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Steve Christie
Tipster dossier — settled-bet performance through 2026-06-02 09:22 UTC
Verdict
STRUCTURALLY LOSING
Small sample (1 bets) — anything below ~100 settled bets means CIs are wide enough to be near-useless. Calibration is negative: actual win rate 0.0% trails market-implied 41.0% by -41.0pp — picks have negative skill relative to fair odds. Bayesian-shrunk ROI (regressed toward -13% population baseline by sample size) is -14.7% — a more honest expectation than the raw -100.0%.
Charts
Cumulative P/L (theoretical $1 stakes)
A straight upward line = consistent profitability. Step-jumps = single fortunate bets carrying the curve.
Monthly ROI %
Top 10 P/L outliers
ROI by odds bracket
Calibration — actual vs implied win rate by odds
Blue bars under orange = picks lose to market expectations.
ROI by day of week
At a glance
Total P/L ($1 stakes)
$-1.00
Bayesian-shrunk ROI
-14.7%
Implied Win % (1/odds)
41.0%
What's driving the ROI?
Strip away the top winning bets and see how the picture changes — a stable record degrades gracefully,
a lucky record collapses.
(insufficient data)
Recent trend
(insufficient sample to compare recent vs prior)
Monthly performance
| Month | N | Win % | Avg Odds | P/L | ROI |
|---|
| 2026-03 | 1 | 0.0% | 2.44 | $-1.00 | -100.0% |
By odds bracket
| Odds | N | Win % | P/L | ROI |
|---|
| 2.0-3.0 | 1 | 0.0% | $-1.00 | -100.0% |
By pre-race rank
No pre-race rank data yet for this tipster.
Strategy Zone (rank ≤ 3 AND odds ≥ 5)
No rank data yet.
By source
(no source data)
By venue
(no venue data with sufficient samples)
By day of week
(no day-of-week data)
Place market
No place outcomes captured yet for this tipster.
Biggest wins
| Date | Venue | Selection | Odds | P/L |
| No wins |
Biggest losses
| Date | Venue | Selection | Odds | P/L |
| 2026-03-04 | launceston | 3. Mastretta | 2.44 | $-1.00 |
Generated 2026-06-02 09:22 UTC. Stats based on theoretical $1 BACK stakes settled on Betfair. Place data uses captured Betfair Starting Price.
ROI = total P/L divided by total bets — high variance at small samples.