Public evidence · not a backtest

Is the OddsPadi engine actually working?

This scorecard uses settled picks that were genuinely published. Internal runs, watchlists, demo predictions and unsettled outcomes do not improve the numbers.

01 · Engine Health

Is the daily system operating?

failed
Latest run7/14/2026, 5:05:47 AM
Fixtures analysed0
Decisions generated0
Public picks today0
Stale decisions0
Settlement backlog0

Provider sources: no provider response. Recorded provider gaps: 2.

02 · Public Pick Performance

What happened after publication?

Not enough dataaccuracy across 0 resolved win/loss picks
Settled picks0
Wins / losses0 / 0
Push / void0 / 0
One-unit ROINot available
Average oddsNot available
Average edgeNot available
Binary Brier scoreNot enough data
Simulated profit+0.00 units
03 · Calibration

Confidence versus reality

A small gap is better

Each rung compares the model's average published chance with the actual win rate. Empty buckets remain visible instead of borrowing evidence from another range.

40–50%0 predictions
Wins
0
Expected wins
0.0
Actual rate
Not enough data
Gap
Not available
50–55%0 predictions
Wins
0
Expected wins
0.0
Actual rate
Not enough data
Gap
Not available
55–60%0 predictions
Wins
0
Expected wins
0.0
Actual rate
Not enough data
Gap
Not available
60–65%0 predictions
Wins
0
Expected wins
0.0
Actual rate
Not enough data
Gap
Not available
65–70%0 predictions
Wins
0
Expected wins
0.0
Actual rate
Not enough data
Gap
Not available
70%+0 predictions
Wins
0
Expected wins
0.0
Actual rate
Not enough data
Gap
Not available
Model chance Actual win rate
04 · Sport Performance

By sport

Settled public-pick performance by sport
GroupSettledW–L–PAccuracyROIBrier
basketball0000Not enough dataNot availableNot enough data
football0000Not enough dataNot availableNot enough data
tennis0000Not enough dataNot availableNot enough data
League view

By league

No settled league sample

League rows will appear after public picks settle.

05 · Market Performance

Where the engine performs

Settled performance across canonical market families
GroupSettledW–L–PAccuracyROIBrier
1X20000Not enough dataNot availableNot enough data
BTTS0000Not enough dataNot availableNot enough data
Moneyline0000Not enough dataNot availableNot enough data
Over/Under0000Not enough dataNot availableNot enough data
Spread0000Not enough dataNot availableNot enough data
Tennis winner0000Not enough dataNot availableNot enough data
06 · Confidence

Low, medium and high

Performance by publication confidence
GroupSettledW–L–PAccuracyROIBrier
high0000Not enough dataNot availableNot enough data
low0000Not enough dataNot availableNot enough data
medium0000Not enough dataNot availableNot enough data
07 · Data Quality

Evidence quality bands

Performance by publication-time data quality
GroupSettledW–L–PAccuracyROIBrier
high0000Not enough dataNot availableNot enough data
low0000Not enough dataNot availableNot enough data
medium0000Not enough dataNot availableNot enough data
unscored0000Not enough dataNot availableNot enough data

Low is below 62%, medium is 62–80%, and high is 80%+. Older rows without retained scores remain unscored.

08 · Closing Line Value

Did the published price beat the close?

0 comparable

Closing odds are not available yet

Published prices remain visible. CLV will appear only after a verified pre-kickoff closing snapshot is stored; no closing price is inferred.

09 · Warnings

What could make these numbers misleading?

2
info

Too few settled picks for a strong conclusion

0 settled public picks are available. Treat accuracy, ROI and calibration as early evidence until at least 30 settle.

watch

Provider coverage has gaps

failed provider state with 2 recorded gaps. The engine does not substitute demo fixtures.

How these numbers are counted

Wins divided by wins plus losses. Pending, push and void results are excluded.

One unit per settled public pick; pushes return the unit and voids are excluded from stake.

Binary published-selection Brier score. Lower is better; pending, push and void results are excluded.

Always excluded
  • mock or demo predictions
  • internal model runs
  • watchlist-only candidates
  • non-positive-edge analyses
  • unsettled picks