How WNBA steals actually behave

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Across 182 WNBA players with at least 10 logged games in steals, this page measures 6567 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 182 players whose distribution supports one. Half the field is more often over it, half more often under. The deepest sample here is Kaila Charles, with 57 logged games. Of the 44 players whose spread can be measured, 0 cluster tightly around their average, 2 vary moderately and 42 swing widely. 182 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 2026-11-15, rebuilt daily from official box scores. Window: 2026-05-08 to 2026-10-31. No prices appear on this page.

6,567 logged player-games from 353 unique games. A player-game is one player in one game, so a single game counts once for every player it logged.

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 182 measured; the figures above this table are over all 182.

WNBA steals: measured field
PlayerClubLogged gamesAverageBalanced lineHit rate there
Kaila CharlesValkyries570.8 stealsOver 0.525 of 57 (44%)
Kaitlyn ChenValkyries570.2 stealsOver 0.512 of 57 (21%)
Kayla ThorntonValkyries570.6 stealsOver 0.522 of 57 (39%)
Veronica BurtonValkyries571.5 stealsOver 1.524 of 57 (42%)
Isobel BorlaseDream560.4 stealsOver 0.515 of 56 (27%)
Kiah StokesValkyries560.5 stealsOver 0.523 of 56 (41%)
Angel ReeseDream551.7 stealsOver 1.529 of 55 (53%)
Jordin CanadaDream551.9 stealsOver 1.534 of 55 (62%)
Naz HillmonDream550.6 stealsOver 0.524 of 55 (44%)
Rhyne HowardDream552.3 stealsOver 2.524 of 55 (44%)
Tiffany HayesValkyries550.9 stealsOver 0.530 of 55 (55%)
Allisha GrayDream541.3 stealsOver 1.518 of 54 (33%)
DeWanna BonnerDream541.0 stealsOver 0.533 of 54 (61%)
Gabby WilliamsValkyries521.8 stealsOver 1.527 of 52 (52%)
Madina OkotDream510.3 stealsOver 0.514 of 51 (27%)
Cecilia ZandalasiniValkyries500.9 stealsOver 0.526 of 50 (52%)
Janelle SalaunValkyries500.5 stealsOver 0.521 of 50 (42%)
Chelsea GrayAces491.4 stealsOver 1.521 of 49 (43%)
Han XuLiberty490.3 stealsOver 0.512 of 49 (24%)
Jackie YoungAces491.0 stealsOver 0.527 of 49 (55%)
Pauline AstierLiberty490.8 stealsOver 0.528 of 49 (57%)
Jonquel JonesLiberty480.6 stealsOver 0.521 of 48 (44%)
Stephanie TalbotAces480.7 stealsOver 0.521 of 48 (44%)
A'ja WilsonAces471.4 stealsOver 1.517 of 47 (36%)
Arike OgunbowaleWings471.0 stealsOver 0.530 of 47 (64%)
Breanna StewartLiberty471.4 stealsOver 1.521 of 47 (45%)
Brianna TurnerAces470.2 stealsOver 0.510 of 47 (21%)
Jewell LoydAces471.1 stealsOver 0.535 of 47 (74%)
Kelsey MitchellFever471.0 stealsOver 0.534 of 47 (72%)
Lexie HullFever470.6 stealsOver 0.518 of 47 (38%)
Georgia AmooreMystics460.3 stealsOver 0.513 of 46 (28%)
Kayla McBrideLynx461.7 stealsOver 1.522 of 46 (48%)
Lauren BettsMystics460.5 stealsOver 0.519 of 46 (41%)
Makayla TimpsonFever460.6 stealsOver 0.521 of 46 (46%)
Marine JohannesLiberty460.7 stealsOver 0.522 of 46 (48%)
Maya CaldwellLynx460.7 stealsOver 0.523 of 46 (50%)
Monique BillingsFever460.9 stealsOver 0.526 of 46 (57%)
Natasha HowardLynx461.5 stealsOver 1.523 of 46 (50%)
Rebekah GardnerLiberty460.5 stealsOver 0.519 of 46 (41%)
Sophie CunninghamFever460.5 stealsOver 0.518 of 46 (39%)

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
Gabby WilliamsValkyries521.8 steals1.162%
Ariel AtkinsSparks421.6 steals1.166%
Rhyne HowardDream552.3 steals1.671%
Jordin CanadaDream551.9 steals1.473%
Azzi FuddWings301.7 steals1.373%
Bridget CarletonFire401.6 steals1.275%
Leila LacanSun301.6 steals1.277%
Chelsea GrayAces491.4 steals1.178%
Kayla McBrideLynx461.7 steals1.378%
Julie AllemandTempo331.3 steals1.078%

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
Kelsey PlumMercury171.0 steals1.2119%
Noemie BrochantMercury431.0 steals1.2118%
Brittney SykesTempo171.2 steals1.3110%
Jordan HorstonStorm371.0 steals1.1109%
Nyara SaballyTempo241.0 steals1.1108%
Saniya RiversSun381.1 steals1.1105%
Natisha HiedemanStorm401.1 steals1.1104%
DeWanna BonnerDream541.0 steals1.1102%
Caitlin ClarkFever431.0 steals1.0102%
Laura JuskaiteTempo441.4 steals1.4101%

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
DiJonai CarringtonSky0.1 (7)1.5 (4)1.4 away
Tonie MorganSparks0.4 (7)1.6 (5)1.2 away
Megan GustafsonFire0.1 (10)1.1 (9)1.0 away
Maddy WestbeldMercury1.0 (5)0.0 (5)1.0 at home
Breanna StewartLiberty1.0 (23)1.8 (24)0.8 away
Jaylyn SherrodStorm1.1 (7)0.3 (6)0.8 at home
Arike OgunbowaleWings1.4 (23)0.6 (24)0.8 at home
Flau'jae JohnsonStorm1.0 (20)1.7 (22)0.7 away
Pauline AstierLiberty0.5 (24)1.1 (25)0.6 away
Jackie YoungAces0.7 (25)1.3 (24)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
Raquel CarreraLiberty0.8 steals0.2 over 25300% above
Raven JohnsonFever1.4 steals0.5 over 42209% above
Zia CookeStorm1.2 steals0.4 over 41207% above
Elizabeth WilliamsSky2.2 steals0.7 over 44203% above
Lexi HeldMercury1.4 steals0.5 over 42180% above
Gianna KneepkensSun0.6 steals0.2 over 36170% above
Megan DiLeoFire0.8 steals0.3 over 22151% above
Megan GustafsonFire1.4 steals0.6 over 19142% above
Holly WinterburnFire1.2 steals0.6 over 29118% above
Karlie SamuelsonFire1.2 steals0.6 over 32113% 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
Kaitlyn ChenValkyries0.0 steals0.2 over 57100% below
Madina OkotDream0.0 steals0.3 over 51100% below
Brianna TurnerAces0.0 steals0.2 over 47100% below
Marine JohannesLiberty0.0 steals0.7 over 46100% below
Maddy SiegristWings0.0 steals0.4 over 44100% below
Stefanie DolsonStorm0.0 steals0.3 over 44100% below
Te-Hina PaopaoDream0.0 steals0.2 over 42100% below
Angela DugalicMystics0.0 steals0.3 over 40100% below
Cassandre ProsperMystics0.0 steals0.2 over 40100% below
Antonia DelaereLynx0.0 steals0.4 over 40100% 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 and grades are Parlay Builder’s own calculations.