Skip to content
betsetgo

BetSetGo — probability-first sports betting model with a transparent, graded track record

Live · paper-trading bankroll · quarter-Kelly stakes · Independent of any book
Total return · paper bankroll · 105 tennis picks · 32 days
-13.4%
Hit rate · 922 events
54.3%
Closing line value · 105 priced picks
-0.6%

These three figures cover the live published model only. Hit rate is 922 graded events; the return and CLV above it are a separate, smaller population — 105 tennis picks · 32 days, which is what the bot staked rather than everything it forecast. The much larger sample on the accuracy page also scores the walk-forward floor, which is the model without news or calibration. Two populations, not two answers.

A model that prices fixtures the way the books do, runs all day across every major league, and shows you where its number disagrees with theirs. Every bet is graded. Every prediction is shown. No hype.

Ticket record19.7% claimed · 24.2% landed+$2,809 at $100/ticket · 29W · 91L of 120 settled · 121dZero EV: priced at fair value
▸ Live · today
35calls
0right
0wrong
35pending
0.62Brier · football · 563 events · naive 0.67
Track record →
▸ AI ticket · today3 legs+7158.8% edgeauto-selected · spread heuristic · model probabilities

The model's combo for today. Quarter-Kelly stake on a $1,000 bankroll.

  1. 01
    tennis · Moneyline — Nadia Podoroska
    Iga Swiatek vs Nadia Podoroska
    +613.7%35.78
  2. 02
    tennis · Moneyline — Dane Sweeny
    Dane Sweeny vs Lorenzo Musetti
    +257.0%14.59
  3. 03
    tennis · Moneyline — Eva Lys
    Mirra Andreeva vs Eva Lys
    +210.1%8.30
The receipt · paper-trading bankroll, 193 snapshots
Max DD 39.6%

▸ Live edges

7 fixtures priced wrong this hour · scanning 15
LgFixturePickBest priceImpliedModelEdge
TENQinwen ZhengvYulia PutintsevaML away3.4429.1%34.9%+23.0%FOOToulouse FCvLille OSCBoth teams to sco…1.7656.8%58.6%+7.3%TENNaomi OsakavKaterina SiniakovaML away4.0424.8%39.6%+63.6%FOOToulouse FCvLille OSCML home4.0224.9%35.1%+45.7%FOOReal Betis BalompiévReal Madrid CFML home7.6913.0%32.8%+162.6%TENJakub MensikvJurij RodionovML away7.0314.2%30.7%+122.0%TENTaylor FritzvMattia BellucciML away7.6913.0%30.6%+142.7%
Calibration · ±19.8pts max bucket deviation across 922 eventsSee all on the Board →

Track it yourself. Save picks, watch the curve for thirty days. Decide.

Read methodologyCreate free account →
betsetgo · Independent · Affiliated with no sportsbook · 18+ · Built by nvision-data