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 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.
For the UEFA Europa League fixture between CSKA Sofia and OFI, the 11Stat model assigns CSKA Sofia a 72% chance of winning, with the draw at 17% and OFI at 10%. The model's leading outcome is a CSKA Sofia 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 League fixture between FC Thun and Lech Poznan, the 11Stat model assigns FC Thun a 11% chance of winning, with the draw at 16% and Lech Poznan at 73%. The model's leading outcome is an Lech Poznan 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 League fixture between Red Bull Salzburg and Mjallby AIF, the 11Stat model assigns Red Bull Salzburg a 66% chance of winning, with the draw at 20% and Mjallby AIF at 14%. The model's leading outcome is a Red Bull Salzburg 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 2. Bundesliga fixture between Eintracht Braunschweig and Hertha BSC, the 11Stat model assigns Eintracht Braunschweig a 9% chance of winning, with the draw at 16% and Hertha BSC at 75%. The model's leading outcome is an Hertha BSC 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 Ligue 1 fixture between Lille and Paris Saint Germain, the 11Stat model assigns Lille a 76% chance of winning, with the draw at 17% and Paris Saint Germain at 7%. The model's leading outcome is a Lille 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 Segunda División fixture between Tenerife and Sporting Gijon, the 11Stat model assigns Tenerife a 67% chance of winning, with the draw at 21% and Sporting Gijon at 12%. The model's leading outcome is a Tenerife 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 Ligue 2 fixture between Rodez and PAU, the 11Stat model assigns Rodez a 78% chance of winning, with the draw at 15% and PAU at 7%. The model's leading outcome is a Rodez 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 2. Bundesliga fixture between 1. FC Heidenheim and Dynamo Dresden, the 11Stat model assigns 1. FC Heidenheim a 9% chance of winning, with the draw at 14% and Dynamo Dresden at 78%. The model's leading outcome is an Dynamo Dresden 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 2. Bundesliga fixture between Karlsruher SC and VfL Wolfsburg, the 11Stat model assigns Karlsruher SC a 14% chance of winning, with the draw at 18% and VfL Wolfsburg at 69%. The model's leading outcome is an VfL Wolfsburg 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 Bundesliga fixture between FSV Mainz 05 and SC Paderborn 07, the 11Stat model assigns FSV Mainz 05 a 69% chance of winning, with the draw at 19% and SC Paderborn 07 at 12%. The model's leading outcome is a FSV Mainz 05 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 Tottenham and Newcastle, the 11Stat model assigns Tottenham a 68% chance of winning, with the draw at 20% and Newcastle at 13%. The model's leading outcome is a Tottenham 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 Real Madrid and Malaga, the 11Stat model assigns Real Madrid a 79% chance of winning, with the draw at 14% and Malaga at 7%. The model's leading outcome is a Real Madrid 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 Bundesliga fixture between FC Augsburg and FC Schalke 04, the 11Stat model assigns FC Augsburg a 28% chance of winning, with the draw at 19% and FC Schalke 04 at 54%. The model's leading outcome is an FC Schalke 04 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 Bahia and Internacional, the 11Stat model assigns Bahia a 66% chance of winning, with the draw at 24% and Internacional at 11%. The model's leading outcome is a Bahia 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 Premier League fixture between Aston Villa and Arsenal, the 11Stat model assigns Aston Villa a 9% chance of winning, with the draw at 14% and Arsenal at 77%. The model's leading outcome is an Arsenal 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 Atalanta and Bologna, the 11Stat model assigns Atalanta a 60% chance of winning, with the draw at 28% and Bologna at 12%. The model's leading outcome is a Atalanta 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 Süper Lig fixture between Amed and Trabzonspor, the 11Stat model assigns Amed a 74% chance of winning, with the draw at 19% and Trabzonspor at 7%. The model's leading outcome is a Amed 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 Championship fixture between Sheffield Utd and Bolton, the 11Stat model assigns Sheffield Utd a 52% chance of winning, with the draw at 32% and Bolton at 16%. The model's leading outcome is a Sheffield Utd 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 Challenge League fixture between Stade Lausanne-Ouchy and Étoile Carouge, the 11Stat model assigns Stade Lausanne-Ouchy a 80% chance of winning, with the draw at 14% and Étoile Carouge at 6%. The model's leading outcome is a Stade Lausanne-Ouchy 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 League Two fixture between Fleetwood Town and Oldham, the 11Stat model assigns Fleetwood Town a 73% chance of winning, with the draw at 20% and Oldham at 7%. The model's leading outcome is a Fleetwood Town 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 Mirassol, the 11Stat model assigns Flamengo a 74% chance of winning, with the draw at 20% and Mirassol at 7%. The model's leading outcome is a Flamengo 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 West Brom and Charlton, the 11Stat model assigns West Brom a 69% chance of winning, with the draw at 19% and Charlton at 13%. The model's leading outcome is a West Brom 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 Championship fixture between Millwall and Wrexham, the 11Stat model assigns Millwall a 51% chance of winning, with the draw at 34% and Wrexham at 16%. The model's leading outcome is a Millwall 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 Premier League fixture between FC Isloch Minsk R. and Bate Borisov, the 11Stat model assigns FC Isloch Minsk R. a 77% chance of winning, with the draw at 18% and Bate Borisov at 5%. The model's leading outcome is a FC Isloch Minsk R. 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 Alashkert and Van, the 11Stat model assigns Alashkert a 73% chance of winning, with the draw at 18% and Van at 9%. The model's leading outcome is a Alashkert 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 Gent and OH Leuven, the 11Stat model assigns Gent a 73% chance of winning, with the draw at 17% and OH Leuven at 9%. The model's leading outcome is a Gent 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 2. Bundesliga fixture between Hannover 96 and Karlsruher SC, the 11Stat model assigns Hannover 96 a 77% chance of winning, with the draw at 18% and Karlsruher SC at 6%. The model's leading outcome is a Hannover 96 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. Bundesliga fixture between Arminia Bielefeld and FC St. Pauli, the 11Stat model assigns Arminia Bielefeld a 69% chance of winning, with the draw at 18% and FC St. Pauli at 13%. The model's leading outcome is a Arminia Bielefeld 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 Premier League fixture between GAP Connah S Quay FC and Haverfordwest County AFC, the 11Stat model assigns GAP Connah S Quay FC a 73% chance of winning, with the draw at 20% and Haverfordwest County AFC at 7%. The model's leading outcome is a GAP Connah S Quay FC 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 Premier League fixture between Cardiff MET and Cambrian & Clydach, the 11Stat model assigns Cardiff MET a 71% chance of winning, with the draw at 18% and Cambrian & Clydach at 11%. The model's leading outcome is a Cardiff MET 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 Primeira Liga fixture between FC Porto and Moreirense, the 11Stat model assigns FC Porto a 72% chance of winning, with the draw at 21% and Moreirense at 8%. The model's leading outcome is a FC Porto 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 2. Bundesliga fixture between VfL Wolfsburg and Energie Cottbus, the 11Stat model assigns VfL Wolfsburg a 72% chance of winning, with the draw at 19% and Energie Cottbus at 9%. The model's leading outcome is a VfL Wolfsburg 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 2. Bundesliga fixture between Holstein Kiel and 1. FC Nürnberg, the 11Stat model assigns Holstein Kiel a 11% chance of winning, with the draw at 17% and 1. FC Nürnberg at 73%. The model's leading outcome is an 1. FC Nürnberg 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 FC Schalke 04 and Bayern München, the 11Stat model assigns FC Schalke 04 a 9% chance of winning, with the draw at 15% and Bayern München at 76%. The model's leading outcome is an Bayern München 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 2. Bundesliga fixture between SpVgg Greuther Fürth and 1. FC Heidenheim, the 11Stat model assigns SpVgg Greuther Fürth a 34% chance of winning, with the draw at 18% and 1. FC Heidenheim at 48%. The model's leading outcome is an 1. FC Heidenheim 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 VfL Osnabrück and Eintracht Braunschweig, the 11Stat model assigns VfL Osnabrück a 16% chance of winning, with the draw at 16% and Eintracht Braunschweig at 68%. The model's leading outcome is an Eintracht Braunschweig 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 Hertha BSC and 1. FC Magdeburg, the 11Stat model assigns Hertha BSC a 23% chance of winning, with the draw at 18% and 1. FC Magdeburg at 59%. The model's leading outcome is an 1. FC Magdeburg 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 La Liga fixture between Valencia and Barcelona, the 11Stat model assigns Valencia a 9% chance of winning, with the draw at 20% and Barcelona at 70%. The model's leading outcome is an Barcelona 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 Arsenal and Chelsea, the 11Stat model assigns Arsenal a 45% chance of winning, with the draw at 21% and Chelsea at 34%. The model's leading outcome is a Arsenal 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 Süper Lig fixture between Kasımpaşa and Amed, the 11Stat model assigns Kasımpaşa a 60% chance of winning, with the draw at 26% and Amed at 14%. The model's leading outcome is a Kasımpaşa 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 FC Isloch Minsk R. and Arsenal, the 11Stat model assigns FC Isloch Minsk R. a 75% chance of winning, with the draw at 19% and Arsenal at 6%. The model's leading outcome is a FC Isloch Minsk R. 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 Dinamo Brest and Bate Borisov, the 11Stat model assigns Dinamo Brest a 60% chance of winning, with the draw at 23% and Bate Borisov at 17%. The model's leading outcome is a Dinamo Brest 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 Serie B fixture between Palermo and Sampdoria, the 11Stat model assigns Palermo a 64% chance of winning, with the draw at 23% and Sampdoria at 13%. The model's leading outcome is a Palermo 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 AEK Athens FC and Lask Linz, the 11Stat model assigns AEK Athens FC a 61% chance of winning, with the draw at 22% and Lask Linz at 17%. The model's leading outcome is a AEK Athens FC 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 Championship fixture between Cardiff and Stoke City, the 11Stat model assigns Cardiff a 54% chance of winning, with the draw at 22% and Stoke City at 25%. The model's leading outcome is a Cardiff 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 Eredivisie fixture between NEC Nijmegen and Excelsior, the 11Stat model assigns NEC Nijmegen a 10% chance of winning, with the draw at 16% and Excelsior at 74%. The model's leading outcome is an Excelsior 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 Paris Saint Germain and Slovan Bratislava, the 11Stat model assigns Paris Saint Germain a 11% chance of winning, with the draw at 19% and Slovan Bratislava at 70%. The model's leading outcome is an Slovan Bratislava 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 Sporting CP and Galatasaray, the 11Stat model assigns Sporting CP a 59% chance of winning, with the draw at 20% and Galatasaray at 21%. The model's leading outcome is a Sporting CP 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 Championship fixture between Derby and West Brom, the 11Stat model assigns Derby a 9% chance of winning, with the draw at 16% and West Brom at 75%. The model's leading outcome is an West Brom 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 Moreirense and Benfica, the 11Stat model assigns Moreirense a 11% chance of winning, with the draw at 18% and Benfica at 71%. The model's leading outcome is an Benfica 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 Como and RB Leipzig, the 11Stat model assigns Como a 62% chance of winning, with the draw at 22% and RB Leipzig at 16%. The model's leading outcome is a Como 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 Stars League fixture between Al-Sailiya and Al Sadd, the 11Stat model assigns Al-Sailiya a 5% chance of winning, with the draw at 13% and Al Sadd at 82%. The model's leading outcome is an Al Sadd 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 Aktobe Jas and Turan Turkistan, the 11Stat model assigns Aktobe Jas a 8% chance of winning, with the draw at 14% and Turan Turkistan at 78%. The model's leading outcome is an Turan Turkistan 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 Bundesliga fixture between Union Berlin and FC Schalke 04, the 11Stat model assigns Union Berlin a 34% chance of winning, with the draw at 21% and FC Schalke 04 at 45%. The model's leading outcome is an FC Schalke 04 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 Cambrian & Clydach and Holywell, the 11Stat model assigns Cambrian & Clydach a 79% chance of winning, with the draw at 14% and Holywell at 7%. The model's leading outcome is a Cambrian & Clydach 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 Premier League fixture between Flint Town United and Cardiff MET, the 11Stat model assigns Flint Town United a 8% chance of winning, with the draw at 17% and Cardiff MET at 75%. The model's leading outcome is an Cardiff MET 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 Süper Lig fixture between Beşiktaş and Erzurumspor FK, the 11Stat model assigns Beşiktaş a 65% chance of winning, with the draw at 24% and Erzurumspor FK at 11%. The model's leading outcome is a Beşiktaş 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 Eintracht Braunschweig and Dynamo Dresden, the 11Stat model assigns Eintracht Braunschweig a 12% chance of winning, with the draw at 15% and Dynamo Dresden at 73%. The model's leading outcome is an Dynamo Dresden 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 FSV Mainz 05 and Eintracht Frankfurt, the 11Stat model assigns FSV Mainz 05 a 70% chance of winning, with the draw at 18% and Eintracht Frankfurt at 12%. The model's leading outcome is a FSV Mainz 05 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 Genoa and Frosinone, the 11Stat model assigns Genoa a 8% chance of winning, with the draw at 18% and Frosinone at 74%. The model's leading outcome is an Frosinone 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 2. Bundesliga fixture between VfL Osnabrück and Hertha BSC, the 11Stat model assigns VfL Osnabrück a 9% chance of winning, with the draw at 14% and Hertha BSC at 77%. The model's leading outcome is an Hertha BSC 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 2. Bundesliga fixture between Karlsruher SC and Energie Cottbus, the 11Stat model assigns Karlsruher SC a 45% chance of winning, with the draw at 21% and Energie Cottbus at 35%. The model's leading outcome is a Karlsruher SC 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 Flamengo and Corinthians, the 11Stat model assigns Flamengo a 64% chance of winning, with the draw at 27% and Corinthians at 9%. The model's leading outcome is a Flamengo 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 Amed and Başakşehir, the 11Stat model assigns Amed a 66% chance of winning, with the draw at 21% and Başakşehir at 13%. The model's leading outcome is a Amed 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 Premier League fixture between Leeds and Newcastle, the 11Stat model assigns Leeds a 62% chance of winning, with the draw at 24% and Newcastle at 14%. The model's leading outcome is a Leeds 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 Como and Parma, the 11Stat model assigns Como a 75% chance of winning, with the draw at 19% and Parma at 6%. The model's leading outcome is a Como 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 Serie A fixture between Bahia and Remo, the 11Stat model assigns Bahia a 69% chance of winning, with the draw at 22% and Remo at 9%. The model's leading outcome is a Bahia 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 Inter and Udinese, the 11Stat model assigns Inter a 66% chance of winning, with the draw at 22% and Udinese at 13%. The model's leading outcome is a Inter 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 Premier League fixture between Shakhtar Donetsk and Chornomorets, the 11Stat model assigns Shakhtar Donetsk a 61% chance of winning, with the draw at 25% and Chornomorets at 14%. The model's leading outcome is a Shakhtar Donetsk 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 La Liga fixture between Alaves and Valencia, the 11Stat model assigns Alaves a 73% chance of winning, with the draw at 19% and Valencia at 8%. The model's leading outcome is a Alaves 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 Elche and Real Madrid, the 11Stat model assigns Elche a 10% chance of winning, with the draw at 21% and Real Madrid at 69%. The model's leading outcome is an Real Madrid 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 Premier League fixture between The New Saints and Flint Town United, the 11Stat model assigns The New Saints a 79% chance of winning, with the draw at 16% and Flint Town United at 5%. The model's leading outcome is a The New Saints 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 Penybont and Briton Ferry, the 11Stat model assigns Penybont a 64% chance of winning, with the draw at 26% and Briton Ferry at 10%. The model's leading outcome is a Penybont 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 Premier League fixture between Barry Town and Ammanford AFC, the 11Stat model assigns Barry Town a 71% chance of winning, with the draw at 19% and Ammanford AFC at 11%. The model's leading outcome is a Barry Town 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.