Guides on football data analytics, AI, xG and probability models. Data-driven analysis, not betting advice.
A football prediction is a confident claim about how a match will end; data-driven analysis is a statistical study that transparently shows probabilities, team form and model agreement. 11Stat belongs to the second group: we guarantee no outcome, we make data easier to read.
xG (Expected Goals) is a statistical metric that expresses the probability of a shot becoming a goal as a number between 0 and 1, revealing the quality of chances a team creates rather than just the final score.
AI cannot guarantee the outcome of a football match; a good model only estimates the probability of each result honestly. Reliability is not about knowing who wins, but about how closely a model's percentages match real-world frequencies over the long run, which is called calibration.
The honest answer is usually "both": the last 5 matches reveal a team's current momentum, while the last 10 reveal its true level. Instead of trusting a single window, 11Stat reads several at once, because a short window is fast but noisy, and a long window is calm but slow.
A football probability model never tells you who "will win" a match; it assigns each outcome a percentage. A good model offers not certainty but a measurable, testable estimate of uncertainty.
Sites like SofaScore and LiveScore show a match's raw data and statistics; 11Stat adds an analysis layer that turns that same data into a probability for every outcome, a model-agreement signal and a risk level. The first answers "what happened", the second asks "what does the data point to, and with what probability" — and neither is betting advice.
The over 2.5 goals probability is calculated by summing every cell of a Poisson-based score matrix where the two teams' goals add up to three or more; under 2.5 is simply the remaining six scorelines — 0-0, 1-0, 0-1, 1-1, 2-0 and 0-2. In major leagues that probability typically sits in a 40-60% band, which means neither side of the line is ever close to certain. This page walks through the full derivation chain, from xG to goal rates to the goal-line ladder. It is football data analytics, not betting advice.
Half-time / full-time analysis splits a football match into two phases — the first half and the second — and assigns a probability to each of the nine possible combinations of half-time leader and full-time result (1/1, X/1, 2/1 … 2/2). The nine scenarios always sum to 100%, and even the tallest cell — typically home-leads-and-wins — rarely clears 20-28% in a balanced match, while comeback cells like 1/2 and 2/1 usually sit at just 2-4%. This page explains how 11Stat derives the grid from per-phase goal expectancy, how lead transitions read as data, and where the distribution's limits lie. It is football data analytics, not betting advice.
For the Primera C fixture between Deportivo Español and Victoriano Arenas, the 11Stat model assigns Deportivo Español a 31% chance of winning, with the draw at 43% and Victoriano Arenas at 26%. The model's leading outcome is a draw, supported by 3 of 4 independent engines and a confidence score of 6.9 out of 10. These figures are calibrated probability estimates, not certainties — they describe how likely each result is, never a guaranteed outcome.
For the South Australia NPL fixture between West Torrens Birkalla and Para Hills Knights, the 11Stat model assigns West Torrens Birkalla a 90% chance of winning, with the draw at 8% and Para Hills Knights at 2%. The model's leading outcome is a West Torrens Birkalla win, supported by 3 of 4 independent engines and a confidence score of 6.7 out of 10. These figures are calibrated probability estimates, not certainties — they describe how likely each result is, never a guaranteed outcome.
For the Serie B fixture between Juventude and Cuiaba, the 11Stat model assigns Juventude a 64% chance of winning, with the draw at 26% and Cuiaba at 10%. The model's leading outcome is a Juventude win, supported by 3 of 4 independent engines and a confidence score of 6.6 out of 10. These figures are calibrated probability estimates, not certainties — they describe how likely each result is, never a guaranteed outcome.
For the Primera C fixture between Mercedes and El Porvenir, the 11Stat model assigns Mercedes a 37% chance of winning, with the draw at 44% and El Porvenir at 19%. The model's leading outcome is a draw, supported by 3 of 4 independent engines and a confidence score of 6.9 out of 10. These figures are calibrated probability estimates, not certainties — they describe how likely each result is, never a guaranteed outcome.
For the Primera B Metropolitana fixture between UAI Urquiza and Comunicaciones, the 11Stat model assigns UAI Urquiza a 23% chance of winning, with the draw at 43% and Comunicaciones at 35%. The model's leading outcome is a draw, supported by 3 of 4 independent engines and a confidence score of 6.7 out of 10. These figures are calibrated probability estimates, not certainties — they describe how likely each result is, never a guaranteed outcome.
For the Primera B Metropolitana fixture between San Martín Burzaco and Sportivo Italiano, the 11Stat model assigns San Martín Burzaco a 22% chance of winning, with the draw at 39% and Sportivo Italiano at 39%. The model's leading outcome is an Sportivo Italiano win, supported by 3 of 4 independent engines and a confidence score of 6.5 out of 10. These figures are calibrated probability estimates, not certainties — they describe how likely each result is, never a guaranteed outcome.
For the Segunda División fixture between Miramar and La Luz, the 11Stat model assigns Miramar a 43% chance of winning, with the draw at 37% and La Luz at 21%. The model's leading outcome is a Miramar win, supported by 3 of 4 independent engines and a confidence score of 6.5 out of 10. These figures are calibrated probability estimates, not certainties — they describe how likely each result is, never a guaranteed outcome.
For the Segunda División fixture between Tacuarembo and Plaza Colonia, the 11Stat model assigns Tacuarembo a 41% chance of winning, with the draw at 36% and Plaza Colonia at 23%. The model's leading outcome is a Tacuarembo win, supported by 3 of 4 independent engines and a confidence score of 6.4 out of 10. These figures are calibrated probability estimates, not certainties — they describe how likely each result is, never a guaranteed outcome.
For the Primera B fixture between Antofagasta and Rangers de Talca, the 11Stat model assigns Antofagasta a 71% chance of winning, with the draw at 22% and Rangers de Talca at 7%. The model's leading outcome is a Antofagasta win, supported by 3 of 4 independent engines and a confidence score of 6.8 out of 10. These figures are calibrated probability estimates, not certainties — they describe how likely each result is, never a guaranteed outcome.
For the Meistriliiga fixture between FC Levadia Tallinn and Tammeka, the 11Stat model assigns FC Levadia Tallinn a 72% chance of winning, with the draw at 20% and Tammeka at 8%. The model's leading outcome is a FC Levadia Tallinn win, supported by 3 of 4 independent engines and a confidence score of 6.7 out of 10. These figures are calibrated probability estimates, not certainties — they describe how likely each result is, never a guaranteed outcome.
For the Primera División - Apertura fixture between Cerro and Racing Montevideo, the 11Stat model assigns Cerro a 21% chance of winning, with the draw at 40% and Racing Montevideo at 39%. The model's leading outcome is a draw, supported by 3 of 4 independent engines and a confidence score of 6.6 out of 10. These figures are calibrated probability estimates, not certainties — they describe how likely each result is, never a guaranteed outcome.
For the Primera C fixture between Deportivo Paraguayo and Central Ballester, the 11Stat model assigns Deportivo Paraguayo a 29% chance of winning, with the draw at 41% and Central Ballester at 30%. The model's leading outcome is a draw, supported by 3 of 4 independent engines and a confidence score of 6.7 out of 10. These figures are calibrated probability estimates, not certainties — they describe how likely each result is, never a guaranteed outcome.
For the Primera Nacional fixture between Patronato and Atlanta, the 11Stat model assigns Patronato a 26% chance of winning, with the draw at 42% and Atlanta at 32%. The model's leading outcome is a draw, supported by 3 of 4 independent engines and a confidence score of 6.7 out of 10. These figures are calibrated probability estimates, not certainties — they describe how likely each result is, never a guaranteed outcome.
For the Primera C fixture between Atletico Atlas and Sacachispas, the 11Stat model assigns Atletico Atlas a 29% chance of winning, with the draw at 41% and Sacachispas at 30%. The model's leading outcome is a draw, supported by 3 of 4 independent engines and a confidence score of 6.7 out of 10. These figures are calibrated probability estimates, not certainties — they describe how likely each result is, never a guaranteed outcome.
For the UEFA Champions League fixture between Vikingur Reykjavik and Hapoel Beer Sheva, the 11Stat model assigns Vikingur Reykjavik a 76% chance of winning, with the draw at 16% and Hapoel Beer Sheva at 8%. The model's leading outcome is a Vikingur Reykjavik win, supported by 3 of 4 independent engines and a confidence score of 6.6 out of 10. These figures are calibrated probability estimates, not certainties — they describe how likely each result is, never a guaranteed outcome.
For the UEFA Europa Conference League fixture between IFK Goteborg and FC Levadia Tallinn, the 11Stat model assigns IFK Goteborg a 8% chance of winning, with the draw at 17% and FC Levadia Tallinn at 75%. The model's leading outcome is an FC Levadia Tallinn win, supported by 3 of 4 independent engines and a confidence score of 6.6 out of 10. These figures are calibrated probability estimates, not certainties — they describe how likely each result is, never a guaranteed outcome.
For the UEFA Champions League fixture between Mjallby AIF and Lincoln Red Imps FC, the 11Stat model assigns Mjallby AIF a 15% chance of winning, with the draw at 25% and Lincoln Red Imps FC at 60%. The model's leading outcome is an Lincoln Red Imps FC win, supported by 3 of 4 independent engines and a confidence score of 6.1 out of 10. These figures are calibrated probability estimates, not certainties — they describe how likely each result is, never a guaranteed outcome.
For the Serie A fixture between Coritiba and Palmeiras, the 11Stat model assigns Coritiba a 14% chance of winning, with the draw at 25% and Palmeiras at 61%. The model's leading outcome is an Palmeiras win, supported by 3 of 4 independent engines and a confidence score of 6.1 out of 10. These figures are calibrated probability estimates, not certainties — they describe how likely each result is, never a guaranteed outcome.
For the UEFA Europa Conference League fixture between Vardar Skopje and Riga, the 11Stat model assigns Vardar Skopje a 10% chance of winning, with the draw at 22% and Riga at 67%. The model's leading outcome is an Riga win, supported by 3 of 4 independent engines and a confidence score of 6.4 out of 10. These figures are calibrated probability estimates, not certainties — they describe how likely each result is, never a guaranteed outcome.
For the UEFA Europa Conference League fixture between Bohemians and Ballkani, the 11Stat model assigns Bohemians a 62% chance of winning, with the draw at 25% and Ballkani at 14%. The model's leading outcome is a Bohemians win, supported by 3 of 4 independent engines and a confidence score of 6.2 out of 10. These figures are calibrated probability estimates, not certainties — they describe how likely each result is, never a guaranteed outcome.
For the UEFA Europa League fixture between Beşiktaş and FC Midtjylland, the 11Stat model assigns Beşiktaş a 35% chance of winning, with the draw at 22% and FC Midtjylland at 44%. The model's leading outcome is an FC Midtjylland win, supported by 3 of 4 independent engines and a confidence score of 6.1 out of 10. These figures are calibrated probability estimates, not certainties — they describe how likely each result is, never a guaranteed outcome.
For the Serie A fixture between Botafogo and Vitoria, the 11Stat model assigns Botafogo a 50% chance of winning, with the draw at 23% and Vitoria at 27%. The model's leading outcome is a Botafogo win, supported by 3 of 4 independent engines and a confidence score of 5.9 out of 10. These figures are calibrated probability estimates, not certainties — they describe how likely each result is, never a guaranteed outcome.
For the UEFA Europa Conference League fixture between Bate Borisov and FC Sion, the 11Stat model assigns Bate Borisov a 7% chance of winning, with the draw at 17% and FC Sion at 76%. The model's leading outcome is an FC Sion win, supported by 3 of 4 independent engines and a confidence score of 6.6 out of 10. These figures are calibrated probability estimates, not certainties — they describe how likely each result is, never a guaranteed outcome.
For the UEFA Europa Conference League fixture between Universitatea Cluj and Brann, the 11Stat model assigns Universitatea Cluj a 14% chance of winning, with the draw at 21% and Brann at 64%. The model's leading outcome is an Brann win, supported by 3 of 4 independent engines and a confidence score of 6.1 out of 10. These figures are calibrated probability estimates, not certainties — they describe how likely each result is, never a guaranteed outcome.
For the Premier League fixture between CSKA Moscow and Baltika, the 11Stat model assigns CSKA Moscow a 9% chance of winning, with the draw at 17% and Baltika at 75%. The model's leading outcome is an Baltika win, supported by 3 of 4 independent engines and a confidence score of 6.5 out of 10. These figures are calibrated probability estimates, not certainties — they describe how likely each result is, never a guaranteed outcome.
For the Allsvenskan fixture between Vasteras SK FK and Orgryte IS, the 11Stat model assigns Vasteras SK FK a 82% chance of winning, with the draw at 13% and Orgryte IS at 6%. The model's leading outcome is a Vasteras SK FK win, supported by 3 of 4 independent engines and a confidence score of 6.7 out of 10. These figures are calibrated probability estimates, not certainties — they describe how likely each result is, never a guaranteed outcome.
For the Challenge League fixture between Rapperswil and FC WIL 1900, the 11Stat model assigns Rapperswil a 82% chance of winning, with the draw at 12% and FC WIL 1900 at 7%. The model's leading outcome is a Rapperswil win, supported by 3 of 4 independent engines and a confidence score of 6.6 out of 10. These figures are calibrated probability estimates, not certainties — they describe how likely each result is, never a guaranteed outcome.
For the Serie A fixture between Santos and Chapecoense-sc, the 11Stat model assigns Santos a 62% chance of winning, with the draw at 23% and Chapecoense-sc at 15%. The model's leading outcome is a Santos win, supported by 3 of 4 independent engines and a confidence score of 6.1 out of 10. These figures are calibrated probability estimates, not certainties — they describe how likely each result is, never a guaranteed outcome.
For the 1. Division fixture between Stromsgodset and Lyn, the 11Stat model assigns Stromsgodset a 81% chance of winning, with the draw at 14% and Lyn at 6%. The model's leading outcome is a Stromsgodset win, supported by 3 of 4 independent engines and a confidence score of 6.7 out of 10. These figures are calibrated probability estimates, not certainties — they describe how likely each result is, never a guaranteed outcome.
For the 1. Division fixture between Niva and Ostrovets FC, the 11Stat model assigns Niva a 75% chance of winning, with the draw at 17% and Ostrovets FC at 8%. The model's leading outcome is a Niva win, supported by 3 of 4 independent engines and a confidence score of 6.5 out of 10. These figures are calibrated probability estimates, not certainties — they describe how likely each result is, never a guaranteed outcome.
For the Serie A fixture between RB Bragantino and Coritiba, the 11Stat model assigns RB Bragantino a 73% chance of winning, with the draw at 19% and Coritiba at 8%. The model's leading outcome is a RB Bragantino win, supported by 3 of 4 independent engines and a confidence score of 6.6 out of 10. These figures are calibrated probability estimates, not certainties — they describe how likely each result is, never a guaranteed outcome.
For the Serie A fixture between Flamengo and Sao Paulo, the 11Stat model assigns Flamengo a 68% chance of winning, with the draw at 23% and Sao Paulo at 10%. The model's leading outcome is a Flamengo win, supported by 3 of 4 independent engines and a confidence score of 6.4 out of 10. These figures are calibrated probability estimates, not certainties — they describe how likely each result is, never a guaranteed outcome.
For the Allsvenskan fixture between Gais and Halmstad, the 11Stat model assigns Gais a 80% chance of winning, with the draw at 16% and Halmstad at 5%. The model's leading outcome is a Gais win, supported by 3 of 4 independent engines and a confidence score of 6.8 out of 10. These figures are calibrated probability estimates, not certainties — they describe how likely each result is, never a guaranteed outcome.
For the Primera Nacional fixture between Atlanta and Almagro, the 11Stat model assigns Atlanta a 73% chance of winning, with the draw at 20% and Almagro at 7%. The model's leading outcome is a Atlanta win, supported by 3 of 4 independent engines and a confidence score of 6.6 out of 10. These figures are calibrated probability estimates, not certainties — they describe how likely each result is, never a guaranteed outcome.
For the Úrvalsdeild fixture between KA Akureyri and Thor Akureyri, the 11Stat model assigns KA Akureyri a 79% chance of winning, with the draw at 14% and Thor Akureyri at 7%. The model's leading outcome is a KA Akureyri win, supported by 3 of 4 independent engines and a confidence score of 6.6 out of 10. These figures are calibrated probability estimates, not certainties — they describe how likely each result is, never a guaranteed outcome.
For the Virsliga fixture between Tukums and Rīgas FS, the 11Stat model assigns Tukums a 8% chance of winning, with the draw at 18% and Rīgas FS at 75%. The model's leading outcome is an Rīgas FS win, supported by 3 of 4 independent engines and a confidence score of 6.5 out of 10. These figures are calibrated probability estimates, not certainties — they describe how likely each result is, never a guaranteed outcome.
For the Premier League fixture between Al Nejmeh and Al Ahed, the 11Stat model assigns Al Nejmeh a 79% chance of winning, with the draw at 16% and Al Ahed at 5%. The model's leading outcome is a Al Nejmeh win, supported by 3 of 4 independent engines and a confidence score of 6.8 out of 10. These figures are calibrated probability estimates, not certainties — they describe how likely each result is, never a guaranteed outcome.
For the UEFA Europa Conference League fixture between Riga and Vardar Skopje, the 11Stat model assigns Riga a 78% chance of winning, with the draw at 16% and Vardar Skopje at 7%. The model's leading outcome is a Riga win, supported by 3 of 4 independent engines and a confidence score of 6.7 out of 10. These figures are calibrated probability estimates, not certainties — they describe how likely each result is, never a guaranteed outcome.
For the Premier League fixture between Paro and Thimphu, the 11Stat model assigns Paro a 76% chance of winning, with the draw at 16% and Thimphu at 9%. The model's leading outcome is a Paro win, supported by 3 of 4 independent engines and a confidence score of 6.5 out of 10. These figures are calibrated probability estimates, not certainties — they describe how likely each result is, never a guaranteed outcome.
For the UEFA Europa Conference League fixture between Apollon Limassol and Dila, the 11Stat model assigns Apollon Limassol a 56% chance of winning, with the draw at 29% and Dila at 15%. The model's leading outcome is a Apollon Limassol win, supported by 3 of 4 independent engines and a confidence score of 6.0 out of 10. These figures are calibrated probability estimates, not certainties — they describe how likely each result is, never a guaranteed outcome.
For the UEFA Champions League fixture between KuPS and Sabah FA, the 11Stat model assigns KuPS a 61% chance of winning, with the draw at 22% and Sabah FA at 16%. The model's leading outcome is a KuPS win, supported by 3 of 4 independent engines and a confidence score of 6.0 out of 10. These figures are calibrated probability estimates, not certainties — they describe how likely each result is, never a guaranteed outcome.
For the Serie A fixture between Chapecoense-sc and Vasco DA Gama, the 11Stat model assigns Chapecoense-sc a 39% chance of winning, with the draw at 25% and Vasco DA Gama at 36%. The model's leading outcome is a Chapecoense-sc win, supported by 3 of 4 independent engines and a confidence score of 5.8 out of 10. These figures are calibrated probability estimates, not certainties — they describe how likely each result is, never a guaranteed outcome.
For the UEFA Champions League fixture between Hapoel Beer Sheva and Vikingur Reykjavik, the 11Stat model assigns Hapoel Beer Sheva a 10% chance of winning, with the draw at 16% and Vikingur Reykjavik at 74%. The model's leading outcome is an Vikingur Reykjavik win, supported by 3 of 4 independent engines and a confidence score of 6.5 out of 10. These figures are calibrated probability estimates, not certainties — they describe how likely each result is, never a guaranteed outcome.
For the UEFA Europa Conference League fixture between FC Copenhagen and Polessya, the 11Stat model assigns FC Copenhagen a 31% chance of winning, with the draw at 18% and Polessya at 51%. The model's leading outcome is an Polessya win, supported by 3 of 4 independent engines and a confidence score of 6.3 out of 10. These figures are calibrated probability estimates, not certainties — they describe how likely each result is, never a guaranteed outcome.
For the UEFA Champions League fixture between Slovan Bratislava and Saburtalo, the 11Stat model assigns Slovan Bratislava a 65% chance of winning, with the draw at 19% and Saburtalo at 16%. The model's leading outcome is a Slovan Bratislava win, supported by 3 of 4 independent engines and a confidence score of 6.1 out of 10. These figures are calibrated probability estimates, not certainties — they describe how likely each result is, never a guaranteed outcome.
For the UEFA Europa League fixture between PAOK and Dynamo Kyiv, the 11Stat model assigns PAOK a 40% chance of winning, with the draw at 19% and Dynamo Kyiv at 41%. The model's leading outcome is an Dynamo Kyiv win, supported by 3 of 4 independent engines and a confidence score of 6.3 out of 10. These figures are calibrated probability estimates, not certainties — they describe how likely each result is, never a guaranteed outcome.
For the UEFA Europa League fixture between FC Midtjylland and Beşiktaş, the 11Stat model assigns FC Midtjylland a 64% chance of winning, with the draw at 22% and Beşiktaş at 14%. The model's leading outcome is a FC Midtjylland win, supported by 3 of 4 independent engines and a confidence score of 6.2 out of 10. These figures are calibrated probability estimates, not certainties — they describe how likely each result is, never a guaranteed outcome.
For the UEFA Europa League fixture between Pafos and HNK Hajduk Split, the 11Stat model assigns Pafos a 14% chance of winning, with the draw at 26% and HNK Hajduk Split at 60%. The model's leading outcome is an HNK Hajduk Split win, supported by 3 of 4 independent engines and a confidence score of 6.1 out of 10. These figures are calibrated probability estimates, not certainties — they describe how likely each result is, never a guaranteed outcome.
For the Eliteserien fixture between Bodo/Glimt and Lillestrom, the 11Stat model assigns Bodo/Glimt a 80% chance of winning, with the draw at 16% and Lillestrom at 4%. The model's leading outcome is a Bodo/Glimt win, supported by 3 of 4 independent engines and a confidence score of 6.8 out of 10. These figures are calibrated probability estimates, not certainties — they describe how likely each result is, never a guaranteed outcome.
For the 2. Liga fixture between Floridsdorfer AC and SKN ST. Polten, the 11Stat model assigns Floridsdorfer AC a 9% chance of winning, with the draw at 13% and SKN ST. Polten at 78%. The model's leading outcome is an SKN ST. Polten win, supported by 3 of 4 independent engines and a confidence score of 6.5 out of 10. These figures are calibrated probability estimates, not certainties — they describe how likely each result is, never a guaranteed outcome.
For the 1. Division fixture between Orsha and Shakhter Soligorsk, the 11Stat model assigns Orsha a 9% chance of winning, with the draw at 15% and Shakhter Soligorsk at 76%. The model's leading outcome is an Shakhter Soligorsk win, supported by 3 of 4 independent engines and a confidence score of 6.4 out of 10. These figures are calibrated probability estimates, not certainties — they describe how likely each result is, never a guaranteed outcome.
For the I Liga fixture between Pogoń Siedlce and Nieciecza, the 11Stat model assigns Pogoń Siedlce a 7% chance of winning, with the draw at 14% and Nieciecza at 78%. The model's leading outcome is an Nieciecza win, supported by 3 of 4 independent engines and a confidence score of 6.6 out of 10. These figures are calibrated probability estimates, not certainties — they describe how likely each result is, never a guaranteed outcome.
For the Eliteserien fixture between Start and Viking, the 11Stat model assigns Start a 9% chance of winning, with the draw at 21% and Viking at 70%. The model's leading outcome is an Viking win, supported by 3 of 4 independent engines and a confidence score of 6.4 out of 10. These figures are calibrated probability estimates, not certainties — they describe how likely each result is, never a guaranteed outcome.
For the Primera Nacional fixture between Ferro Carril Oeste and Godoy Cruz, the 11Stat model assigns Ferro Carril Oeste a 61% chance of winning, with the draw at 30% and Godoy Cruz at 10%. The model's leading outcome is a Ferro Carril Oeste win, supported by 3 of 4 independent engines and a confidence score of 6.4 out of 10. These figures are calibrated probability estimates, not certainties — they describe how likely each result is, never a guaranteed outcome.