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 efficiency

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

#		Freq	Plays	Pts	TO%	Efficiency
1	Pauline Astier NYL	60.2%	121	149	13.2%	123.1
2	Sophie Cunningham IND	57.3%	90	110	13.3%	122.2
3	Megan Gustafson PDX	66.0%	142	173	4.9%	121.8
4	Monique Billings IND	51.1%	68	80	8.8%	117.6
5	Kelsey Mitchell IND	66.2%	294	342	8.2%	116.3
6	Olivia Miles MIN	69.3%	253	287	17.8%	113.4
7	Jessica Shepard DAL	50.0%	157	176	13.4%	112.1
8	Paige Bueckers DAL	66.4%	273	304	11.0%	111.4
9	Jonquel Jones NYL	64.3%	187	208	11.8%	111.2
10	Olivia Nelson-Ododa CON	65.7%	109	120	16.5%	110.1
11	Aliyah Boston IND	67.2%	227	249	15.4%	109.7
12	Kamilla Cardoso CHI	63.3%	176	193	14.8%	109.7
13	NaLyssa Smith LVA	56.0%	122	132	9.8%	108.2
14	Kiki Iriafen WAS	57.3%	150	161	9.3%	107.3
15	Tiffany Hayes GSV	62.7%	99	106	14.1%	107.1
16	Sonia Citron WAS	59.1%	175	187	14.9%	106.9
17	Natasha Howard MIN	54.7%	198	211	18.7%	106.6
18	Madina Okot ATL	62.8%	76	81	21.1%	106.6
19	Nneka Ogwumike LAS	62.2%	178	189	6.7%	106.2
20	Lexie Hull IND	58.3%	81	86	13.6%	106.2
21	A'ja Wilson LVA	64.2%	305	322	12.5%	105.6
22	Breanna Stewart NYL	65.4%	274	289	10.9%	105.5
23	Natasha Mack PHX	50.7%	75	79	20.0%	105.3
24	Sarah Ashlee Barker PDX	58.4%	139	146	17.3%	105.0
25	Marina Mabrey TOR	68.0%	289	303	14.9%	104.8
26	Veronica Burton GSV	58.7%	183	190	13.7%	103.8
27	Janelle Salaun GSV	66.0%	188	195	6.9%	103.7
28	Sydney Taylor CHI	63.2%	141	146	12.1%	103.5
29	Awak Kuier DAL	52.5%	63	65	15.9%	103.2
30	Kaitlyn Chen GSV	62.1%	95	98	15.8%	103.2
31	Natisha Hiedeman SEA	65.7%	247	254	16.2%	102.8
32	Jacy Sheldon CHI	56.1%	78	80	12.8%	102.6
33	Bridget Carleton PDX	63.2%	180	181	10.6%	100.6
34	Jackie Young LVA	63.9%	234	235	12.0%	100.4
35	Rae Burrell LAS	65.8%	169	168	15.4%	99.4
36	Kayla McBride MIN	65.4%	221	219	10.4%	99.1
37	Nia Coffey MIN	58.5%	103	102	7.8%	99.0
38	Maddy Siegrist DAL	48.7%	58	57	5.2%	98.3
39	Dearica Hamby LAS	57.4%	162	159	11.7%	98.1
40	Laura Juskaite TOR	58.5%	114	111	15.8%	97.4
41	Carla Leite PDX	61.4%	202	196	20.8%	97.0
42	Gabby Williams GSV	62.3%	225	218	12.0%	96.9
43	Kahleah Copper PHX	66.0%	315	305	11.7%	96.8
44	Marine Johannes NYL	66.0%	142	137	19.0%	96.5
45	Rhyne Howard ATL	53.7%	198	190	8.6%	96.0
46	Luisa Geiselsoder PDX	74.1%	86	81	14.0%	94.2
47	Frieda Buhner PDX	64.5%	69	65	13.0%	94.2
48	Natasha Cloud CHI	63.0%	133	125	20.3%	94.0
49	Jade Melbourne SEA	63.2%	134	126	20.1%	94.0
50	Shakira Austin WAS	63.7%	191	178	20.4%	93.2

Top mid clock efficiency leaders

The current 2026 Season WNBA leaders in play context mid clock efficiency are Pauline Astier (123.1, NYL), Sophie Cunningham (122.2, IND), Megan Gustafson (121.8, PDX), Monique Billings (117.6, IND), and Kelsey Mitchell (116.3, IND).

Stat leaders

Play contexts

Mid clock efficiency

NBA

WNBA

Methodology