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 %

Mid clock frequency

A half court play with 4 seconds or more on the shot clock Learn more

#		Eff	Plays	Pts	TO%	Frequency
1	Luisa Geiselsoder PDX	94.2	86	81	14.0%	74.1%
2	Caitlin Clark IND	91.5	282	258	17.7%	70.0%
3	Olivia Miles MIN	113.4	253	287	17.8%	69.3%
4	Awa Fam SEA	89.5	143	128	18.2%	68.8%
5	Marina Mabrey TOR	104.8	289	303	14.9%	68.0%
6	Aaliyah Edwards CON	87.5	112	98	14.3%	67.5%
7	Aliyah Boston IND	109.7	227	249	15.4%	67.2%
8	Paige Bueckers DAL	111.4	273	304	11.0%	66.4%
9	Kelsey Mitchell IND	116.3	294	342	8.2%	66.2%
10	Rachel Banham CHI	83.3	66	55	16.7%	66.0%
11	Kahleah Copper PHX	96.8	315	305	11.7%	66.0%
12	Megan Gustafson PDX	121.8	142	173	4.9%	66.0%
13	Marine Johannes NYL	96.5	142	137	19.0%	66.0%
14	Janelle Salaun GSV	103.7	188	195	6.9%	66.0%
15	Rae Burrell LAS	99.4	169	168	15.4%	65.8%
16	Natisha Hiedeman SEA	102.8	247	254	16.2%	65.7%
17	Olivia Nelson-Ododa CON	110.1	109	120	16.5%	65.7%
18	Aziaha James DAL	93.2	103	96	7.8%	65.6%
19	Kayla McBride MIN	99.1	221	219	10.4%	65.4%
20	Breanna Stewart NYL	105.5	274	289	10.9%	65.4%
21	Skylar Diggins CHI	91.1	191	174	12.0%	65.2%
22	Jewell Loyd LVA	85.0	113	96	8.8%	64.6%
23	Azzi Fudd DAL	92.9	184	171	8.2%	64.6%
24	Noemie Brochant PHX	90.2	82	74	13.4%	64.6%
25	Zia Cooke SEA	73.9	138	102	14.5%	64.5%
26	Frieda Buhner PDX	94.2	69	65	13.0%	64.5%
27	Alanna Smith DAL	83.1	65	54	21.5%	64.4%
28	Jonquel Jones NYL	111.2	187	208	11.8%	64.3%
29	A'ja Wilson LVA	105.6	305	322	12.5%	64.2%
30	Jackie Young LVA	100.4	234	235	12.0%	63.9%
31	Shakira Austin WAS	93.2	191	178	20.4%	63.7%
32	Kennedy Burke CON	91.8	134	123	14.9%	63.5%
33	Ariel Atkins LAS	79.0	124	98	15.3%	63.3%
34	Kamilla Cardoso CHI	109.7	176	193	14.8%	63.3%
35	Saniya Rivers CON	56.4	133	75	18.0%	63.3%
36	Bridget Carleton PDX	100.6	180	181	10.6%	63.2%
37	Jade Melbourne SEA	94.0	134	126	20.1%	63.2%
38	Sydney Taylor CHI	103.5	141	146	12.1%	63.2%
39	Natasha Cloud CHI	94.0	133	125	20.3%	63.0%
40	Madina Okot ATL	106.6	76	81	21.1%	62.8%
41	Tiffany Hayes GSV	107.1	99	106	14.1%	62.7%
42	Valeriane Ayayi PHX	89.9	79	71	22.8%	62.7%
43	Angela Dugalic WAS	84.4	64	54	12.5%	62.7%
44	Naz Hillmon ATL	82.9	117	97	16.2%	62.6%
45	Myisha Hines-Allen IND	88.2	68	60	33.8%	62.4%
46	Nell Angloma CON	81.0	58	47	15.5%	62.4%
47	Gabby Williams GSV	96.9	225	218	12.0%	62.3%
48	Nneka Ogwumike LAS	106.2	178	189	6.7%	62.2%
49	Kaitlyn Chen GSV	103.2	95	98	15.8%	62.1%
50	Elizabeth Williams CHI	80.2	86	69	5.8%	61.9%

Top mid clock frequency leaders

The current 2026 Season WNBA leaders in play context mid clock frequency are Luisa Geiselsoder (74.1%, PDX), Caitlin Clark (70.0%, IND), Olivia Miles (69.3%, MIN), Awa Fam (68.8%, SEA), and Marina Mabrey (68.0%, TOR).

Stat leaders

Play contexts

Mid clock frequency

NBA

WNBA

Methodology