WNBAGM

Azurá Stevens

Chicago Sky · F · 2026 stats, contract & trade value

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Talent score
48
#56 in the W
Trade value
42
#69 in the W
Contract surplus
-16.1
talent vs. salary expectation
Position
F
Talent & trade value 20–9966+ star40–65 rotationunder 40 fringe

Over her deal through 2028, Stevens is producing 16.1 pts below what her salary should buy — contract surplus averages every remaining year, with future seasons projected on the league aging curve and discounted.

Azurá Stevens headshot

Azurá Stevens

48
Chicago Sky · F · age 30
Value & contract
Talent
48
Rotation
Trade value
42
Replacement
Surplus
-16.1
Overpaid
Talent trend48– flat
954320
LG AVG
Last 30 daysToday
Contract3 yrs · $3.15M gtd
2026$1MGTD
2027$1.05MGTD
2028$1.1MGTD
GuaranteedNon-guaranteedTeam option

Box scoreper game · 31 GP
PoorGreatpercentile vs qualified
Points
66
10.7
Assists
66
2.2
Rebounds
88
6.5
Usage
69
21.5 %
Efficiency
27
51 % TS
On-court impactwRAPM · 1,582 poss · 2026-08-30
PoorGreatpercentile vs qualified
Offense
24
−1.2
Defense
11
−1.9

wRAPM — her effect on team net scoring per 100 possessions, adjusted for teammates and opponents.

Stands out for rebounding; defense is the soft spot. Reads as a Rotation-level talent.
Talent outlook
2026
48 talent
2027
46 proj
4053
2028
44 proj
3853

Projected per stat on the fitted league aging curves (scoring fades, rebounding holds, minutes drive late decline) — 4,700 player-seasons, 1997–2025. Ranges are 10th–90th percentile from held-out backtest error.

Career stats
SeasonTeamGPMPGPPGRPGAPGSPGBPGTOVFG%3P%FT%
2018DAL3420.68.94.61.30.91.11.543.0%31.8%78.8%
2019DAL916.04.83.60.60.61.11.035.8%11.1%80.0%
2020CHI1327.311.55.91.50.91.81.550.0%38.5%85.0%
2021CHI3019.67.44.60.80.80.70.950.0%33.3%81.3%
2022CHI3521.910.63.90.80.51.10.747.2%36.2%74.4%
2023LAS3526.010.85.91.11.20.91.540.4%32.1%75.4%
2024LAS2024.79.67.01.90.80.91.839.9%35.0%81.5%
2025LAS4412.88.02.11.21.1
2026CHI3124.610.76.52.20.80.71.642.6%25.2%78.8%
Projected · 2027–2028
SeasonTalentPPGRPGAPG
20274610.86.72.1
2028449.86.32.0

Future-year talent figures above are projections on the league aging curve (fit from 4,692 player-seasons, 1997–2025), not measurements — they fade in the display because they should.How the projections work →

Best team fits

Her attribute profile scored against each team's current roster deficits — where she'd fill the biggest hole, not just where she'd be fun.

Portland Fire16-24 · thinnest in rebounding / size + playmaking / ball-handling · 1.9M space
build this trade · fit score 55
Connecticut Sun10-30 · thinnest in scoring + playmaking / ball-handling · 1.0M space
build this trade · fit score 50
Washington Mystics24-16 · thinnest in playmaking / ball-handling + scoring · 1.4M space
build this trade · fit score 42

What would it take?

A fair package each interested team would have to send for Azurá Stevens — assembled and priced by the same engine that grades trades, most valuable pieces first until the outgoing value matches hers. The percentage is what that package is worth on the trade-value scale: 100% is an even match for Azurá Stevens, above 100% a slight overpay to get there. Open one in the machine to tweak it.

Portland Fire sendsneeds a filler · 105% of Stevens’s value
Bridget Carleton
open this trade in the machine →
Connecticut Sun sendscap-legal · 117% of Stevens’s value
Aaliyah Edwards
open this trade in the machine →
Washington Mystics sendscap-legal · 107% of Stevens’s value
Lauren Betts
open this trade in the machine →

A starting point, not a prediction — each package is the fewest fair pieces by model value, and a real deal would flex around roster fit and both front offices. “Needs a filler” means the salaries don't yet fit under the cap without another piece.

Chicago Sky teammates

Aging comps

The closest player-seasons in league history (1997–2025) to her current age, per-36 profile, and role — the careers her projection walks alongside.

  • Jonquel Jones · 2023 · age 30
  • Michelle Snow · 2010 · age 31
  • Cheyenne Parker-Tyus · 2022 · age 30

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