Sara Bejlek vs Ekaterina Alexandrova

hard wta masters_1000 best of 3 tennis_wta_cincinnati_open · commence 2026-08-18 20:30:00+00:00 · completed winner: a

P(Sara Bejlek) = 1.000  |  P(Ekaterina Alexandrova) = 0.000
live composite (last tick)

Sharp anchor — Pinnacle pre-match

Pinnacle P(Sara Bejlek) 0.515
Pinnacle P(Ekaterina Alexandrova) 0.485
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 Sara BejlekEkaterina Alexandrova 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
Sara Bejlek unknown 4 0.500 0.2
Ekaterina Alexandrova big_server 145 0.708 5.1

Style matchup signal: style matchup low_data: missing archetype or surface

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)

AdjustmentSara BejlekEkaterina AlexandrovaNet
Match fatigue (14d load) -1.50pp (load 3.0) -3.00pp (load 7.6) +1.50pp

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 (200 ticks)

Time Set Game Score Server P(Sara Bejlek) P(Ekaterina Alexandrova) Exp games Source
22:49:10 3 4 {'sets': [[6, 0], [0, 6]], 'current_set_games': [3, 1], 'sets_won_synthetic': True, 'point_score': ['40', '40']} b 0.576 0.424 30.8 feed
22:49:40 3 4 {'sets': [[6, 0], [0, 6]], 'current_set_games': [3, 1], 'sets_won_synthetic': True, 'point_score': ['40', 'A']} b 0.562 0.438 30.8 feed
22:50:11 3 5 {'sets': [[6, 0], [0, 6]], 'current_set_games': [4, 1], 'sets_won_synthetic': True, 'point_score': ['0', '0']} b 0.725 0.275 31.8 feed
22:50:41 3 5 {'sets': [[6, 0], [0, 6]], 'current_set_games': [4, 1], 'sets_won_synthetic': True, 'point_score': ['0', '0']} b 0.722 0.278 31.7 feed
22:51:12 3 5 {'sets': [[6, 0], [0, 6]], 'current_set_games': [4, 1], 'sets_won_synthetic': True, 'point_score': ['0', '0']} b 0.726 0.274 31.8 feed
22:51:43 3 5 {'sets': [[6, 0], [0, 6]], 'current_set_games': [4, 1], 'sets_won_synthetic': True, 'point_score': ['0', '0']} b 0.740 0.260 31.8 feed
22:52:38 3 5 {'sets': [[6, 0], [0, 6]], 'current_set_games': [4, 1], 'sets_won_synthetic': True, 'point_score': ['15', '15']} b 0.716 0.284 31.8 feed
22:53:09 3 5 {'sets': [[6, 0], [0, 6]], 'current_set_games': [4, 1], 'sets_won_synthetic': True, 'point_score': ['30', '15']} b 0.745 0.255 31.9 feed
22:53:39 3 5 {'sets': [[6, 0], [0, 6]], 'current_set_games': [4, 1], 'sets_won_synthetic': True, 'point_score': ['30', '30']} b 0.712 0.288 31.7 feed
22:54:10 3 5 {'sets': [[6, 0], [0, 6]], 'current_set_games': [4, 1], 'sets_won_synthetic': True, 'point_score': ['40', '30']} b 0.734 0.266 31.8 feed
22:54:41 3 5 {'sets': [[6, 0], [0, 6]], 'current_set_games': [4, 1], 'sets_won_synthetic': True, 'point_score': ['40', '40']} b 0.733 0.267 31.8 feed
22:55:11 3 5 {'sets': [[6, 0], [0, 6]], 'current_set_games': [4, 1], 'sets_won_synthetic': True, 'point_score': ['40', 'A']} b 0.717 0.283 31.8 feed
22:55:42 3 6 {'sets': [[6, 0], [0, 6]], 'current_set_games': [5, 1], 'sets_won_synthetic': True, 'point_score': ['0', '0']} b 0.859 0.141 32.7 feed
22:56:12 3 6 {'sets': [[6, 0], [0, 6]], 'current_set_games': [5, 1], 'sets_won_synthetic': True, 'point_score': ['15', '0']} b 0.873 0.127 32.8 feed
22:56:43 3 6 {'sets': [[6, 0], [0, 6]], 'current_set_games': [5, 1], 'sets_won_synthetic': True, 'point_score': ['15', '15']} b 0.866 0.134 32.8 feed
22:57:13 3 6 {'sets': [[6, 0], [0, 6]], 'current_set_games': [5, 1], 'sets_won_synthetic': True, 'point_score': ['30', '30']} b 0.873 0.127 32.8 feed
22:57:44 3 6 {'sets': [[6, 0], [0, 6]], 'current_set_games': [5, 1], 'sets_won_synthetic': True, 'point_score': ['40', '30']} b 0.871 0.129 32.8 feed
22:58:15 3 7 {'sets': [[6, 0], [0, 6]], 'current_set_games': [5, 2], 'sets_won_synthetic': True, 'point_score': ['0', '0']} b 0.735 0.265 33.8 feed
22:58:45 3 7 {'sets': [[6, 0], [0, 6]], 'current_set_games': [5, 2], 'sets_won_synthetic': True, 'point_score': ['0', '0']} b 0.714 0.286 33.7 feed
22:59:16 3 7 {'sets': [[6, 0], [0, 6]], 'current_set_games': [5, 2], 'sets_won_synthetic': True, 'point_score': ['0', '0']} b 0.730 0.270 33.8 feed
22:59:46 3 7 {'sets': [[6, 0], [0, 6]], 'current_set_games': [5, 2], 'sets_won_synthetic': True, 'point_score': ['0', '0']} b 0.728 0.272 33.8 feed
23:00:17 3 7 {'sets': [[6, 0], [0, 6]], 'current_set_games': [5, 2], 'sets_won_synthetic': True, 'point_score': ['0', '15']} b 0.719 0.281 33.7 feed
23:00:47 3 7 {'sets': [[6, 0], [0, 6]], 'current_set_games': [5, 2], 'sets_won_synthetic': True, 'point_score': ['0', '30']} b 0.717 0.283 33.7 feed
23:01:18 3 7 {'sets': [[6, 0], [0, 6]], 'current_set_games': [5, 2], 'sets_won_synthetic': True, 'point_score': ['0', '30']} b 0.717 0.283 33.7 feed
23:01:48 3 7 {'sets': [[6, 0], [0, 6]], 'current_set_games': [5, 2], 'sets_won_synthetic': True, 'point_score': ['15', '30']} b 0.719 0.281 33.8 feed
23:02:19 3 7 {'sets': [[6, 0], [0, 6]], 'current_set_games': [5, 2], 'sets_won_synthetic': True, 'point_score': ['15', '40']} b 0.725 0.275 33.8 feed
23:02:49 3 7 {'sets': [[6, 0], [0, 6]], 'current_set_games': [5, 2], 'sets_won_synthetic': True, 'point_score': ['15', '40']} b 0.732 0.268 33.8 feed
23:03:20 4 8 {'sets': [[6, 0], [6, 0], [0, 6]], 'current_set_games': [6, 2], 'sets_won_synthetic': True, 'point_score': ['9', '16']} b 1.000 0.000 0.0 feed
23:18:42 4 8 {'sets': [[6, 0], [6, 0], [0, 6]], 'current_set_games': [6, 2], 'sets_won_synthetic': True, 'point_score': ['9', '16']} b 1.000 0.000 0.0 feed
23:19:42 4 8 {'sets': [[6, 0], [6, 0], [0, 6]], 'current_set_games': [6, 2], 'sets_won_synthetic': True, 'point_score': ['9', '16']} b 1.000 0.000 0.0 feed

Showing last 30 of 200 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.