TT Lossbeater/WTT Feeder Berlin Women Quals
WTT Feeder Berlin Women QualsMatch #12459869
Played Aug 19Finished
Ying Syuan Wu
Home
1.11
At publish
Lost last 2Form at publish
3–7Last 10Lost last 2
Final
0 – 3
Set by set
911711611––––
Lorena Morsch
Away
6.00
At publish
Won last 1Form at publish
4–6Last 10Won last 1
The read, and what happenedsealed at 11:03 and never touched — 54.0% is still 54.0%
Graded at full timeLorena Morsch to win
54.0%
54.0%
Sealed before the first serve and never touched. The record is only checkable because of that.
Read
Rightno pick shipped
«Right» is not «we won». No pick was shipped, so this is a read that turned out correct — not a call that won.
How it is goingYing Syuan Wu above · Lorena Morsch below
Set 1 · 9-11
Set 2 · 7-11
Set 3 · 6-11
Point 55 set 3, 6-11 — our read held Lorena Morsch at 54.0%
55 points played in total.
H2H Ying Syuan Wu 0–1 Lorena Morsch Ying Syuan Wu has won 0 of their 1 meetings.
The pickNo pick published
Sealed 11:03What took a side1 for · 1 against · 3 silent
SignalWhat it readSideVerdictWhy it voted that way
Market
1.11 (84%)
Wu
Wrong
no bar to clear — a priced side always votes
H2H
0-1 in 1
—
Too close
1 played, under the floor of 3
Form (L5)
Wu 40% vs Morsch 60%
Morsch
Correct
20pp gap, over the 15pp bar
Form (L10)
Wu 30% vs Morsch 40%
—
Too close
10pp gap, under the 15pp bar
Streak
Wu -2 · Morsch +1
—
Too close
neither holds a run of 3 on their own
Not whether we were right, but which read failed. One match proves nothing — the calibration is the aggregate of rows like these, and that aggregate does not exist yet.
This table lists the interface catalogue — the one you already see in ALIGN / CONFLICT. The engine weighs its own subset, and they are not the same set. It says so here instead of hiding it.
1 for, 3 silent — and still no pick. The gate cuts it all the same.
Signal confidence: 84% — Strong (leans Wu) · live re-read · sealed at 46% before the first serve
Decision Summary
Why this prediction
- Morsch form (60%) outperforms what odds imply (17%)
Market vs Signals
Market oddsWu 1.11 / Morsch 6.00
Signal prob.84% / 16%
Edge (Wu)+0.0pp
WTT Feeder Berlin Women Quals · #12459869
Wu1.11
30%won 3 of 10 · last 10
Lost last 2
oldest → newest30%takes the first set · 3 of 10
Morsch6.00
40%won 4 of 10 · last 10
oldest → newest
56%takes the first set · 5 of 9
Head to head
H2H window
The recordacross 1 meeting
HomeWu0wins
AwayMorsch1wins
Morsch leads 1–0.
First set to match win · in this matchup
Not enough first sets
Neither side has won the first set three times here, so there is no rate to publish.
Set by set, in this 1 meetingevery set carries its own n — a fifth set only exists when the match reaches one
S1
Only 1 match reached it — below the 3 needed to publish a rate
S2
Only 1 match reached it — below the 3 needed to publish a rate
S3
Only 1 match reached it — below the 3 needed to publish a rate
How that 1 finishedn = 1, below the 3 needed
3–0Straight, home0
3–1Four sets, home0
3–2Decider, home0
2–3Decider, away0
1–3Four sets, away0
0–3Straight, away1
This 1 meeting
MetricWuMorschW − MBasisWins01−1in 1 meetingFirst set01−1of 1Avg pointsper match22.033.0−11.0per matchSweeps01−13–0 or 0–3
Career, not this matchup
MetricWuMorschBasisWin rate · lifetime3 / 10 vs 4 / 1030%40%3 / 10 vs 4 / 10Avg sets wonper match1.01.6per match
Deep Dive by Market
Each market builds on the overview aboveForecast
History
Forecastthe model predicts this marketHistorythis is what the H2H did — no prediction
Match Winner
WuWu 1.11/Morsch 6.00
Read onlywould have missed
What we said
84.4%
Wu · sealed before the serve
What happened
0–3
Morsch won
Recent Results
H2H · no odds on record1
LAug 19 · 16:30Y. Wu—9760L. Morsch—1111113
Y. Wu10
LAug 20 · 09:15Y. Wu—4171191A. Brzyska—11197113LAug 6 · 04:45C. Huang3.001111113Y. Wu1.369670LJul 27 · 13:25Y. Wu2.2061240T. Chien1.601114113WJul 27 · 07:10S. Chen1.731311651Y. Wu2.0015511113WJul 26 · 12:40D. Otabayeva9.005230Y. Wu1.041111113LJul 21 · 09:40S. Law5.001211113Y. Wu1.1410990LMay 3 · 16:55E. Samara1.361211113Y. Wu3.0010970LMay 2 · 15:53M. Kuai1.011111113Y. Wu15.006440WMay 2 · 10:25Y. Wu6.501211118113Y. Shin1.10108131182LMay 2 · 08:49Y. Wu4.505611101N. Kim1.1711119123
L. Morsch10
LAug 26 · 09:20T. Ke2.101411113L. Morsch1.6712950LAug 21 · 08:00L. Morsch5.009440R. Mende1.141111113WAug 19 · 10:55A. Brzyska1.28791111102L. Morsch3.50111151123LMay 16 · 15:35N. Zheng—1113163L. Morsch—811140LMay 15 · 11:15L. Morsch—1251191I. Matos—14117113WMar 3 · 16:05J. Wong1.835490L. Morsch1.831111113WMar 2 · 16:05L. Morsch—11115113D. Kelly—861181LMar 2 · 10:45Y. Kaneyoshi1.011111113L. Morsch15.007680LNov 6 · 11:25L. Morsch1.44118761J. Wang2.6331111113LNov 5 · 16:00A. Pavlovic1.4421211113L. Morsch2.631110951
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