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 %

Half court frequency

All plays besides transition, early offense and putbacks Learn more

#		Eff	Plays	Pts	TO%	Frequency
1	Luisa Geiselsoder PDX	79.6	108	86	14.8%	93.1%
2	Tiffany Hayes GSV	101.4	143	145	10.5%	90.5%
3	Cecilia Zandalasini GSV	84.7	163	138	18.4%	88.6%
4	Paige Bueckers DAL	109.5	359	393	9.5%	87.3%
5	Kaitlyn Chen GSV	107.5	133	143	12.0%	86.9%
6	Shakira Austin WAS	85.7	259	222	18.5%	86.3%
7	Gabby Williams GSV	93.9	311	292	9.6%	86.1%
8	Awa Fam SEA	92.2	179	165	16.8%	86.1%
9	Janelle Salaun GSV	108.2	245	265	6.5%	86.0%
10	Lauren Betts WAS	93.6	110	103	17.3%	85.9%
11	Carla Leite PDX	89.4	282	252	19.9%	85.7%
12	Veronica Burton GSV	94.4	267	252	12.4%	85.6%
13	Olivia Miles MIN	105.5	310	327	16.5%	84.9%
14	A'ja Wilson LVA	105.7	402	425	9.7%	84.6%
15	Olivia Nelson-Ododa CON	105.0	140	147	15.0%	84.3%
16	Angela Dugalic WAS	75.6	86	65	11.6%	84.3%
17	Alanna Smith DAL	70.6	85	60	21.2%	84.2%
18	Frieda Buhner PDX	90.0	90	81	11.1%	84.1%
19	Natisha Hiedeman SEA	97.5	316	308	15.5%	84.0%
20	Naz Hillmon ATL	89.2	157	140	12.1%	84.0%
21	Georgia Amoore WAS	72.0	143	103	24.5%	83.6%
22	Myisha Hines-Allen IND	78.0	91	71	29.7%	83.5%
23	Jade Melbourne SEA	93.8	177	166	18.6%	83.5%
24	Marine Johannes NYL	94.4	179	169	17.3%	83.3%
25	Aliyah Boston IND	103.6	281	291	14.2%	83.1%
26	Noemie Brochant PHX	88.6	105	93	13.3%	82.7%
27	Marina Mabrey TOR	103.7	350	363	13.7%	82.4%
28	Megan Gustafson PDX	128.8	177	228	4.5%	82.3%
29	Lexi Held PHX	80.4	107	86	15.0%	82.3%
30	Chelsea Gray LVA	84.3	249	210	21.7%	82.2%
31	Zia Cooke SEA	74.4	176	131	11.9%	82.2%
32	Breanna Stewart NYL	102.0	344	351	9.6%	82.1%
33	Natasha Cloud CHI	86.7	173	150	19.7%	82.0%
34	Bridget Carleton PDX	99.1	233	231	9.4%	81.8%
35	Caitlin Clark IND	82.7	329	272	19.8%	81.6%
36	Saniya Rivers CON	57.6	170	98	17.1%	81.0%
37	Jackie Young LVA	100.7	296	298	12.8%	80.9%
38	Alyssa Thomas PHX	84.1	283	238	20.5%	80.6%
39	Valeriane Ayayi PHX	96.0	101	97	20.8%	80.2%
40	Kiki Iriafen WAS	95.7	210	201	9.0%	80.2%
41	Aaliyah Edwards CON	94.0	133	125	14.3%	80.1%
42	Jewell Loyd LVA	88.6	140	124	7.1%	80.0%
43	Rae Burrell LAS	98.0	205	201	14.6%	79.8%
44	Pauline Astier NYL	105.6	160	169	14.4%	79.6%
45	Jonquel Jones NYL	114.3	231	264	12.6%	79.4%
46	Maria Conde TOR	80.9	173	140	14.5%	79.4%
47	Rachel Banham CHI	84.8	79	67	17.7%	79.0%
48	Nia Coffey MIN	102.9	139	143	5.8%	79.0%
49	Rhyne Howard ATL	91.1	291	265	7.9%	78.9%
50	Cotie McMahon WAS	80.2	116	93	17.2%	78.9%

Top half court frequency leaders

The current 2026 Season WNBA leaders in play context half court frequency are Luisa Geiselsoder (93.1%, PDX), Tiffany Hayes (90.5%, GSV), Cecilia Zandalasini (88.6%, GSV), Paige Bueckers (87.3%, DAL), and Kaitlyn Chen (86.9%, GSV).

Stat leaders

Play contexts

Half court frequency

NBA

WNBA

Methodology