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 UEFA Champions League fixture between Levski Sofia and Kairat Almaty, the 11Stat model assigns Levski Sofia a 61% chance of winning, with the draw at 23% and Kairat Almaty at 16%. The model's leading outcome is a Levski Sofia 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 Sparta Praha and Lyon, the 11Stat model assigns Sparta Praha a 64% chance of winning, with the draw at 19% and Lyon at 17%. The model's leading outcome is a Sparta Praha 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 Úrvalsdeild fixture between Thor Akureyri and Breidablik, the 11Stat model assigns Thor Akureyri a 12% chance of winning, with the draw at 16% and Breidablik at 72%. The model's leading outcome is an Breidablik 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 Conference League fixture between Brann and Apollon Limassol, the 11Stat model assigns Brann a 18% chance of winning, with the draw at 23% and Apollon Limassol at 60%. The model's leading outcome is an Apollon Limassol 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 Copa Do Brasil fixture between Cruzeiro and Chapecoense-sc, the 11Stat model assigns Cruzeiro a 57% chance of winning, with the draw at 26% and Chapecoense-sc at 16%. The model's leading outcome is a Cruzeiro 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 Ykkönen fixture between Tampere United and KPV-j, the 11Stat model assigns Tampere United a 77% chance of winning, with the draw at 17% and KPV-j at 6%. The model's leading outcome is a Tampere United 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 Capital Territory NPL fixture between Queanbeyan City and Tuggeranong United, the 11Stat model assigns Queanbeyan City a 55% chance of winning, with the draw at 20% and Tuggeranong United at 25%. The model's leading outcome is a Queanbeyan City 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 FC Thun and Vikingur Reykjavik, the 11Stat model assigns FC Thun a 44% chance of winning, with the draw at 22% and Vikingur Reykjavik at 34%. The model's leading outcome is a FC Thun 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 Jagiellonia and Rangers, the 11Stat model assigns Jagiellonia a 55% chance of winning, with the draw at 29% and Rangers at 17%. The model's leading outcome is a Jagiellonia 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 Europa League fixture between KuPS and Universitatea Craiova, the 11Stat model assigns KuPS a 50% chance of winning, with the draw at 23% and Universitatea Craiova at 28%. The model's leading outcome is a KuPS 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 2. Bundesliga fixture between VfL Bochum and Hertha BSC, the 11Stat model assigns VfL Bochum a 11% chance of winning, with the draw at 17% and Hertha BSC at 72%. The model's leading outcome is an Hertha BSC 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 Bundesliga fixture between SCR Altach and WSG Wattens, the 11Stat model assigns SCR Altach a 26% chance of winning, with the draw at 19% and WSG Wattens at 55%. The model's leading outcome is an WSG Wattens 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 Liga Profesional Argentina fixture between Rosario Central and Aldosivi, the 11Stat model assigns Rosario Central a 65% chance of winning, with the draw at 25% and Aldosivi at 10%. The model's leading outcome is a Rosario Central 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 Jupiler Pro League fixture between Club Brugge KV and Kortrijk, the 11Stat model assigns Club Brugge KV a 16% chance of winning, with the draw at 17% and Kortrijk at 67%. The model's leading outcome is an Kortrijk 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 Premier League fixture between The New Saints and Haverfordwest County AFC, the 11Stat model assigns The New Saints a 17% chance of winning, with the draw at 27% and Haverfordwest County AFC at 56%. The model's leading outcome is an Haverfordwest County AFC 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 2. Bundesliga fixture between SV Darmstadt 98 and Holstein Kiel, the 11Stat model assigns SV Darmstadt 98 a 70% chance of winning, with the draw at 18% and Holstein Kiel at 11%. The model's leading outcome is a SV Darmstadt 98 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 2. Bundesliga fixture between 1. FC Magdeburg and Eintracht Braunschweig, the 11Stat model assigns 1. FC Magdeburg a 47% chance of winning, with the draw at 23% and Eintracht Braunschweig at 30%. The model's leading outcome is a 1. FC Magdeburg 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 Primeira Liga fixture between Guimaraes and Arouca, the 11Stat model assigns Guimaraes a 70% chance of winning, with the draw at 23% and Arouca at 8%. The model's leading outcome is a Guimaraes 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 Palmeiras and Internacional, the 11Stat model assigns Palmeiras a 68% chance of winning, with the draw at 21% and Internacional at 12%. The model's leading outcome is a Palmeiras 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 Serie A fixture between Cruzeiro and Mirassol, the 11Stat model assigns Cruzeiro a 60% chance of winning, with the draw at 28% and Mirassol at 13%. The model's leading outcome is a Cruzeiro 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 Serie A fixture between RB Bragantino and Corinthians, the 11Stat model assigns RB Bragantino a 57% chance of winning, with the draw at 28% and Corinthians at 15%. The model's leading outcome is a RB Bragantino 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 Eerste Divisie fixture between Jong AZ and FC Eindhoven, the 11Stat model assigns Jong AZ a 78% chance of winning, with the draw at 16% and FC Eindhoven at 6%. The model's leading outcome is a Jong AZ 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 Sportivo Barracas and Claypole, the 11Stat model assigns Sportivo Barracas a 69% chance of winning, with the draw at 23% and Claypole at 8%. The model's leading outcome is a Sportivo Barracas 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 Primera C fixture between Sacachispas and Deportivo Paraguayo, the 11Stat model assigns Sacachispas a 53% chance of winning, with the draw at 38% and Deportivo Paraguayo at 9%. The model's leading outcome is a Sacachispas 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 Champions League fixture between FK Crvena Zvezda and Hapoel Beer Sheva, the 11Stat model assigns FK Crvena Zvezda a 71% chance of winning, with the draw at 18% and Hapoel Beer Sheva at 11%. The model's leading outcome is a FK Crvena Zvezda 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 Champions League fixture between Lyon and Sparta Praha, the 11Stat model assigns Lyon a 70% chance of winning, with the draw at 16% and Sparta Praha at 14%. The model's leading outcome is a Lyon 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 Champions League fixture between Slovan Bratislava and Mjallby AIF, the 11Stat model assigns Slovan Bratislava a 66% chance of winning, with the draw at 20% and Mjallby AIF at 14%. The model's leading outcome is a Slovan Bratislava 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 Conference League fixture between Rapid Vienna and Paide, the 11Stat model assigns Rapid Vienna a 66% chance of winning, with the draw at 20% and Paide at 14%. The model's leading outcome is a Rapid Vienna 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 AFC Champions League Two fixture between Arkadag and Goa, the 11Stat model assigns Arkadag a 73% chance of winning, with the draw at 18% and Goa at 9%. The model's leading outcome is a Arkadag 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 Torneo Federal A fixture between Alvarado and Huracan Las Heras, the 11Stat model assigns Alvarado a 73% chance of winning, with the draw at 21% and Huracan Las Heras at 6%. The model's leading outcome is a Alvarado 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 UEFA Europa League fixture between Pafos and Red Bull Salzburg, the 11Stat model assigns Pafos a 8% chance of winning, with the draw at 18% and Red Bull Salzburg at 75%. The model's leading outcome is an Red Bull Salzburg 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 League fixture between Vikingur Reykjavik and FC Thun, the 11Stat model assigns Vikingur Reykjavik a 49% chance of winning, with the draw at 21% and FC Thun at 30%. The model's leading outcome is a Vikingur Reykjavik 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 Conference League fixture between FC Sion and FC Noah, the 11Stat model assigns FC Sion a 70% chance of winning, with the draw at 18% and FC Noah at 12%. The model's leading outcome is a FC Sion 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 2. Bundesliga fixture between Holstein Kiel and FC St. Pauli, the 11Stat model assigns Holstein Kiel a 28% chance of winning, with the draw at 21% and FC St. Pauli at 51%. The model's leading outcome is an FC St. Pauli 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 Ligue 2 fixture between Reims and Dunkerque, the 11Stat model assigns Reims a 61% chance of winning, with the draw at 24% and Dunkerque at 15%. The model's leading outcome is a Reims 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 Jupiler Pro League fixture between Cercle Brugge and St. Truiden, the 11Stat model assigns Cercle Brugge a 16% chance of winning, with the draw at 25% and St. Truiden at 59%. The model's leading outcome is an St. Truiden 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 2. Bundesliga fixture between 1. FC Kaiserslautern and Karlsruher SC, the 11Stat model assigns 1. FC Kaiserslautern a 80% chance of winning, with the draw at 13% and Karlsruher SC at 7%. The model's leading outcome is a 1. FC Kaiserslautern 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 2. Bundesliga fixture between VfL Osnabrück and 1. FC Magdeburg, the 11Stat model assigns VfL Osnabrück a 13% chance of winning, with the draw at 17% and 1. FC Magdeburg at 70%. The model's leading outcome is an 1. FC Magdeburg 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 Süper Lig fixture between Kasımpaşa and Trabzonspor, the 11Stat model assigns Kasımpaşa a 72% chance of winning, with the draw at 21% and Trabzonspor at 7%. The model's leading outcome is a Kasımpaşa 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 Championship fixture between Portsmouth and QPR, the 11Stat model assigns Portsmouth a 10% chance of winning, with the draw at 20% and QPR at 70%. The model's leading outcome is an QPR 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 2. Bundesliga fixture between Dynamo Dresden and SV Darmstadt 98, the 11Stat model assigns Dynamo Dresden a 40% chance of winning, with the draw at 20% and SV Darmstadt 98 at 40%. The model's leading outcome is a Dynamo Dresden 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 2. Bundesliga fixture between Arminia Bielefeld and Energie Cottbus, the 11Stat model assigns Arminia Bielefeld a 65% chance of winning, with the draw at 21% and Energie Cottbus at 14%. The model's leading outcome is a Arminia Bielefeld 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 Atletico-MG and Gremio, the 11Stat model assigns Atletico-MG a 57% chance of winning, with the draw at 27% and Gremio at 16%. The model's leading outcome is a Atletico-MG 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 Slovan Bratislava and Celje, the 11Stat model assigns Slovan Bratislava a 67% chance of winning, with the draw at 20% and Celje at 13%. The model's leading outcome is a Slovan Bratislava 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 Champions League fixture between NEC Nijmegen and Bodo/Glimt, the 11Stat model assigns NEC Nijmegen a 20% chance of winning, with the draw at 21% and Bodo/Glimt at 58%. The model's leading outcome is an Bodo/Glimt 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 Champions League fixture between Celtic and Lask Linz, the 11Stat model assigns Celtic a 19% chance of winning, with the draw at 23% and Lask Linz at 58%. The model's leading outcome is an Lask Linz 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 Europa League fixture between Benfica and Aarhus, the 11Stat model assigns Benfica a 75% chance of winning, with the draw at 16% and Aarhus at 10%. The model's leading outcome is a Benfica 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 League fixture between Mjallby AIF and Red Bull Salzburg, the 11Stat model assigns Mjallby AIF a 10% chance of winning, with the draw at 16% and Red Bull Salzburg at 74%. The model's leading outcome is an Red Bull Salzburg 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 League fixture between Egnatia Rrogozhinë and Lillestrom, the 11Stat model assigns Egnatia Rrogozhinë a 73% chance of winning, with the draw at 17% and Lillestrom at 10%. The model's leading outcome is a Egnatia Rrogozhinë 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 La Liga fixture between Real Betis and Real Sociedad, the 11Stat model assigns Real Betis a 68% chance of winning, with the draw at 21% and Real Sociedad at 12%. The model's leading outcome is a Real Betis 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 Bundesliga fixture between Ried and Grazer AK, the 11Stat model assigns Ried a 73% chance of winning, with the draw at 15% and Grazer AK at 12%. The model's leading outcome is a Ried 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 Segunda División fixture between Cordoba and Girona, the 11Stat model assigns Cordoba a 18% chance of winning, with the draw at 17% and Girona at 66%. The model's leading outcome is an Girona 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 Liga Profesional Argentina fixture between Estudiantes de Rio Cuarto and San Lorenzo, the 11Stat model assigns Estudiantes de Rio Cuarto a 18% chance of winning, with the draw at 44% and San Lorenzo at 38%. The model's leading outcome is a draw, 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 Penybont and Llandudno, the 11Stat model assigns Penybont a 8% chance of winning, with the draw at 21% and Llandudno at 71%. The model's leading outcome is an Llandudno 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 Cardiff MET and The New Saints, the 11Stat model assigns Cardiff MET a 69% chance of winning, with the draw at 22% and The New Saints at 9%. The model's leading outcome is a Cardiff MET 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 Holywell and Barry Town, the 11Stat model assigns Holywell a 9% chance of winning, with the draw at 17% and Barry Town at 74%. The model's leading outcome is an Barry Town 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 Süper Lig fixture between Fenerbahçe and Konyaspor, the 11Stat model assigns Fenerbahçe a 67% chance of winning, with the draw at 25% and Konyaspor at 9%. The model's leading outcome is a Fenerbahçe 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 Primeira Liga fixture between Sporting CP and Alverca, the 11Stat model assigns Sporting CP a 72% chance of winning, with the draw at 19% and Alverca at 8%. The model's leading outcome is a Sporting CP 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 Ligue 1 fixture between Estac Troyes and Paris FC, the 11Stat model assigns Estac Troyes a 73% chance of winning, with the draw at 17% and Paris FC at 10%. The model's leading outcome is a Estac Troyes 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 Championship fixture between Derby and Cardiff, the 11Stat model assigns Derby a 10% chance of winning, with the draw at 16% and Cardiff at 75%. The model's leading outcome is an Cardiff 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 Eldense and Cadiz, the 11Stat model assigns Eldense a 11% chance of winning, with the draw at 15% and Cadiz at 75%. The model's leading outcome is an Cadiz 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 Championship fixture between Birmingham and Bristol City, the 11Stat model assigns Birmingham a 66% chance of winning, with the draw at 23% and Bristol City at 12%. The model's leading outcome is a Birmingham 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 La Liga fixture between Getafe and Racing Santander, the 11Stat model assigns Getafe a 66% chance of winning, with the draw at 22% and Racing Santander at 12%. The model's leading outcome is a Getafe 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 Serie A fixture between Venezia and Lecce, the 11Stat model assigns Venezia a 68% chance of winning, with the draw at 20% and Lecce at 13%. The model's leading outcome is a Venezia 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 Serie A fixture between Santos and Mirassol, the 11Stat model assigns Santos a 62% chance of winning, with the draw at 24% and Mirassol at 13%. The model's leading outcome is a Santos 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 Serie A fixture between Atalanta and Sassuolo, the 11Stat model assigns Atalanta a 61% chance of winning, with the draw at 24% and Sassuolo at 15%. The model's leading outcome is a Atalanta 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 Bologna and Lazio, the 11Stat model assigns Bologna a 13% chance of winning, with the draw at 20% and Lazio at 68%. The model's leading outcome is an Lazio 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 Premier League fixture between Baltika and Rubin, the 11Stat model assigns Baltika a 60% chance of winning, with the draw at 24% and Rubin at 16%. The model's leading outcome is a Baltika 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 Liga Profesional Argentina fixture between Tigre and Central Cordoba de Santiago, the 11Stat model assigns Tigre a 51% chance of winning, with the draw at 34% and Central Cordoba de Santiago at 15%. The model's leading outcome is a Tigre 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 Ligue 2 fixture between Reims and Annecy, the 11Stat model assigns Reims a 64% chance of winning, with the draw at 21% and Annecy at 15%. The model's leading outcome is a Reims 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 Champions League fixture between Bodo/Glimt and NEC Nijmegen, the 11Stat model assigns Bodo/Glimt a 70% chance of winning, with the draw at 20% and NEC Nijmegen at 10%. The model's leading outcome is a Bodo/Glimt 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 Champions League fixture between Sabah FA and Hapoel Beer Sheva, the 11Stat model assigns Sabah FA a 66% chance of winning, with the draw at 21% and Hapoel Beer Sheva at 14%. The model's leading outcome is a Sabah FA 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 Non League Premier - Northern fixture between Bury and Lancaster City, the 11Stat model assigns Bury a 78% chance of winning, with the draw at 15% and Lancaster City at 7%. The model's leading outcome is a Bury 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 La Liga fixture between Real Madrid and Real Sociedad, the 11Stat model assigns Real Madrid a 68% chance of winning, with the draw at 19% and Real Sociedad at 13%. The model's leading outcome is a Real Madrid 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 Champions League fixture between Viking and Dinamo Zagreb, the 11Stat model assigns Viking a 19% chance of winning, with the draw at 20% and Dinamo Zagreb at 61%. The model's leading outcome is an Dinamo Zagreb 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 1. Division fixture between Stabaek and Ranheim, the 11Stat model assigns Stabaek a 82% chance of winning, with the draw at 12% and Ranheim at 6%. The model's leading outcome is a Stabaek 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.