How WNBA steals actually behave

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Across 199 WNBA players with at least 10 logged games in steals, this page measures 7499 games in total. The median player in that field averages 0.7 steals. The line closest to a coin flip sits at 0.5 for the median of the 199 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 47 players whose spread can be measured, 0 cluster tightly around their average, 3 vary moderately and 44 swing widely. 199 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 steals

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 199 measured; the figures above this table are over all 199.

WNBA steals — measured field
PlayerClubLogged gamesAverageBalanced lineHit rate there
Alyssa ThomasMercury631.5 stealsOver 1.528 of 63 (44%)
Chelsea GrayAces621.6 stealsOver 1.528 of 62 (45%)
DeWanna BonnerDream621.0 stealsOver 0.539 of 62 (63%)
Jackie YoungAces621.0 stealsOver 0.539 of 62 (63%)
Jewell LoydAces611.2 stealsOver 1.517 of 61 (28%)
Kahleah CopperMercury610.7 stealsOver 0.534 of 61 (56%)
A'ja WilsonAces601.6 stealsOver 1.524 of 60 (40%)
Kelsey MitchellFever591.1 stealsOver 0.539 of 59 (66%)
Kiah StokesValkyries590.4 stealsOver 0.520 of 59 (34%)
Lexie HullFever590.7 stealsOver 0.526 of 59 (44%)
NaLyssa SmithAces590.6 stealsOver 0.528 of 59 (47%)
Natasha HowardLynx591.5 stealsOver 1.527 of 59 (46%)
Courtney WilliamsLynx581.3 stealsOver 1.525 of 58 (43%)
Jessica ShepardWings580.7 stealsOver 0.532 of 58 (55%)
Kayla McBrideLynx581.5 stealsOver 1.527 of 58 (47%)
Bridget CarletonFire571.3 stealsOver 1.520 of 57 (35%)
Natasha MackMercury570.7 stealsOver 0.524 of 57 (42%)
Brianna TurnerAces560.3 stealsOver 0.515 of 56 (27%)
Natisha HiedemanStorm561.1 stealsOver 0.535 of 56 (63%)
Aliyah BostonFever551.5 stealsOver 1.524 of 55 (44%)
Kaila CharlesValkyries550.9 stealsOver 0.529 of 55 (53%)
Makayla TimpsonFever550.4 stealsOver 0.518 of 55 (33%)
Maya CaldwellLynx550.7 stealsOver 0.527 of 55 (49%)
Naz HillmonDream550.6 stealsOver 0.522 of 55 (40%)
Rhyne HowardDream552.1 stealsOver 1.533 of 55 (60%)
Veronica BurtonValkyries551.6 stealsOver 1.526 of 55 (47%)
Allisha GrayDream541.2 stealsOver 0.536 of 54 (67%)
Nia CoffeyLynx540.7 stealsOver 0.525 of 54 (46%)
Emily EngstlerFire531.3 stealsOver 1.520 of 53 (38%)
Erica WheelerSparks530.9 stealsOver 0.534 of 53 (64%)
Jonquel JonesLiberty530.6 stealsOver 0.524 of 53 (45%)
Nneka OgwumikeSparks531.2 stealsOver 1.514 of 53 (26%)
Dearica HambySparks521.5 stealsOver 1.522 of 52 (42%)
Elizabeth WilliamsSky520.7 stealsOver 0.526 of 52 (50%)
Kamilla CardosoSky520.5 stealsOver 0.522 of 52 (42%)
Lexi HeldMercury520.4 stealsOver 0.513 of 52 (25%)
Natasha CloudSky521.2 stealsOver 1.519 of 52 (37%)
Stefanie DolsonStorm520.3 stealsOver 0.514 of 52 (27%)
Stephanie TalbotAces520.5 stealsOver 0.519 of 52 (37%)
Jade MelbourneStorm510.9 stealsOver 0.533 of 51 (65%)

The steadiest WNBA steals 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 steals records
PlayerClubLogged gamesAverageStandard deviationSpread as % of average
Leïla LacanSun102.3 steals1.667%
Rhyne HowardDream552.1 steals1.468%
Gabby WilliamsValkyries501.6 steals1.169%
Ariel AtkinsSparks471.6 steals1.170%
Azzi FuddWings301.7 steals1.373%
Azurá StevensSparks111.1 steals0.873%
Jordin CanadaDream491.8 steals1.475%
Leila LacanSun271.7 steals1.275%
Kayla McBrideLynx581.5 steals1.279%
A'ja WilsonAces601.6 steals1.379%

The widest WNBA steals 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 steals swings
PlayerClubLogged gamesAverageStandard deviationSpread as % of average
Amy OkonkwoFire131.2 steals1.5120%
Noemie BrochantMercury411.0 steals1.2119%
Emma MeessemanLiberty141.1 steals1.2114%
Jackie YoungAces621.0 steals1.1108%
Laura JuskaiteTempo411.2 steals1.3107%
Brittney SykesTempo301.0 steals1.1107%
DeWanna BonnerDream621.0 steals1.1103%
Jordan HorstonStorm351.1 steals1.1103%
Kelsey PlumMercury281.1 steals1.1103%
Natisha HiedemanStorm561.1 steals1.1101%

The widest home and away gaps in WNBA steals

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 steals — venue gaps
PlayerClubHome (games)Away (games)Gap
Amy OkonkwoFire1.8 (6)0.7 (7)1.1 at home
DiJonai CarringtonSky0.3 (12)1.2 (9)0.9 away
Arike OgunbowaleWings1.4 (22)0.6 (20)0.8 at home
Temi FágbénléValkyries0.4 (7)1.2 (5)0.8 away
Megan GustafsonFire0.1 (20)0.8 (16)0.7 away
Lucy OlsenMystics0.1 (15)0.8 (16)0.7 away
Breanna StewartLiberty1.0 (24)1.7 (26)0.7 away
Emma MeessemanLiberty1.5 (6)0.8 (8)0.7 at home
Rae BurrellSparks1.1 (25)0.5 (26)0.6 at home
Pauline AstierLiberty0.5 (20)1.1 (21)0.6 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
PlayerClubLast 5Full logDifference
Lexi HeldMercury1.8 steals0.4 over 52368% above
Megan GustafsonFire1.4 steals0.4 over 36260% above
Zia CookeStorm1.2 steals0.4 over 44211% above
Natasha MackMercury2.0 steals0.7 over 57185% above
Isobel BorlaseDream0.8 steals0.3 over 42158% above
Kennedy BurkeSun2.4 steals0.9 over 51155% above
Kaitlyn ChenValkyries0.6 steals0.2 over 50150% above
Karlie SamuelsonFire1.4 steals0.6 over 30147% above
Aziaha JamesWings2.0 steals0.9 over 45131% above
Holly WinterburnFire1.2 steals0.6 over 29118% 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
PlayerClubLast 5Full logDifference
Kamilla CardosoSky0.0 steals0.5 over 52100% below
Stefanie DolsonStorm0.0 steals0.3 over 52100% below
Odyssey SimsWings0.0 steals0.7 over 51100% below
Michaela OnyenwereMystics0.0 steals0.4 over 48100% below
Han XuLiberty0.0 steals0.3 over 41100% below
Anastasiia Olairi KosuLynx0.0 steals0.4 over 40100% below
Marine JohannesLiberty0.0 steals0.8 over 38100% below
Cassandre ProsperMystics0.0 steals0.3 over 36100% below
Aaliyah NyeSparks0.0 steals0.1 over 36100% below
Sydney TaylorSky0.0 steals0.7 over 35100% below

Common questions

Where does the WNBA steals 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 steals 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 steals 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 steals 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.