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Radar

Scan any mix of ice hockey markets and leagues for the strongest selections

New here? How to use the radar
Set how many picks and which leagues — everything else has a sensible default. Then read the Calibrated column, not Model: it is the probability after the model has been corrected by its own track record.
  • Rank by Signal (default) gives picks that actually say something. Most likely to land returns safer but more obvious selections.
  • Lift is the quickest read: 3.0× means three times likelier than that selection normally is in the league.
  • Fair odds is break-even. Only worth backing at a longer price.
  • Keep one pick per match on — two picks from the same game tend to win or lose together.
  • Set Look ahead to Today or This week for the day's or week's best, then use Back and Next below the table to move past the top ten.
Full guide →
55%
0 of 48 selected /
1 of 1 selected /
No picks match those filters. Lower the minimum confidence, widen the leagues, or untick “must beat the base rate”. If nothing at all appears, generate picks first:
./.venv/bin/python -m pipeline.picks_icehockey --calibrate --generate
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Radar

What this page is for

Fixtures lists everything; the radar picks. Every market on every priced fixture is scored, and the strongest selections are ranked and put in front of you, with the best of them in the carousel at the top.

How the ranking works

A selection rises when the model's probability is far enough from the price being offered to be worth acting on. That distance is the edge, and the ordering is by edge, not by confidence — a 78% pick with no edge ranks below a 34% pick with a large one. A high probability and a good bet are different things, and this page is sorted by the second.

Using the filters

Market, league and confidence narrow the list without changing the ranking inside it. Anything you add to the slip is carried to the Bet slip page, where the combined price is worked out.

Read this before trusting the order

The ranking is only as good as the model behind it. Check Calibration to see whether its probabilities mean what they say, and Track record to see how selections like these have actually landed. If the banner at the top of the page says the model does not beat its own baseline, this ordering is noise wearing a confident face.

Press esc to close Read the full guide