Stat leaders

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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 turnover %

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

#		Freq	Eff	Plays	Pts	Turnover %
1	Myisha Hines-Allen IND	62.4%	88.2	68	60	33.8%
2	Georgia Amoore WAS	60.8%	68.3	104	71	29.8%
3	Cecilia Zandalasini GSV	54.3%	80.0	100	80	26.0%
4	Chelsea Gray LVA	59.1%	83.8	179	150	25.1%
5	Valeriane Ayayi PHX	62.7%	89.9	79	71	22.8%
6	Alyssa Thomas PHX	60.4%	86.8	212	184	22.6%
7	Erica Wheeler LAS	56.7%	75.6	119	90	21.8%
8	Alanna Smith DAL	64.4%	83.1	65	54	21.5%
9	Angel Reese ATL	54.5%	72.8	224	163	21.4%
10	Madina Okot ATL	62.8%	106.6	76	81	21.1%
11	Carla Leite PDX	61.4%	97.0	202	196	20.8%
12	Cotie McMahon WAS	59.2%	87.4	87	76	20.7%
13	Shakira Austin WAS	63.7%	93.2	191	178	20.4%
14	Natasha Cloud CHI	63.0%	94.0	133	125	20.3%
15	Jade Melbourne SEA	63.2%	94.0	134	126	20.1%
16	Jordin Canada ATL	57.0%	83.9	155	130	20.0%
17	Natasha Mack PHX	50.7%	105.3	75	79	20.0%
18	Emily Engstler PDX	54.5%	83.6	122	102	19.7%
19	Marine Johannes NYL	66.0%	96.5	142	137	19.0%
20	Lauren Betts WAS	53.9%	88.4	69	61	18.8%
21	Natasha Howard MIN	54.7%	106.6	198	211	18.7%
22	Awa Fam SEA	68.8%	89.5	143	128	18.2%
23	Saniya Rivers CON	63.3%	56.4	133	75	18.0%
24	Olivia Miles MIN	69.3%	113.4	253	287	17.8%
25	Caitlin Clark IND	70.0%	91.5	282	258	17.7%
26	Sarah Ashlee Barker PDX	58.4%	105.0	139	146	17.3%
27	Maria Conde TOR	56.4%	84.6	123	104	17.1%
28	Raven Johnson IND	59.7%	66.2	71	47	16.9%
29	Rachel Banham CHI	66.0%	83.3	66	55	16.7%
30	Olivia Nelson-Ododa CON	65.7%	110.1	109	120	16.5%
31	Lexi Held PHX	61.5%	76.3	80	61	16.3%
32	Natisha Hiedeman SEA	65.7%	102.8	247	254	16.2%
33	Naz Hillmon ATL	62.6%	82.9	117	97	16.2%
34	Awak Kuier DAL	52.5%	103.2	63	65	15.9%
35	Kaitlyn Chen GSV	62.1%	103.2	95	98	15.8%
36	Laura Juskaite TOR	58.5%	97.4	114	111	15.8%
37	Charlisse Leger-Walker CON	56.7%	85.2	115	98	15.7%
38	Nell Angloma CON	62.4%	81.0	58	47	15.5%
39	Rae Burrell LAS	65.8%	99.4	169	168	15.4%
40	Aliyah Boston IND	67.2%	109.7	227	249	15.4%
41	Ariel Atkins LAS	63.3%	79.0	124	98	15.3%
42	Aneesah Morrow CON	56.5%	73.0	126	92	15.1%
43	Flau'jae Johnson SEA	61.2%	78.0	227	177	15.0%
44	Marina Mabrey TOR	68.0%	104.8	289	303	14.9%
45	Kennedy Burke CON	63.5%	91.8	134	123	14.9%
46	Sonia Citron WAS	59.1%	106.9	175	187	14.9%
47	Kamilla Cardoso CHI	63.3%	109.7	176	193	14.8%
48	Zia Cooke SEA	64.5%	73.9	138	102	14.5%
49	Aaliyah Edwards CON	67.5%	87.5	112	98	14.3%
50	Gabriela Jaquez CHI	57.2%	89.0	91	81	14.3%

Top mid clock turnover % leaders

The current 2026 Season WNBA leaders in play context mid clock turnover % are Myisha Hines-Allen (33.8%, IND), Georgia Amoore (29.8%, WAS), Cecilia Zandalasini (26.0%, GSV), Chelsea Gray (25.1%, LVA), and Valeriane Ayayi (22.8%, PHX).

Stat leaders

Play contexts

Mid clock turnover %

NBA

WNBA

Methodology