PROPEDIA TENNIS
Basel · Vienna · Guangzhou Open · Tokyo
7 singles matches · 4 tournaments
Tour
Level
Venue
Event
BIGGEST MISMATCH
Diana Shnaider 82%
Diana Shnaider vs Mia Pohankova · Tokyo · Pan Pacific Open
COIN FLIP OF THE DAY
Vacherot 41% / 59%
vs Taylor Fritz · Basel · Swiss Indoors — the market will price this tighter than the Elo gap
TOTAL GAMES OVER WATCH
O22.5 · 60%
Valentin Vacherot vs Taylor Fritz — sim median 25 games, tiebreak 46%
MODEL ML RECORD
35-17
67% on 52 graded model ML picks · 60%+ picks: 26-11 · tracked since Oct 27
TODAYSaturday, October 31, 20267 matches
JiriLehecka #21 · Elo 1956No model
INDOOR HARDSemifinal12:00 ET · Basel
Jan-LennardStruff #— · Elo —No model
MATCH SIMNo sim — a player has no current Elo rating (see notes)
AlexanderZverev #2 · Elo 210765% · fair -187
INDOOR HARDSemifinal11:30 ET · Vienna
Alexde Minaur #10 · Elo 198235% · fair +187
MATCH SIMSim (10k): Zverev 65% · Median 25 games · O22.5 59% · TB 46%
VV
ValentinVacherot #31 · Elo 185841% · fair +145
INDOOR HARDFINAL7-6 6-3
TaylorFritz #13 · Elo 193559% · fair -145
RESULTVacherot won 7-6 6-3 · Model ✗ (59%) · Sim median 25 games vs 22 actual
DaniilMedvedev #5 · Elo 199532% · fair +209
INDOOR HARDFINAL4-6 6-7
CarlosAlcaraz #3 · Elo 215068% · fair -209
RESULTAlcaraz won 4-6 6-7 · Model ✓ (68%) · Sim median 25 games vs 23 actual
XS
XinranSun #— · Elo —No model
OUTDOOR HARDFINAL7-5 6-7 0-6
HarrietDart #115 · Elo 1647No model
RESULTDart won 7-5 6-7 0-6 · No model
KQ
KaitlinQuevedo #86 · Elo 173540% · fair +151
OUTDOOR HARDFINAL2-6 0-6
LilliTagger #53 · Elo 177660% · fair -151
RESULTTagger won 2-6 0-6 · Model ✓ (60%) · Sim median 24 games vs 14 actual
DianaShnaider #13 · Elo 197282% · fair -442
OUTDOOR HARDFINAL6-4 7-6
MiaPohankova #144 · Elo 169718% · fair +442
MP
RESULTShnaider won 6-4 7-6 · Model ✓ (82%) · Sim median 22 games vs 23 actual
TOMORROWSunday, November 1, 20260 matches
Order of play not published yet — this section fills in as the draw is set.

How the model works — formula ships with the board, like every Propedia section

Win % = Elo expectancy on a blended rating gap: gap = 0.7 × (surface Elo gap — the surface being played) + 0.3 × (overall Elo gap), P = 1 / (1 + 10^(−gap/400)). Elo ratings are Jeff Sackmann's published Tennis Abstract ratings (overall + Hard/Clay/Grass splits, updated weekly). The sim then converts that win % into a serve-point edge around the tour serve baseline (ATP 64.0% / WTA 56.5% of service points won), calibrates it through the exact point→game→set chain, and runs 10,000 Monte Carlo matches for total games, tiebreak and set-score distributions. Sim win % tracks the Elo win % within ~1 pt across the day's modelled matches — that's the calibration check.
Surface & form design: every stat splits by surface (Hard / Clay / Grass Elo shown in the Tape); recent form is computed on-surface and recency-weighted in the production build — a clay run does not inflate a grass number.
Known gaps, shown not hidden: A player with no current Tennis Abstract Elo carries no model % on their card. Charting stats (Match Charting Project, last 52 weeks) only exist for players with 5+ charted matches. Book lines are not in any free feed we hold — model % + fair odds only, exactly how UFC launched.
SURFACE WATCH
Off their best surface today — Elo drop in red
None today