Aryna Sabalenka vs Linda Noskova

hard wta grand_slam best of 3 tennis_wta_us_open · commence 2026-09-08 15:30:00+00:00 · completed winner: a

P(Aryna Sabalenka) = 1.000  |  P(Linda Noskova) = 0.000
live composite (last tick)

Sharp anchor — Pinnacle pre-match

Pinnacle P(Aryna Sabalenka) 0.703
Pinnacle P(Linda Noskova) 0.297
n_books observed 1 live

Sharp anchor sourced via OddsAPI event_id lookup → Pinnacle no-vig computation. (Field-id mismatch fix shipped 2026-05-02 — pinnacle capture is now the source of truth for pre-match anchoring.)

Surface ELO radar

Surface Aryna SabalenkaLinda Noskova Diff (a−b)
hard 1500 (0) 1500 (0) +0
clay 1500 (0) 1500 (0) +0
grass 1500 (0) 1500 (0) +0
indoor 1500 (0) 1500 (0) +0
overall 1500 (0) 1500 (0) +0

Per-surface ELO from 24h-cached global rater. Number-in-parens = matches contributing to that rating.

Style matchup (display-only · v0 priors · NOT in headline)

Player Archetype n matches Hold % Aces / match
Aryna Sabalenka big_server 190 0.750 5.3
Linda Noskova all_court 65 0.736 3.9

Matchup adjustment: +0.00pp toward Linda Noskova on hard.

v0 sharp priors per tennis-betting-expert lock 2026-05-02. Display-only — NOT blended into the headline composite probability above. Promotion to wired-in pending: N≥200 archetype-tagged settled matches with closing-line capture + Brier delta ≥+0.005 vs unwired baseline + no 5pp-bucket regression. Re-evaluate post-Roland Garros (2026-06-09).

Composite adjustments (live)

AdjustmentAryna SabalenkaLinda NoskovaNet
Match fatigue (14d load) -2.50pp (load 5.0) -2.15pp (load 4.3) -0.35pp

Live adjustments flowed into the headline composite probability above. Surface transition gated to documented poor-history (>15% win-rate drop in first 3 surface-change matches). Fatigue: 14-day load weighted by best-of (BO5=2.0, BO3=1.0), capped ±3pp. Tennis-betting-expert RG R1 audit 2026-05-24.

Composite signal weights

SignalWeight
surface_elo 0.35
recent_form 0.18
h2h_matrix 0.16
surface_transition 0.11
match_simulator 0.10
tournament_fatigue 0.10
Sum 1.00

Locked weights per tennis-betting-expert composite design 2026-04-26. Signals flagged low_data are excluded; remaining weights renormalize proportionally. h2h overweighting noted in audit; will be revisited with a dedicated calibration pass after Roland Garros.

Live trajectory (58 ticks)

Time Set Game Score Server P(Aryna Sabalenka) P(Linda Noskova) Exp games Source
16:01:36 1 5 {'sets': [], 'current_set_games': [4, 1], 'sets_won_synthetic': True, 'point_score': ['0', '30']} b 0.628 0.372 29.5 feed
16:02:07 1 5 {'sets': [], 'current_set_games': [4, 1], 'sets_won_synthetic': True, 'point_score': ['15', '30']} b 0.597 0.403 29.5 feed
16:02:38 1 5 {'sets': [], 'current_set_games': [4, 1], 'sets_won_synthetic': True, 'point_score': ['15', '40']} b 0.611 0.389 29.5 feed
16:03:08 1 5 {'sets': [], 'current_set_games': [4, 1], 'sets_won_synthetic': True, 'point_score': ['30', '40']} b 0.603 0.397 29.6 feed
16:03:39 1 5 {'sets': [], 'current_set_games': [4, 1], 'sets_won_synthetic': True, 'point_score': ['40', '40']} b 0.602 0.398 29.5 feed
16:04:09 1 6 {'sets': [], 'current_set_games': [4, 2], 'sets_won_synthetic': True, 'point_score': ['0', '0']} b 0.523 0.477 30.4 feed
16:04:40 1 6 {'sets': [], 'current_set_games': [4, 2], 'sets_won_synthetic': True, 'point_score': ['0', '15']} b 0.525 0.475 30.2 feed
16:05:11 1 6 {'sets': [], 'current_set_games': [4, 2], 'sets_won_synthetic': True, 'point_score': ['0', '30']} b 0.535 0.465 30.4 feed
16:05:41 1 6 {'sets': [], 'current_set_games': [4, 2], 'sets_won_synthetic': True, 'point_score': ['0', '40']} b 0.521 0.479 30.5 feed
16:06:12 1 6 {'sets': [], 'current_set_games': [4, 2], 'sets_won_synthetic': True, 'point_score': ['15', '40']} b 0.555 0.445 30.7 feed
16:06:43 1 7 {'sets': [], 'current_set_games': [5, 2], 'sets_won_synthetic': True, 'point_score': ['0', '0']} b 0.604 0.396 31.5 feed
16:07:13 1 7 {'sets': [], 'current_set_games': [5, 2], 'sets_won_synthetic': True, 'point_score': ['0', '0']} b 0.599 0.401 31.4 feed
16:11:42 1 8 {'sets': [], 'current_set_games': [5, 3], 'sets_won_synthetic': True, 'point_score': ['0', '0']} b 0.542 0.458 32.3 feed
16:12:13 1 8 {'sets': [], 'current_set_games': [5, 3], 'sets_won_synthetic': True, 'point_score': ['0', '15']} b 0.538 0.462 32.4 feed
16:12:43 1 8 {'sets': [], 'current_set_games': [5, 3], 'sets_won_synthetic': True, 'point_score': ['0', '15']} b 0.525 0.475 32.4 feed
16:13:14 1 8 {'sets': [], 'current_set_games': [5, 3], 'sets_won_synthetic': True, 'point_score': ['15', '15']} b 0.527 0.473 32.5 feed
18:19:28 4 13 {'sets': [[6, 0], [6, 0], [0, 6]], 'current_set_games': [7, 6], 'sets_won_synthetic': True, 'point_score': ['18', '17']} b 1.000 0.000 0.0 feed
18:20:28 4 13 {'sets': [[6, 0], [6, 0], [0, 6]], 'current_set_games': [7, 6], 'sets_won_synthetic': True, 'point_score': ['18', '17']} b 1.000 0.000 0.0 feed
18:21:28 4 13 {'sets': [[6, 0], [6, 0], [0, 6]], 'current_set_games': [7, 6], 'sets_won_synthetic': True, 'point_score': ['18', '17']} b 1.000 0.000 0.0 feed
18:22:28 4 13 {'sets': [[6, 0], [6, 0], [0, 6]], 'current_set_games': [7, 6], 'sets_won_synthetic': True, 'point_score': ['18', '17']} b 1.000 0.000 0.0 feed
18:23:28 4 13 {'sets': [[6, 0], [6, 0], [0, 6]], 'current_set_games': [7, 6], 'sets_won_synthetic': True, 'point_score': ['18', '17']} b 1.000 0.000 0.0 feed
18:24:29 4 13 {'sets': [[6, 0], [6, 0], [0, 6]], 'current_set_games': [7, 6], 'sets_won_synthetic': True, 'point_score': ['18', '17']} b 1.000 0.000 0.0 feed
18:25:29 4 13 {'sets': [[6, 0], [6, 0], [0, 6]], 'current_set_games': [7, 6], 'sets_won_synthetic': True, 'point_score': ['18', '17']} b 1.000 0.000 0.0 feed
18:26:29 4 13 {'sets': [[6, 0], [6, 0], [0, 6]], 'current_set_games': [7, 6], 'sets_won_synthetic': True, 'point_score': ['18', '17']} b 1.000 0.000 0.0 feed
18:27:29 4 13 {'sets': [[6, 0], [6, 0], [0, 6]], 'current_set_games': [7, 6], 'sets_won_synthetic': True, 'point_score': ['18', '17']} b 1.000 0.000 0.0 feed
18:28:29 4 13 {'sets': [[6, 0], [6, 0], [0, 6]], 'current_set_games': [7, 6], 'sets_won_synthetic': True, 'point_score': ['18', '17']} b 1.000 0.000 0.0 feed
18:29:29 4 13 {'sets': [[6, 0], [6, 0], [0, 6]], 'current_set_games': [7, 6], 'sets_won_synthetic': True, 'point_score': ['18', '17']} b 1.000 0.000 0.0 feed
18:30:29 4 13 {'sets': [[6, 0], [6, 0], [0, 6]], 'current_set_games': [7, 6], 'sets_won_synthetic': True, 'point_score': ['18', '17']} b 1.000 0.000 0.0 feed
18:31:29 4 13 {'sets': [[6, 0], [6, 0], [0, 6]], 'current_set_games': [7, 6], 'sets_won_synthetic': True, 'point_score': ['18', '17']} b 1.000 0.000 0.0 feed
18:32:29 4 13 {'sets': [[6, 0], [6, 0], [0, 6]], 'current_set_games': [7, 6], 'sets_won_synthetic': True, 'point_score': ['18', '17']} b 1.000 0.000 0.0 feed

Showing last 30 of 58 ticks.

Tennis variance: best-of-3 single-match outcomes are noisy. Composite + trajectory shown for transparency, not as a tout. Use closing-line comparison (vs Pinnacle anchor above) as the canonical edge metric.