Jessica Pegula vs Emma Navarro

hard wta grand_slam best of 3 tennis_wta_us_open · commence 2026-09-08 23:00:00+00:00 · completed winner: a

P(Jessica Pegula) = 1.000  |  P(Emma Navarro) = 0.000
live composite (last tick)

Sharp anchor — Pinnacle pre-match

Pinnacle P(Jessica Pegula) 0.777
Pinnacle P(Emma Navarro) 0.223
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 Jessica PegulaEmma Navarro 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
Jessica Pegula aggressive_baseliner 189 0.726 2.6
Emma Navarro aggressive_baseliner 62 0.662 1.3

Matchup adjustment: +0.00pp toward Emma Navarro 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)

AdjustmentJessica PegulaEmma NavarroNet
Match fatigue (14d load) -3.00pp (load 6.0) -2.15pp (load 4.3) -0.85pp

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(Jessica Pegula) P(Emma Navarro) Exp games Source
02:31:11 3 6 {'sets': [[6, 0], [0, 6]], 'current_set_games': [4, 2], 'sets_won_synthetic': True, 'point_score': ['0', '15']} b 0.587 0.413 34.8 feed
02:31:41 3 6 {'sets': [[6, 0], [0, 6]], 'current_set_games': [4, 2], 'sets_won_synthetic': True, 'point_score': ['0', '15']} b 0.571 0.429 34.8 feed
02:32:12 3 6 {'sets': [[6, 0], [0, 6]], 'current_set_games': [4, 2], 'sets_won_synthetic': True, 'point_score': ['0', '30']} b 0.579 0.421 34.8 feed
02:32:42 3 6 {'sets': [[6, 0], [0, 6]], 'current_set_games': [4, 2], 'sets_won_synthetic': True, 'point_score': ['15', '30']} b 0.554 0.446 34.8 feed
02:33:13 3 6 {'sets': [[6, 0], [0, 6]], 'current_set_games': [4, 2], 'sets_won_synthetic': True, 'point_score': ['15', '40']} b 0.589 0.411 34.8 feed
02:33:43 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 35.8 feed
02:34:14 3 7 {'sets': [[6, 0], [0, 6]], 'current_set_games': [5, 2], 'sets_won_synthetic': True, 'point_score': ['0', '0']} b 0.722 0.278 35.8 feed
02:34:44 3 7 {'sets': [[6, 0], [0, 6]], 'current_set_games': [5, 2], 'sets_won_synthetic': True, 'point_score': ['0', '0']} b 0.732 0.268 35.8 feed
02:35:15 3 7 {'sets': [[6, 0], [0, 6]], 'current_set_games': [5, 2], 'sets_won_synthetic': True, 'point_score': ['0', '0']} b 0.719 0.281 35.7 feed
02:35:45 3 7 {'sets': [[6, 0], [0, 6]], 'current_set_games': [5, 2], 'sets_won_synthetic': True, 'point_score': ['0', '15']} b 0.739 0.261 35.8 feed
02:36:16 3 7 {'sets': [[6, 0], [0, 6]], 'current_set_games': [5, 2], 'sets_won_synthetic': True, 'point_score': ['15', '15']} b 0.740 0.260 35.8 feed
02:36:47 3 7 {'sets': [[6, 0], [0, 6]], 'current_set_games': [5, 2], 'sets_won_synthetic': True, 'point_score': ['30', '15']} b 0.716 0.284 35.8 feed
02:37:17 3 7 {'sets': [[6, 0], [0, 6]], 'current_set_games': [5, 2], 'sets_won_synthetic': True, 'point_score': ['30', '30']} b 0.725 0.275 35.7 feed
02:37:48 3 7 {'sets': [[6, 0], [0, 6]], 'current_set_games': [5, 2], 'sets_won_synthetic': True, 'point_score': ['40', '30']} b 0.724 0.276 35.8 feed
02:38:19 3 8 {'sets': [[6, 0], [0, 6]], 'current_set_games': [5, 3], 'sets_won_synthetic': True, 'point_score': ['0', '0']} b 0.561 0.439 36.7 feed
02:38:49 3 8 {'sets': [[6, 0], [0, 6]], 'current_set_games': [5, 3], 'sets_won_synthetic': True, 'point_score': ['0', '15']} b 0.577 0.423 36.9 feed
02:39:20 3 8 {'sets': [[6, 0], [0, 6]], 'current_set_games': [5, 3], 'sets_won_synthetic': True, 'point_score': ['0', '15']} b 0.564 0.436 36.8 feed
02:39:50 3 8 {'sets': [[6, 0], [0, 6]], 'current_set_games': [5, 3], 'sets_won_synthetic': True, 'point_score': ['15', '30']} b 0.582 0.418 36.9 feed
02:40:21 3 8 {'sets': [[6, 0], [0, 6]], 'current_set_games': [5, 3], 'sets_won_synthetic': True, 'point_score': ['30', '30']} b 0.576 0.424 36.7 feed
02:40:51 3 8 {'sets': [[6, 0], [0, 6]], 'current_set_games': [5, 3], 'sets_won_synthetic': True, 'point_score': ['30', '30']} b 0.583 0.417 36.9 feed
02:41:22 3 8 {'sets': [[6, 0], [0, 6]], 'current_set_games': [5, 3], 'sets_won_synthetic': True, 'point_score': ['40', '40']} b 0.572 0.428 36.8 feed
02:41:53 3 8 {'sets': [[6, 0], [0, 6]], 'current_set_games': [5, 3], 'sets_won_synthetic': True, 'point_score': ['40', '40']} b 0.576 0.424 36.8 feed
02:42:23 3 8 {'sets': [[6, 0], [0, 6]], 'current_set_games': [5, 3], 'sets_won_synthetic': True, 'point_score': ['A', '40']} b 0.580 0.420 36.8 feed
02:42:54 3 8 {'sets': [[6, 0], [0, 6]], 'current_set_games': [5, 3], 'sets_won_synthetic': True, 'point_score': ['40', '40']} b 0.573 0.427 36.8 feed
02:43:24 3 8 {'sets': [[6, 0], [0, 6]], 'current_set_games': [5, 3], 'sets_won_synthetic': True, 'point_score': ['40', 'A']} b 0.559 0.441 36.8 feed
02:44:12 4 9 {'sets': [[6, 0], [6, 0], [0, 6]], 'current_set_games': [6, 3], 'sets_won_synthetic': True, 'point_score': ['13', '15']} b 1.000 0.000 0.0 feed
03:01:57 4 9 {'sets': [[6, 0], [6, 0], [0, 6]], 'current_set_games': [6, 3], 'sets_won_synthetic': True, 'point_score': ['13', '15']} b 1.000 0.000 0.0 feed
03:02:57 4 9 {'sets': [[6, 0], [6, 0], [0, 6]], 'current_set_games': [6, 3], 'sets_won_synthetic': True, 'point_score': ['13', '15']} b 1.000 0.000 0.0 feed
03:03:57 4 9 {'sets': [[6, 0], [6, 0], [0, 6]], 'current_set_games': [6, 3], 'sets_won_synthetic': True, 'point_score': ['13', '15']} b 1.000 0.000 0.0 feed
03:04:57 4 9 {'sets': [[6, 0], [6, 0], [0, 6]], 'current_set_games': [6, 3], 'sets_won_synthetic': True, 'point_score': ['13', '15']} 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.