Every morning this page refreshes with a new set of mathematical predictions covering the day's fixtures across football, basketball and tennis. The numbers are generated automatically from recent form, head-to-head records and scoring patterns, so by the time you open the page, the data is already there. Whether you follow the Premier League, the NBA or ATP Challenger events, you will find probability figures and score forecasts in one place.
Statistical analysis does not replace your own judgement, but it does give you a structured starting point. Instead of relying on gut feeling alone, you can see which outcomes a mathematical model considers most likely and decide how much weight to give those figures alongside whatever you already know about the teams or players involved.
What Is the Today Section?
This section lists every match that Forebet has processed for the current calendar day. The predictions are not written by a pundit - they come from a model that ingests historical results, current league positions, average goals scored and conceded, and several other variables, then converts that data into probability percentages and a most-likely scoreline.
Because sport changes quickly, the page updates throughout the day as team news and other late information filters through. A match you checked this morning may show slightly different probability figures by kick-off time, reflecting any adjustments the system has made. That live quality is one of the main reasons people return to the page every day rather than just once a week.
Football Predictions
Football accounts for the largest share of today's listings. On a typical day you will find matches from the English Premier League, La Liga, Serie A, the Bundesliga and Ligue 1, as well as African competitions including the Nigerian Professional Football League and CAF club fixtures. Cup rounds, youth tournaments and lower-division leagues also appear when the model has enough historical data to produce a stable estimate.
For each match the model displays the win probability for the home side, the draw probability and the win probability for the away side. Alongside those three figures you will see a predicted correct score, an over/under goals line and a Both Teams to Score indication. Expected goals, often abbreviated as xG, appear where the underlying data supports them. That figure estimates how many goals each side would score on average given the quality of chances the statistics suggest they will create, which is often more telling than raw results alone.
When reading a football prediction, pay attention to current form over a longer sample rather than just the last two or three games. A team sitting mid-table might have conceded heavily at home across the season even if they won last weekend, and the model weighs that broader picture accordingly. The full predictions archive lets you compare how the model has performed across past matchdays.
Basketball Predictions
Basketball adds a different analytical dimension. Scoring is higher and more frequent than in football, so the probability model works with points totals and spread estimates rather than single-goal margins. Forebet pulls in points per game, defensive ratings, pace of play and recent away or home records to calculate which team is more likely to win and by roughly how many points.
NBA fixtures dominate on most days, but EuroLeague, national leagues from Spain, Turkey, France and other markets also appear. Because basketball schedules are dense - teams sometimes play three times in four days - fatigue and rotation patterns carry real weight in the model. A team on the second night of a back-to-back away from home will show that in its adjusted probability figures.
Tennis Predictions
Tennis predictions on this page cover ATP Tour, WTA Tour, ATP Challenger and ITF events. The model evaluates surface preference, recent match wins and losses, head-to-head history between the two players, and service statistics where available. Hard-court specialists and clay-court specialists have meaningfully different expected performances against the same opponent depending on the venue, and the model reflects that.
One practical detail: tennis results can shift sharply when a player is carrying a minor injury that has not yet been reported publicly. The model cannot account for information that is not in the data feed, so always cross-check player news before placing any weight on a tight prediction. You can browse all sports covered on this site to see which disciplines have predictions available beyond the main three.
How the Mathematical Model Works
The model behind these forecasts is built on statistical inference rather than opinion. It processes a defined number of recent fixtures for each team or player, calculates weighted averages for attacking output and defensive solidity, and then runs a probability simulation across many scoreline combinations. The output is the set of percentages and the most-likely scoreline you see on screen.
Key inputs typically include results and goals from the last 10-15 matches, separate home and away performance records, head-to-head outcomes, average goals scored and conceded per game, and xG figures where the data supplier provides them. League strength is also factored in - a 2-0 win against a bottom-half side carries less weight than the same result against a top-four opponent. The model is not infallible, and upsets happen precisely because football and other sports involve human performance, which no algorithm fully captures.
Types of Predictions Explained
Each listing shows several prediction types, and knowing what each one represents helps you use the data sensibly.
- Match Winner (1X2): the probability of a home win, draw or away win, expressed as percentages that add to 100.
- Double Chance: combines two of the three 1X2 outcomes - for example, home win or draw - giving a higher probability at the cost of a lower potential return.
- Both Teams to Score: indicates whether the model expects both sides to get on the scoresheet, based on each team's recent attacking and defensive records.
- Over / Under Goals: the most common line is 2.5 total goals, though other thresholds appear depending on the match.
- Correct Score: the single scoreline the model considers most statistically likely. It will be correct less often than the match winner prediction, simply because there are many more possible scorelines than there are possible winners.
- Probability Indicators: colour-coded confidence bands that give a quick visual read on how strongly the model favours one outcome over the alternatives.
Browsing by League
When a full matchday is busy - say, a midweek round with fixtures across eight or nine leagues simultaneously - scrolling through every match in one list becomes unwieldy. The league filter lets you isolate just the competition you care about and compare all of its matches side by side. That makes it easier to spot patterns, such as a run of low-scoring games in one division or consistently high xG figures in another.
League-by-league browsing is also useful if you follow a specific club and want to see how their opponents earlier in the week performed, which can inform your read of the team's fatigue level before their next fixture. If you want to plan ahead, tomorrow's predictions are already available for matches where the model has sufficient data.
Reading Today's Predictions in Practice
Start with the probability percentages. A 68% probability of a home win means the model rates that outcome as clearly the most likely, but it also means there is still a meaningful chance it does not happen. No single figure should be read as a certainty. Look next at the correct score forecast - it often tells you something about the match dynamic the model expects, such as a tight low-scoring game versus an open high-scoring one, even when the exact scoreline does not materialise.
Form indicators show each team's results across their most recent matches, often coded by win, draw or loss. A team with four wins from five looks very different from a team with one win from five, even if their league positions are close. Combining the probability figure, the correct score estimate, the form bar and any xG data gives you a richer picture than any single number alone. The home page has a quick-start guide to the main display elements if any column is unclear.
Responsible Use of Predictions
These predictions are an analytical tool, not a guarantee of any outcome. Mathematical models are built on historical patterns, and sport regularly produces results that fall outside those patterns - injuries, red cards, weather conditions and simple human unpredictability all play a role. Treat the figures as one input in your own assessment, not as a definitive answer.
If you use these predictions to inform betting decisions, set a clear limit on what you are prepared to spend and stick to it regardless of how confident any single forecast looks. Chasing losses after an unexpected result is one of the most common ways recreational bettors run into difficulty. 18+ only. Please gamble responsibly.
FAQ
The predictions refresh automatically each morning based on the latest available data. Some matches also receive a mid-day update if significant team news arrives, such as an injury or a lineup change, before kick-off.
Correct score predictions are harder to get right than match-winner forecasts because there are many possible scorelines for any game. The model shows the most probable scoreline, but it works best as a guide to the likely match pattern rather than an exact result.
On most days you will find coverage of the major European leagues, African competitions including CAF events and the Nigerian Professional Football League, as well as cup rounds and selected lower-division fixtures where the model has enough historical data to produce a meaningful forecast.
It is the model's estimate of how likely a given outcome is based on current form, head-to-head records and scoring averages. A 70% probability means the model expects that outcome to happen roughly seven times out of ten across a large number of similar matches, not that it will definitely occur today.
Yes. Forecasts for upcoming fixtures are published as soon as the model has processed sufficient data, usually at least 24 hours in advance. You can find them on the tomorrow's predictions page.
Expected goals, or xG, measures the quality of scoring chances a team creates or concedes based on factors like shot location and assist type. It often predicts future performance better than raw goals because it strips out luck from individual matches. A team with consistently high xG but few actual goals is often due a run of better results.