2026-07-17

Day by day

these are the scout_ml picks — the book grading is currently serving, and the same set listed in the sheet below. The season figure in the header bar is that same book over the whole season; this is a recent window of it.

31–16 · 66% · +6.84u across the last 1 days

07/1731–1666%+6.84u4 games

permalink to 2026-07-17 →

LAS @ CHI4–7−3.83u

Sydney Taylor Under 20.5 PRA22 vs 20.5 — missed by a hairshots didn't fall — the read held upTaylor's efficient 60% shooting night (6-10 FG, 4-7 3PT) combined with 26 minutes of run time pushed her over the line with 22 PRA, as her elite 81% true shooting percentage and 20% usage rate translated to consistent scoring output that exceeded the 20.5 threshold.
Natasha Cloud Under 3.5 REB6 vs 3.5shots didn't fall — the read held upCloud doubled her recent rebounding average with 6 boards, benefiting from an extra 6 minutes of court time (32 vs. 26.2 pregame expectation) and increased involvement as a playmaker (9 assists on 14% usage suggesting heavy ball-handling and floor time).
Natasha Cloud Under 21.5 PRA30 vs 21.5no clean explanationCloud's 9 assists and 6 rebounds pushed her to 30 PRA despite modest scoring, as she logged 32 minutes and ran the offense efficiently at 69% true shooting in a blowout win (+11).
Sydney Taylor Under 2.5 3PM4 vs 2.5no clean explanationTaylor's 4-7 three-point shooting (57%) far exceeded her typical volume and efficiency, with her 20% usage rate concentrated heavily on outside attempts rather than drives or mid-range looks. The hot hand proved unstoppable despite the modest 26 minutes, as she connected on over half her deep attempts to easily surpass the 2.5 line.
Natasha Cloud Under 9.5 RA15 vs 9.5shots didn't fall — the read held upCloud's 9 assists pushed her over the 9.5 line as she operated as the primary playmaker in 32 minutes, well above typical run for a bench role. Her efficient 69% true shooting and zero turnovers enabled high-volume, high-confidence decision-making that generated the additional dime needed to bust the under.
Sydney Taylor Under 18.5 PA21 vs 18.5 — missed by a hairshots didn't fall — the read held upTaylor's efficient 6-10 shooting (60% FG, 57% from three) on elevated usage (20%) in 26 minutes resulted in 19 points, but her 4 free-throw attempts—converting all 4—provided the 2 additional points needed to clear 18.5.

SEA @ IND8–3+2.32u

Natisha Hiedeman Under 4.5 AST8 vs 4.5shots didn't fall — the read held upHiedeman doubled her assist projection with 8 dimes in 30 minutes, operating as a primary facilitator with 20% usage and connecting on 55% of her field goals to generate efficient scoring opportunities for teammates. The high-volume playmaking in a steady role made the under an underestimate of her distribution touch.
Dominique Malonga Under 17.5 PTS28 vs 17.5paid over the fair numberMalonga torched the under with a 13-22 shooting night (59% FG) and 39% usage rate in 29 minutes, nearly doubling the 17.5-point line. Her elite 61% true shooting and aggressive volume in a high-usage role made the under untenable from the start.
Monique Billings Under 8.5 PTS16 vs 8.5shots didn't fall — the read held upBillings erupted with 31 minutes—well above her pre-game 20.1—and converted 11 of 14 shots (79% TS) to easily clear 8.5 points; the extended role and elite efficiency on high volume were the decisive factors.

ATL @ TOR10–4+3.38u

Naz Hillmon Under 1.5 3PM4 vs 1.5shots didn't fall — the read held upHillmon went perfect from three (4-4) in just 25 minutes, a sharp departure from her L10 average of 1.0 threes and her typical volume—she simply got hot at the right time when opportunities presented themselves. The under was predicated on her historical shooting pattern, but elite efficiency from deep (100% on limited attempts) overrode the volume concerns that justified the 1.5 threshold.
Julie Allemand Under 18.5 PRA20 vs 18.5 — missed by a hairshots didn't fall — the read held upAllemand's efficient 9 points (3-5 FG, 3-4 3PT) combined with 5 rebounds and 6 assists to reach 20 PRA, as she stayed on the floor for a full 32 minutes without fouling out despite 3 personal fouls. Her high true shooting percentage (90%) meant even limited scoring volume was highly productive relative to the betting threshold.
Maria Conde Under 11.5 PA18 vs 11.5paid over the fair numberConde cashed 8-of-9 free throws and drew fouls at a high rate, accumulating 18 points despite shooting just 2-8 from the field, which pushed her well over the 11.5 assists + points projection. Her 31 minutes and 18% usage still generated enough volume to exceed the line through efficient free-throw shooting and getting to the line.
Julie Allemand Under 11.5 PR14 vs 11.5shots didn't fall — the read held upAllemand's elite 90% true shooting—fueled by perfect 3-point shooting (3-4) and efficient field-goal work (3-5)—pushed her to 14 points despite modest volume, easily clearing the 11.5 under. She maximized her 32 minutes and 12% usage with near-flawless scoring efficiency rather than volume.

CON @ PHO9–2+4.97u

DeWanna Bonner Under 8.5 RA11 vs 8.5shots didn't fall — the read held upBonner's 10 rebounds easily cleared the 8.5 line despite poor scoring efficiency, as she logged a team-high 30 minutes and maintained strong rebounding activity on 11 shot attempts. The Under missed because her rebounding volume—not scoring—drove the prop, and she was on the floor constantly in what appears to have been a low-scoring, possession-heavy game.
Monique Akoa Makani Under 3.5 AST4 vs 3.5 — missed by a hairshots didn't fall — the read held upDespite a season-low 20 minutes and invisible scoring (0-for-6), Akoa Makani still reached 4 assists on modest 19% usage, suggesting she maintained setup duties even in limited action and off-night shooting. Her recent L10 average of 2.3 assists underestimated her floor playmaking role, which proved resilient enough to clear 3.5 despite the offensive drought.

Flat 1 unit per priced bet, settled at the price we posted. Voids are not bets — excluded from the record, the hit rate and the units. Open a day for the per-game split and why each loss lost.