Alexander Zverev vs Alejandro Tabilo

hard atp grand_slam best of 5 tennis_atp_us_open · commence 2026-09-06 00:25:00+00:00 · completed winner: a

P(Alexander Zverev) = 1.000  |  P(Alejandro Tabilo) = 0.000
live composite (last tick)

BO5 — elevated retirement risk

Best-of-5 matches (ATP men's Slams) historically retire at a materially higher rate than best-of-3. Per-player retirement frequency over their last 30 matches:
Alexander Zverev: 0/30 (0.0%)
Alejandro Tabilo: 0/30 (0.0%)

Sharp anchor — Pinnacle pre-match

Pinnacle P(Alexander Zverev) 0.819
Pinnacle P(Alejandro Tabilo) 0.181
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 Alexander ZverevAlejandro Tabilo 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
Alexander Zverev all_court 196 0.865 9.9
Alejandro Tabilo big_server 52 0.798 8.5

Matchup adjustment: +0.00pp toward Alejandro Tabilo 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)

AdjustmentAlexander ZverevAlejandro TabiloNet
Match fatigue (14d load) -2.00pp (load 4.0) -2.00pp (load 4.0) +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

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(Alexander Zverev) P(Alejandro Tabilo) Exp games Source
04:54:10 3 5 {'sets': [[6, 0], [6, 0]], 'current_set_games': [3, 2], 'sets_won_synthetic': True, 'point_score': ['0', '0']} b 0.876 0.124 43.1 feed
04:54:41 3 5 {'sets': [[6, 0], [6, 0]], 'current_set_games': [3, 2], 'sets_won_synthetic': True, 'point_score': ['0', '0']} b 0.881 0.119 43.0 feed
04:55:12 3 5 {'sets': [[6, 0], [6, 0]], 'current_set_games': [3, 2], 'sets_won_synthetic': True, 'point_score': ['0', '15']} b 0.877 0.123 43.1 feed
04:55:42 3 5 {'sets': [[6, 0], [6, 0]], 'current_set_games': [3, 2], 'sets_won_synthetic': True, 'point_score': ['15', '15']} b 0.881 0.119 43.3 feed
04:56:12 3 5 {'sets': [[6, 0], [6, 0]], 'current_set_games': [3, 2], 'sets_won_synthetic': True, 'point_score': ['30', '15']} b 0.890 0.110 42.5 feed
04:56:43 3 5 {'sets': [[6, 0], [6, 0]], 'current_set_games': [3, 2], 'sets_won_synthetic': True, 'point_score': ['40', '15']} b 0.883 0.117 43.1 feed
04:57:14 3 5 {'sets': [[6, 0], [6, 0]], 'current_set_games': [3, 2], 'sets_won_synthetic': True, 'point_score': ['40', '30']} b 0.876 0.124 43.1 feed
04:57:44 3 5 {'sets': [[6, 0], [6, 0]], 'current_set_games': [3, 2], 'sets_won_synthetic': True, 'point_score': ['40', '40']} b 0.879 0.121 43.3 feed
04:58:15 3 5 {'sets': [[6, 0], [6, 0]], 'current_set_games': [3, 2], 'sets_won_synthetic': True, 'point_score': ['40', 'A']} b 0.877 0.123 43.0 feed
04:58:46 3 5 {'sets': [[6, 0], [6, 0]], 'current_set_games': [3, 2], 'sets_won_synthetic': True, 'point_score': ['40', '40']} b 0.886 0.114 43.1 feed
04:59:16 3 5 {'sets': [[6, 0], [6, 0]], 'current_set_games': [3, 2], 'sets_won_synthetic': True, 'point_score': ['40', 'A']} b 0.878 0.122 43.2 feed
04:59:47 3 5 {'sets': [[6, 0], [6, 0]], 'current_set_games': [3, 2], 'sets_won_synthetic': True, 'point_score': ['40', '40']} b 0.878 0.122 43.1 feed
05:00:17 3 5 {'sets': [[6, 0], [6, 0]], 'current_set_games': [3, 2], 'sets_won_synthetic': True, 'point_score': ['40', 'A']} b 0.870 0.130 43.4 feed
05:00:48 3 6 {'sets': [[6, 0], [6, 0]], 'current_set_games': [4, 2], 'sets_won_synthetic': True, 'point_score': ['0', '0']} b 0.898 0.102 43.2 feed
05:01:18 3 6 {'sets': [[6, 0], [6, 0]], 'current_set_games': [4, 2], 'sets_won_synthetic': True, 'point_score': ['0', '0']} b 0.873 0.127 43.5 feed
05:01:49 3 6 {'sets': [[6, 0], [6, 0]], 'current_set_games': [4, 2], 'sets_won_synthetic': True, 'point_score': ['0', '0']} b 0.895 0.105 42.9 feed
05:02:19 3 6 {'sets': [[6, 0], [6, 0]], 'current_set_games': [4, 2], 'sets_won_synthetic': True, 'point_score': ['0', '30']} b 0.889 0.111 42.9 feed
05:02:50 3 6 {'sets': [[6, 0], [6, 0]], 'current_set_games': [4, 2], 'sets_won_synthetic': True, 'point_score': ['0', '30']} b 0.903 0.097 42.8 feed
05:03:21 3 6 {'sets': [[6, 0], [6, 0]], 'current_set_games': [4, 2], 'sets_won_synthetic': True, 'point_score': ['0', '40']} b 0.890 0.110 43.2 feed
05:03:51 3 6 {'sets': [[6, 0], [6, 0]], 'current_set_games': [4, 2], 'sets_won_synthetic': True, 'point_score': ['0', '40']} b 0.896 0.104 43.2 feed
05:04:22 3 7 {'sets': [[6, 0], [6, 0]], 'current_set_games': [5, 2], 'sets_won_synthetic': True, 'point_score': ['0', '0']} b 0.924 0.076 41.8 feed
05:04:52 3 7 {'sets': [[6, 0], [6, 0]], 'current_set_games': [5, 2], 'sets_won_synthetic': True, 'point_score': ['0', '0']} b 0.933 0.067 41.7 feed
05:05:23 3 7 {'sets': [[6, 0], [6, 0]], 'current_set_games': [5, 2], 'sets_won_synthetic': True, 'point_score': ['0', '0']} b 0.934 0.066 41.7 feed
05:05:53 3 7 {'sets': [[6, 0], [6, 0]], 'current_set_games': [5, 2], 'sets_won_synthetic': True, 'point_score': ['0', '0']} b 0.924 0.076 41.9 feed
05:06:31 3 7 {'sets': [[6, 0], [6, 0]], 'current_set_games': [5, 2], 'sets_won_synthetic': True, 'point_score': ['15', '0']} b 0.920 0.080 42.1 feed
05:07:02 3 7 {'sets': [[6, 0], [6, 0]], 'current_set_games': [5, 2], 'sets_won_synthetic': True, 'point_score': ['15', '15']} b 0.930 0.070 41.9 feed
05:07:32 3 7 {'sets': [[6, 0], [6, 0]], 'current_set_games': [5, 2], 'sets_won_synthetic': True, 'point_score': ['15', '30']} b 0.939 0.061 41.8 feed
05:08:20 3 7 {'sets': [[6, 0], [6, 0]], 'current_set_games': [5, 2], 'sets_won_synthetic': True, 'point_score': ['15', '40']} b 0.940 0.060 41.9 feed
05:08:51 3 7 {'sets': [[6, 0], [6, 0]], 'current_set_games': [5, 2], 'sets_won_synthetic': True, 'point_score': ['30', '40']} b 0.931 0.069 42.0 feed
05:09:21 4 8 {'sets': [[6, 0], [6, 0], [6, 0]], 'current_set_games': [6, 2], 'sets_won_synthetic': True, 'point_score': ['10', '19']} 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.