12	Stephanie Talbot NYL	75.0	8	6	50.0%	5.1%
13	Kelsey Mitchell IND	97.7	43	42	4.7%	5.1%
14	Aaliyah Nye LVA	50.0	10	5	10.0%	5.1%
15	Rhyne Howard ATL	60.7	28	17	14.3%	4.7%
16	Marine Johannes NYL	21.4	14	3	7.1%	4.5%
17	Paige Bueckers DAL	106.7	30	32	0.0%	4.5%
18	Courtney Williams MIN	43.3	30	13	33.3%	4.3%
19	Veronica Burton GSV	108.3	24	26	12.5%	4.3%
20	Lexi Held PHX	50.0	8	4	12.5%	4.3%
21	Saniya Rivers CON	77.8	18	14	16.7%	4.3%
22	Sami Whitcomb PHX	88.9	18	16	11.1%	4.2%
23	Satou Sabally PHX	60.7	28	17	21.4%	4.2%
24	Damiris Dantas IND	0.0	8	0	37.5%	4.0%
25	Sabrina Ionescu NYL	76.7	30	23	13.3%	4.0%
26	Skylar Diggins SEA	89.3	28	25	17.9%	3.9%
27	Breanna Stewart NYL	90.9	22	20	18.2%	3.9%
28	Dana Evans LVA	116.7	12	14	8.3%	3.9%
29	Chelsea Gray LVA	47.6	21	10	52.4%	3.8%
30	DiJonai Carrington MIN	71.4	14	10	14.3%	3.8%
31	Carla Leite GSV	66.7	12	8	25.0%	3.8%
32	Aziaha James DAL	83.3	12	10	8.3%	3.7%
33	Alyssa Thomas PHX	43.5	23	10	26.1%	3.5%
34	Dominique Malonga SEA	90.9	11	10	18.2%	3.5%
35	Kennedy Burke NYL	100.0	9	9	11.1%	3.4%
36	Jewell Loyd LVA	35.3	17	6	35.3%	3.3%
37	Ariel Atkins CHI	50.0	16	8	37.5%	3.3%
38	Natisha Hiedeman MIN	58.3	12	7	16.7%	3.3%
39	Emily Engstler WAS	50.0	6	3	50.0%	3.3%
40	Monique Akoa Makani PHX	154.5	11	17	18.2%	3.3%
41	Sonia Citron WAS	100.0	21	21	4.8%	3.3%
42	Azura Stevens LAS	105.9	17	18	29.4%	3.2%
43	Natasha Howard IND	75.0	16	12	25.0%	3.1%
44	Dearica Hamby LAS	116.7	24	28	12.5%	3.1%
45	Allisha Gray ATL	45.5	22	10	22.7%	3.1%
46	Kayla McBride MIN	118.8	16	19	12.5%	3.0%
47	Aneesah Morrow CON	72.7	11	8	45.5%	3.0%
48	Kathryn Westbeld PHX	71.4	7	5	0.0%	2.9%
49	Kitija Laksa PHX	33.3	6	2	33.3%	2.9%
50	Li Yueru DAL	0.0	6	0	50.0%	2.9%

Top early offense frequency leaders

The current 2025 Season WNBA leaders in play context early offense frequency are JJ Quinerly (9.2%, DAL), Julie Allemand (7.3%, LAS), Natasha Cloud (7.2%, NYL), Jade Melbourne (6.4%, WAS), and Myisha Hines-Allen (6.2%, DAL).

Stat leaders

Play contexts

Early offense frequency

NBA

WNBA

Methodology