TENNIS · ITF_WOMEN · 10/28/2026
Kaat Coppez vs Sandra Samir
Sandra Samir · 79.8% model probability
Sports prediction track record
See what was recorded before the result was known. Every forecast is scored for accuracy, and for what 1 unit on it returned at the best price when it was published.
On the board now
1 game forecast todayFirst up 8:00 PM ET
| Time | Matchup | Mkt | Seg | Line | Best | Edge | Str | Band | |||
|---|---|---|---|---|---|---|---|---|---|---|---|
| Upcoming · 1 | |||||||||||
| 8:00 PM | MIL @ TB | ML | FG | — | -136BR | Model columns are in every plan — start a free trial to see them | |||||
Upcoming · 1
Recently settled
The latest settled 60-minute forecasts from each sport, graded on the final result, with the best sportsbook price when each was published. Wins and losses alike — the tally is the full record over the last 30 days, not just these games.
4016W · 2029L · last 30 days · 66% right
How often a frozen forecast named the winner, checkpoint by checkpoint. Accuracy only — no price and no units here; the units record prices each forecast separately.
last 30 days
24 hours out
57.5%
1197 of 2081 graded
60 minutes out
66.9%
4322 of 6465 graded
In play
80.1%
4266 of 5327 graded
An in-play forecast is taken after the game has started and already reflects the score, so it is not comparable to the ones published before it. A hit rate is not a return either: a correct forecast at a short price can still lose money over a season.
Loading record filters…
Published winner forecasts, scored separately at each checkpoint. Periods follow game or tournament start dates. Golf has its own tournament cohorts.
Forecast record
3,309–1,366
70.8% over 4,675 graded
Forecast accuracy
70.8%
Correct
3,309
Incorrect
1,366
Graded
4,675
Pending
102
Ties: 0
Voids: 0
Ungraded: 283
Recorded missing forecasts: 563
A recorded missing forecast is a game we did not price at that checkpoint. We never generate one after the fact, so the gap is published rather than filled.
As of 10/28/2026, 3:34:56 AM Eastern. Metrics and rows come from the same report snapshot.
60-minute pregame · 70.8% · 3309 correct / 1366 incorrect
24-hour early · 65.2% · 215 correct / 115 incorrect
Live in-game (after set 1) · 84.7% · 3525 correct / 636 incorrect
The complete cohort
TENNIS · ITF_WOMEN · 10/28/2026
Sandra Samir · 79.8% model probability
TENNIS · ITF_WOMEN · 10/28/2026
Kamilla Bartone · 96.6% model probability
TENNIS · ITF_WOMEN · 10/28/2026
Katarina Kuzmova · 97.0% model probability
TENNIS · ITF_MEN · 10/28/2026
Thando Longwe-Smit · 58.2% model probability
TENNIS · ITF_MEN · 10/28/2026
Amr Elsayed · 82.0% model probability
TENNIS · ITF_WOMEN · 10/28/2026
Nastasja Mariana Schunk · 70.4% model probability
TENNIS · ITF_MEN · 10/28/2026
Nikita Mashtakov · 81.2% model probability
TENNIS · ITF_MEN · 10/28/2026
Chirag Duhan · 73.6% model probability
TENNIS · ITF_MEN · 10/28/2026
Alexander Chang · 51.8% model probability
TENNIS · ITF_MEN · 10/28/2026
Matyas Kozlovsky · 60.8% model probability
TENNIS · ITF_MEN · 10/28/2026
Dan Brand · 52.1% model probability
TENNIS · ITF_WOMEN · 10/28/2026
Ekaterina Yashina · 75.5% model probability
TENNIS · ITF_MEN · 10/28/2026
Maksim Shin · 91.6% model probability
TENNIS · WTA · 10/28/2026
Paula Badosa Gibert · 70.6% model probability
TENNIS · ITF_WOMEN · 10/28/2026
Karla Popovic · 91.5% model probability
TENNIS · ITF_WOMEN · 10/28/2026
Kristina Dmitruk · 99.4% model probability
TENNIS · ITF_WOMEN · 10/28/2026
Selina Atay · 75.3% model probability
TENNIS · ITF_MEN · 10/28/2026
Kousuke Ogura · 73.0% model probability
TENNIS · ITF_MEN · 10/28/2026
Stefan Storch · 53.2% model probability
TENNIS · ITF_MEN · 10/28/2026
Cooper Kose · 63.4% model probability
tennis-prematch-ml-v1 · tennis-freeze-v1 · 3787 graded · 2696 correct · 1091 incorrect · 71.2%
tennis-elo-surface-v2 · tennis-freeze-v1 · 888 graded · 613 correct · 275 incorrect · 69.0%