How WNBA turnovers actually behave

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Across 210 WNBA players with at least 10 logged games in turnovers, this page measures 7674 games in total. The median player in that field averages 1.1 turnovers. The line closest to a coin flip sits at 0.5 for the median of the 210 players whose distribution supports one — half the field is more often over it, half more often under. The deepest sample here is Alyssa Thomas, with 63 logged games. Of the 119 players whose spread can be measured, 1 cluster tightly around their average, 40 vary moderately and 78 swing widely. 210 of them have at least three games home and away, so the venue gap below is measured rather than assumed. Every figure is counted from official box scores and describes games already played. It is not a projection, and on its own it says nothing about whether any price on offer is worth taking.

Measured as of 2026-09-20, rebuilt daily from official box scores. Window: 2025-08-16 to 2026-09-19. No prices appear on this page.

Where the coin-flip line sits in WNBA turnovers

Each player's own most balanced threshold — the half-point line he has finished above in closest to half his logged games — measured from his distribution rather than read off a book. Deepest sample first, not best to worst. The 40 deepest samples of 210 measured; the figures above this table are over all 210.

WNBA turnovers — measured field
Player	Club	Logged games	Average	Balanced line	Hit rate there
Alyssa Thomas	Mercury	63	3.7 turnovers	Over 3.5	33 of 63 (52%)
Chelsea Gray	Aces	62	2.5 turnovers	Over 2.5	29 of 62 (47%)
DeWanna Bonner	Dream	62	0.7 turnovers	Over 0.5	37 of 62 (60%)
Jackie Young	Aces	62	2.4 turnovers	Over 2.5	25 of 62 (40%)
Jewell Loyd	Aces	61	0.9 turnovers	Over 0.5	41 of 61 (67%)
Kahleah Copper	Mercury	61	2.2 turnovers	Over 2.5	24 of 61 (39%)
A'ja Wilson	Aces	60	2.3 turnovers	Over 2.5	28 of 60 (47%)
Kelsey Mitchell	Fever	59	1.9 turnovers	Over 1.5	38 of 59 (64%)
Kiah Stokes	Valkyries	59	0.4 turnovers	Over 0.5	16 of 59 (27%)
Lexie Hull	Fever	59	0.9 turnovers	Over 0.5	37 of 59 (63%)
NaLyssa Smith	Aces	59	0.9 turnovers	Over 0.5	37 of 59 (63%)
Natasha Howard	Lynx	59	2.4 turnovers	Over 2.5	25 of 59 (42%)
Courtney Williams	Lynx	58	2.0 turnovers	Over 1.5	38 of 58 (66%)
Jessica Shepard	Wings	58	1.8 turnovers	Over 1.5	32 of 58 (55%)
Kayla McBride	Lynx	58	1.4 turnovers	Over 1.5	24 of 58 (41%)
Bridget Carleton	Fire	57	1.0 turnovers	Over 0.5	35 of 57 (61%)
Natasha Mack	Mercury	57	0.7 turnovers	Over 0.5	31 of 57 (54%)
Brianna Turner	Aces	56	0.6 turnovers	Over 0.5	27 of 56 (48%)
Natisha Hiedeman	Storm	56	2.0 turnovers	Over 1.5	35 of 56 (63%)
Aliyah Boston	Fever	55	2.2 turnovers	Over 2.5	25 of 55 (45%)
Kaila Charles	Valkyries	55	1.1 turnovers	Over 0.5	36 of 55 (65%)
Makayla Timpson	Fever	55	0.6 turnovers	Over 0.5	22 of 55 (40%)
Maya Caldwell	Lynx	55	0.8 turnovers	Over 0.5	31 of 55 (56%)
Naz Hillmon	Dream	55	1.3 turnovers	Over 1.5	24 of 55 (44%)
Rhyne Howard	Dream	55	1.4 turnovers	Over 1.5	21 of 55 (38%)
Veronica Burton	Valkyries	55	1.8 turnovers	Over 1.5	27 of 55 (49%)
Allisha Gray	Dream	54	1.4 turnovers	Over 1.5	23 of 54 (43%)
Nia Coffey	Lynx	54	0.6 turnovers	Over 0.5	25 of 54 (46%)
Emily Engstler	Fire	53	1.6 turnovers	Over 1.5	25 of 53 (47%)
Erica Wheeler	Sparks	53	1.7 turnovers	Over 1.5	28 of 53 (53%)
Jonquel Jones	Liberty	53	2.1 turnovers	Over 2.5	19 of 53 (36%)
Nneka Ogwumike	Sparks	53	1.9 turnovers	Over 1.5	31 of 53 (58%)
Dearica Hamby	Sparks	52	2.0 turnovers	Over 2.5	18 of 52 (35%)
Elizabeth Williams	Sky	52	0.9 turnovers	Over 0.5	28 of 52 (54%)
Kamilla Cardoso	Sky	52	2.0 turnovers	Over 1.5	27 of 52 (52%)
Lexi Held	Mercury	52	0.9 turnovers	Over 0.5	31 of 52 (60%)
Natasha Cloud	Sky	52	2.2 turnovers	Over 2.5	20 of 52 (38%)
Stefanie Dolson	Storm	52	0.7 turnovers	Over 0.5	26 of 52 (50%)
Stephanie Talbot	Aces	52	0.7 turnovers	Over 0.5	27 of 52 (52%)
Jade Melbourne	Storm	51	1.8 turnovers	Over 1.5	31 of 51 (61%)

The steadiest WNBA turnovers records

Standard deviation in the market’s own units, and the same figure as a share of the player’s average so it means the same thing in points as in passing yards. A narrow spread means the average is close to what a typical game actually looked like; it says nothing about what the next one will look like.

The steadiest WNBA turnovers records
Player	Club	Logged games	Average	Standard deviation	Spread as % of average
Caitlin Clark	Fever	37	4.6 turnovers	1.6	34%
Teja Oblak	Fire	29	2.5 turnovers	1.1	43%
Marina Mabrey	Tempo	44	2.9 turnovers	1.3	43%
Alyssa Thomas	Mercury	63	3.7 turnovers	1.7	45%
Angel Reese	Dream	48	3.3 turnovers	1.5	45%
Olivia Miles	Lynx	39	3.1 turnovers	1.6	52%
A'ja Wilson	Aces	60	2.3 turnovers	1.2	54%
Sevgi Uzun	Sky	11	1.5 turnovers	0.8	54%
Kelsey Mitchell	Fever	59	1.9 turnovers	1.1	55%
Kelsey Plum	Mercury	28	2.8 turnovers	1.5	55%

The widest WNBA turnovers swings

The other end of the same measurement. A wide spread means the average describes the middle of a broad range rather than a typical night, which is worth knowing before reading anything into that average.

The widest WNBA turnovers swings
Player	Club	Logged games	Average	Standard deviation	Spread as % of average
Dana Evans	Aces	34	1.0 turnovers	1.3	126%
Holly Winterburn	Fire	29	1.1 turnovers	1.2	115%
Olivia Nelson-Ododa	Sun	39	1.4 turnovers	1.6	115%
Alicia Florez	Mystics	29	1.2 turnovers	1.4	111%
Iliana Rupert	Valkyries	12	1.1 turnovers	1.2	110%
Rachel Banham	Sky	49	1.0 turnovers	1.1	109%
Gabriela Jaquez	Sky	37	1.2 turnovers	1.3	109%
Ezi Magbegor	Storm	27	1.1 turnovers	1.2	107%
Odyssey Sims	Wings	51	1.3 turnovers	1.4	106%
Azzi Fudd	Wings	30	1.1 turnovers	1.2	106%

The widest home and away gaps in WNBA turnovers

Both averages are over the games actually played at each venue, and the game count for each is in the cell beside it. A gap measured over a handful of games either way is one you cannot distinguish from noise — this table prints the denominators so you can tell which is which. Three games a side is the floor for appearing here at all.

WNBA turnovers — venue gaps
Player	Club	Home (games)	Away (games)	Gap
Jordan Harrison	Fire	3.6 (7)	0.7 (7)	2.9 at home
Ezi Magbegor	Storm	1.8 (12)	0.5 (15)	1.3 at home
Shey Peddy	Fever	1.7 (7)	0.4 (10)	1.3 at home
Janelle Salaün	Valkyries	2.0 (8)	0.8 (5)	1.2 at home
DiJonai Carrington	Sky	0.3 (12)	1.2 (9)	0.9 away
Emma Meesseman	Liberty	2.3 (6)	1.4 (8)	0.9 at home
Tina Charles	Sun	1.7 (6)	0.8 (6)	0.9 at home
Zia Cooke	Storm	1.5 (21)	0.7 (23)	0.8 at home
Rori Harmon	Mystics	1.5 (4)	0.7 (9)	0.8 at home
Teaira McCowan	Lynx	0.2 (5)	1.0 (5)	0.8 away

Ahead of their own baseline over the last five

Last five logged games against the full log, reported only where the gap is more than a tenth of the player’s own average. It is a description of five games that have been played and it is not a forecast of the sixth.

Ahead of their own baseline over the last five
Player	Club	Last 5	Full log	Difference
Shatori Walker-Kimbrough	Dream	0.6 turnovers	0.2 over 25	200% above
Jaylyn Sherrod	Storm	1.0 turnovers	0.4 over 22	175% above
Megan Gustafson	Fire	1.4 turnovers	0.5 over 36	165% above
Aaliyah Nye	Sparks	0.4 turnovers	0.2 over 36	140% above
Kia Nurse	Tempo	1.4 turnovers	0.6 over 51	130% above
Taylor Thierry	Storm	0.4 turnovers	0.2 over 17	127% above
Julie Vanloo	Liberty	2.4 turnovers	1.1 over 15	112% above
Emma Cannon	Sparks	1.8 turnovers	0.9 over 17	104% above
Nyara Sabally	Tempo	2.8 turnovers	1.4 over 27	99% above
Nyadiew Puoch	Fire	1.2 turnovers	0.6 over 41	89% above

Behind their own baseline over the last five

The same comparison in the other direction, and the same caveat: five games is five games, and a run below a baseline is as often noise as it is a change.

Behind their own baseline over the last five
Player	Club	Last 5	Full log	Difference
Antonia Delaere	Lynx	0.0 turnovers	0.4 over 37	100% below
Tyasha Harris	Fever	0.0 turnovers	0.5 over 36	100% below
Angela Dugalic	Mystics	0.0 turnovers	0.7 over 35	100% below
Rori Harmon	Mystics	0.0 turnovers	0.9 over 13	100% below
Haley Jones	Wings	0.2 turnovers	1.6 over 17	88% below
Marine Fauthoux	Liberty	0.2 turnovers	1.2 over 19	83% below
Lexie Hull	Fever	0.2 turnovers	0.9 over 59	78% below
Ariel Atkins	Sparks	0.4 turnovers	1.7 over 47	76% below
Raven Johnson	Fever	0.2 turnovers	0.8 over 36	74% below
Te-Hina Paopao	Dream	0.2 turnovers	0.7 over 47	73% below

Common questions

Where does the WNBA turnovers coin-flip line sit?

At the half-point threshold each player has finished above in about half their logged games. It is measured per player from their own distribution rather than read off a sportsbook, which is why it is on this page at all: a posted line moves through the day and this page is rebuilt once, so a number taken from a book would be wrong by morning.

Is this a ranking of the best WNBA turnovers props?

No. Nothing here is ordered by how good a bet it is, and no price is quoted anywhere on the page. The tables are ordered by sample depth, by spread and by the size of a measured gap, because those are the things a game log can actually establish.

How many games are behind each turnovers figure?

The count is printed beside every one of them. A player only appears once they have ten or more logged games in the market, and games they did not play are absent rather than counted as zero, so an average describes games they were actually in.

Does a turnovers trend on this page predict the next game?

No. A trend here is a comparison between a player’s last five logged games and their full log, and it is reported only when the gap is large enough to be worth naming. It is a description of what has happened, and history is not a forecast.

What these tables are measuring, explained: how to read a hit rate and what its denominator hides, what an over/under line is and what it is not.

WNBA player props and live odds

Odds and lines come from licensed data feeds and refresh on a schedule; hit rates, edges and grades are Parlay Builder’s own calculations.