Browse today's football predictions, match odds, confidence ratings, and key stats across major leagues.
Save fixtures with the ☆ star and view them later on
My Selection.
Houston Dynamo FC IISt. Louis City II11/07/2026 23:00
1.85
3.30
3.30
175%
–
Un3.5
?-?
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Editorial & Statistical Review:
All match analysis is reviewed by the Supatips Football Analytics Team, led by
Ade Ola.
Predictions represent statistical probabilities, not guaranteed outcomes. 18+ only — please gamble responsibly.
Ade has spent years building statistical models for football matches, with a focus on
probability-led analysis over gut-feel tipster culture. He reviews every page on Supatips
before publication and writes the methodology guides.
Read full bio →
How Supatips Works
Every day, Supatips pulls fixture data across 100+ leagues and runs each match through a
probability model that considers recent form, home and away records, attacking and defensive
output, and bookmaker pricing signals. The result is a 1X2 probability split — home win,
draw, away win — alongside a confidence rating and a goals-market view.
The table above shows today's 265 fixtures. Each row displays the
odds, the model's preferred outcome, and a confidence percentage. Finished matches show a
✓ or ✗ marker so you can see how the picks held up.
So far today, 94 of 175 settled predictions
have been correct — a 54% rate on finished matches.
A higher confidence percentage means the model leans more strongly toward one outcome,
not that the result is certain. Use the figures as a guide, not a guarantee.
What the Numbers Actually Mean
The odds column shows the market price for home win (1), draw (X), and away win (2).
The highlighted odds box is the one the model backs. Confidence runs from roughly 33%
(perfectly even three-way split) up to around 75%+ for very one-sided fixtures.
A match sitting at 40–45% confidence is genuinely close — the model has a preference
but not a strong one.
The goals column shows whether the model expects a high-scoring or tight game, useful for
readers interested in over/under markets. You can click through to dedicated markets —
Over 2.5 goals,
Both Teams to Score,
Correct Score — for a deeper view of each fixture.
How the Model Is Built
The core of the analysis is a Poisson-based probability model calibrated on attack and
defence strength for each team. It factors in home advantage, which historically adds
around 0.3–0.4 goals per game at most levels. Form weighting means recent results carry
more influence than older ones, and the model cross-checks its output against market
pricing to flag cases where there may be value on one side.
This is not a tipping service built on opinion. The page does not pick teams based on
reputation, support base, or hype. If a smaller side has the statistical edge in a given
match, that is what the model shows — and that transparency is the point.
Expected Goals (xG) and Fixture Context
Where xG data is available it feeds into the model's assessment of attacking quality —
a team creating 2.1 xG per game is genuinely dangerous, even if their recent scoreline
looks modest. Alongside this, fixture context matters: a team rotating heavily ahead of
a cup game reads differently to a full-strength side with nothing to manage.
Saving Matches and Building Your Own View
The ☆ star button next to each fixture lets you save it to
My Selection. Your saved fixtures are stored in
your browser so they persist across sessions. This is useful if you want to track a
handful of matches through the day without scrolling back through the full table.
Other Markets Worth Exploring
The 1X2 result market is only one way to look at a fixture. Supatips also covers a range
of other markets, each with its own analysis page:
Supatips is an analytical and informational service. The predictions here are
probability estimates — not financial advice, not tips from an insider, and
definitely not guarantees of any result.
Football is unpredictable by nature. A 70% confidence figure still means the model
is wrong roughly three times in ten. Over a long run, statistical models add
structure to decision-making — but no model eliminates uncertainty.
If you choose to use these predictions alongside betting, please keep the following in mind:
Only stake money you are genuinely comfortable losing.
Set a hard budget and treat it as a fixed entertainment cost — not an investment.
Never chase a loss. A bad run does not mean a correction is due.
Take breaks. If betting stops feeling enjoyable, step back.
These predictions are one input — your own judgement matters too.
Free support is available if gambling is causing concern:
🔞 18+ only. Check that sports betting is legal in your country before placing any wager.
Frequently Asked Questions
Are the predictions on Supatips free?
Yes — everything on this page is free. The full fixture table, odds, confidence ratings,
and goals-market data are all published without a paywall. Some additional content is
available for registered users.
How often is the page updated?
The fixture table refreshes throughout the day. Scores and result markers update as
matches finish, so the accuracy tracker at the top of the page reflects live data
rather than just predictions made before kick-off.
What does the confidence percentage mean?
It is the model's estimated probability for the predicted outcome — the highest of the
three 1X2 probabilities. A 58% confidence home win means the model puts a 58% chance
on that result, with the remaining 42% split between draw and away win. It is not a
certainty; it is a measure of how one-sided the model sees the fixture.
What does 180 Predictions and Stats refer to?
It describes the breadth of Supatips' match coverage — not just a single result tip
per game, but analysis across multiple angles: result, goals, BTTS, HT/FT, correct
score, and double chance. The idea is to give readers a fuller statistical picture
of each fixture rather than one number to bet on.
How do I save matches to My Selection?
Tap the ☆ star icon on any match row. Saved fixtures move to
My Selection, which stores your picks in
the browser so they are still there when you come back later.
Why does the model sometimes back the underdog?
The model does not factor in team reputation, shirt colour, or public opinion —
only statistical signals. If a smaller club has better recent form, a stronger
defensive record, and home advantage, the numbers may favour them over a bigger
name that is struggling for form. That is part of the point: the analysis tries
to be honest with the data rather than follow the crowd.
