Mirra Andreeva vs Anastasia Potapova

hard wta grand_slam best of 3 tennis_wta_us_open · commence 2026-09-07 15:00:00+00:00 · completed winner: a

P(Mirra Andreeva) = 1.000 | P(Anastasia Potapova) = 0.000

live composite (last tick)

Sharp anchor — Pinnacle pre-match

Pinnacle P(Mirra Andreeva)	0.823
Pinnacle P(Anastasia Potapova)	0.177
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	Mirra Andreeva	Anastasia Potapova	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
Mirra Andreeva	aggressive_baseliner	37	0.692	2.6
Anastasia Potapova	all_court	119	0.618	2.1

Matchup adjustment: +0.00pp toward Anastasia Potapova 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)

Adjustment	Mirra Andreeva	Anastasia Potapova	Net
Match fatigue (14d load)	-1.50pp (load 3.0)	-1.50pp (load 3.0)	+0.00pp

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

Signal	Weight
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(Mirra Andreeva)	P(Anastasia Potapova)	Exp games	Source
17:21:47	3	7	{'sets': [[6, 0], [0, 6]], 'current_set_games': [4, 3], 'sets_won_synthetic': True, 'point_score': ['0', '0']}	b	0.504	0.496	37.7	feed
17:22:18	3	7	{'sets': [[6, 0], [0, 6]], 'current_set_games': [4, 3], 'sets_won_synthetic': True, 'point_score': ['0', '0']}	b	0.502	0.498	37.8	feed
17:22:55	3	7	{'sets': [[6, 0], [0, 6]], 'current_set_games': [4, 3], 'sets_won_synthetic': True, 'point_score': ['0', '0']}	b	0.495	0.504	37.7	feed
17:23:26	3	7	{'sets': [[6, 0], [0, 6]], 'current_set_games': [4, 3], 'sets_won_synthetic': True, 'point_score': ['0', '0']}	b	0.511	0.489	37.8	feed
17:23:57	3	7	{'sets': [[6, 0], [0, 6]], 'current_set_games': [4, 3], 'sets_won_synthetic': True, 'point_score': ['0', '15']}	b	0.483	0.516	37.8	feed
17:24:27	3	7	{'sets': [[6, 0], [0, 6]], 'current_set_games': [4, 3], 'sets_won_synthetic': True, 'point_score': ['0', '30']}	b	0.497	0.503	37.8	feed
17:24:58	3	7	{'sets': [[6, 0], [0, 6]], 'current_set_games': [4, 3], 'sets_won_synthetic': True, 'point_score': ['15', '30']}	b	0.505	0.495	37.8	feed
17:25:28	3	7	{'sets': [[6, 0], [0, 6]], 'current_set_games': [4, 3], 'sets_won_synthetic': True, 'point_score': ['15', '40']}	b	0.488	0.512	37.8	feed
17:25:59	3	7	{'sets': [[6, 0], [0, 6]], 'current_set_games': [4, 3], 'sets_won_synthetic': True, 'point_score': ['15', '40']}	b	0.506	0.494	37.9	feed
17:26:29	3	7	{'sets': [[6, 0], [0, 6]], 'current_set_games': [4, 3], 'sets_won_synthetic': True, 'point_score': ['30', '40']}	b	0.496	0.504	37.7	feed
17:27:00	3	8	{'sets': [[6, 0], [0, 6]], 'current_set_games': [5, 3], 'sets_won_synthetic': True, 'point_score': ['0', '0']}	b	0.566	0.434	38.7	feed
17:27:31	3	8	{'sets': [[6, 0], [0, 6]], 'current_set_games': [5, 3], 'sets_won_synthetic': True, 'point_score': ['0', '15']}	b	0.587	0.413	38.8	feed
17:28:01	3	8	{'sets': [[6, 0], [0, 6]], 'current_set_games': [5, 3], 'sets_won_synthetic': True, 'point_score': ['0', '15']}	b	0.580	0.420	38.8	feed
17:28:32	3	8	{'sets': [[6, 0], [0, 6]], 'current_set_games': [5, 3], 'sets_won_synthetic': True, 'point_score': ['0', '15']}	b	0.574	0.426	38.7	feed
17:29:02	3	8	{'sets': [[6, 0], [0, 6]], 'current_set_games': [5, 3], 'sets_won_synthetic': True, 'point_score': ['0', '15']}	b	0.571	0.429	38.8	feed
17:29:33	3	8	{'sets': [[6, 0], [0, 6]], 'current_set_games': [5, 3], 'sets_won_synthetic': True, 'point_score': ['0', '15']}	b	0.571	0.429	38.8	feed
17:30:03	3	8	{'sets': [[6, 0], [0, 6]], 'current_set_games': [5, 3], 'sets_won_synthetic': True, 'point_score': ['0', '15']}	b	0.569	0.431	38.8	feed
17:30:34	3	8	{'sets': [[6, 0], [0, 6]], 'current_set_games': [5, 3], 'sets_won_synthetic': True, 'point_score': ['0', '15']}	b	0.587	0.413	38.8	feed
17:31:04	3	8	{'sets': [[6, 0], [0, 6]], 'current_set_games': [5, 3], 'sets_won_synthetic': True, 'point_score': ['0', '15']}	b	0.558	0.442	38.8	feed
17:31:36	3	0	{'sets': [[6, 0], [0, 6]], 'current_set_games': [0, 0], 'sets_won_synthetic': True, 'point_score': ['0', '15']}	b	0.505	0.495	30.8	feed
17:32:06	3	0	{'sets': [[6, 0], [0, 6]], 'current_set_games': [0, 0], 'sets_won_synthetic': True, 'point_score': ['0', '15']}	b	0.501	0.499	30.8	feed
17:32:37	3	0	{'sets': [[6, 0], [0, 6]], 'current_set_games': [0, 0], 'sets_won_synthetic': True, 'point_score': ['0', '15']}	b	0.493	0.506	30.8	feed
17:33:07	3	0	{'sets': [[6, 0], [0, 6]], 'current_set_games': [0, 0], 'sets_won_synthetic': True, 'point_score': ['0', '15']}	b	0.506	0.494	30.8	feed
17:33:38	3	0	{'sets': [[6, 0], [0, 6]], 'current_set_games': [0, 0], 'sets_won_synthetic': True, 'point_score': ['0', '15']}	b	0.503	0.497	30.8	feed
17:34:08	3	0	{'sets': [[6, 0], [0, 6]], 'current_set_games': [0, 0], 'sets_won_synthetic': True, 'point_score': ['0', '15']}	b	0.504	0.496	30.8	feed
17:34:39	3	0	{'sets': [[6, 0], [0, 6]], 'current_set_games': [0, 0], 'sets_won_synthetic': True, 'point_score': ['0', '15']}	b	0.502	0.498	30.7	feed
17:35:09	3	0	{'sets': [[6, 0], [0, 6]], 'current_set_games': [0, 0], 'sets_won_synthetic': True, 'point_score': ['0', '15']}	b	0.504	0.496	30.8	feed
17:35:40	3	8	{'sets': [[6, 0], [0, 6]], 'current_set_games': [5, 3], 'sets_won_synthetic': True, 'point_score': ['0', '30']}	b	0.562	0.438	38.8	feed
17:36:11	3	8	{'sets': [[6, 0], [0, 6]], 'current_set_games': [5, 3], 'sets_won_synthetic': True, 'point_score': ['0', '40']}	b	0.579	0.421	38.8	feed
17:36:41	4	9	{'sets': [[6, 0], [6, 0], [0, 6]], 'current_set_games': [6, 3], 'sets_won_synthetic': True, 'point_score': ['14', '17']}	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.