Using Sportmonks’ AI and advanced Metrics
With the Sportmonks Football API and Predictions API you will be able to do deeper analysis of games. Before AND during a game. “Analysing a game beforehand?” Besides offering Head-2-Head data we also offer deep insights with our Prediction API. The AI included in this API is trained by millions of matches.
Our model delivers precise predictions for upcoming matches by leveraging cutting-edge machine-learning algorithms and a vast database of historical football data. It factors in key variables like team momentum, injury reports, head-to-head statistics, and more.
Additionally, we integrate a player contribution analysis, elevating our forecasts’ accuracy even further. This approach evaluates individual player performances and their influence on the team’s success, offering more profound insights into their potential impact on match outcomes. The model considers several vital metrics, including recent player form, positional role, and overall contributions to team dynamics.
Add to the Prediction API the Expected Goals Metrics and Pressure Index, and you have a complete set of tools to analyse El Clásico on a professional level. Statistics like possession, Passing Accuracy, shots, and so on do help. However, they are simply not enough to predict a match as big and intense as El Clásico.
The evolution of predictive models in football has transformed drastically over the years, thanks to advancements in machine learning and data analytics. In the past, football predictions were primarily based on subjective analysis and basic statistics. However, with the rise of machine learning algorithms, models have become far more sophisticated. These models now consider various dynamic variables, such as a player’s form, recent match performances, team injuries, and historical head-to-head results. This shift from static data to complex, real-time inputs has revolutionised predictions, delivering higher accuracy and insight.
Modern predictive models process vast datasets, training on historical and live data to identify patterns and trends that may go unnoticed by traditional methods. Factors like team formations, player fitness, and even psychological elements can now be analysed, allowing these models to provide a more nuanced understanding of likely outcomes. As the technology evolves, football predictions are becoming increasingly reliable, helping fans, analysts, scouts, and betting markets make more informed decisions based on real-time intelligence and predictive analytics.
Let’s have a look at the last El Clásico in Madrid. Real Madrid – FC Barcelona in La Liga April 21 2024, Fixture ID: 18850124. We will find out what the Prediction API had to say about this matchup and what actually happened.
"id": 12529052,
"fixture_id": 18850124,
"predictions": {
"yes": 56.6,
"no": 43.4
},
"type_id": 231,
"type": {
"id": 231,
"name": "Both Teams To Score Probability",
"code": "both-teams-to-score-probability",
"developer_name": "BTTS_PROBABILITY",
"model_type": "prediction",
"stat_group": null
The match ended in 3-2 for Real Madrid. As you can see the prediction for both teams to score was correct.
"id": 12528961,
"fixture_id": 18850124,
"predictions": {
"yes": 42.01,
"no": 46.57,
"equal": 11.42
},
"type_id": 1687,
"type": {
"id": 1687,
"name": "Corners Over/Under 9 Probability",
"code": "corners-over-under-9-probability",
"developer_name": "CORNERS_OVER_UNDER_9_PROBABILITY",
"model_type": "prediction",
"stat_group": null
Well, with two corners for Madrid and eighth for Barcelona, the Prediction API was wrong here. Because it is actually over nine corners. Why do I show this? It is a probability. Even if the chances are slim, it can still happen. Same as with Expected Goals. Top strikers will have shots for open goal with an xG of 0,95 and still miss. The Predicton API is here to help narrow down your misses on your bets.
Now, the moment you all have been waiting for, was the proper winner predicted?
"id": 12529058,
"fixture_id": 18850124,
"predictions": {
"home": 51.16,
"away": 24.22,
"draw": 24.62
},
"type_id": 237,
"type": {
"id": 237,
"name": "Fulltime Result Probability",
"code": "fulltime-result-probability",
"developer_name": "FULLTIME_RESULT_PROBABILITY",
"model_type": "prediction",
"stat_group": null
Yes, the match ended in a 3-2 win for Real Madrid. Based on the prediction model, the home team was given the highest chance of winning.
Let’s go a bit further back. Real Madrid – FC Barcelona 16th of October 2022 Fixture ID: 18545173.
"id": 4091663,
"fixture_id": 18545173,
"predictions": {
"home": 39.578,
"away": 35.339,
"draw": 25.078
},
"type_id": 237,
"type": {
"id": 237,
"name": "Fulltime Result Probability",
"code": "fulltime-result-probability",
"developer_name": "FULLTIME_RESULT_PROBABILITY",
"model_type": "prediction",
"stat_group": null
The prediction API gave the highest chance to a winner, which was most likely to be Real Madrid. The end result was a 3-1 victory for Real Madrid.
"id": 4091665,
"fixture_id": 18545173,
"predictions": {
"yes": 57.32,
"no": 42.68
},
"type_id": 231,
"type": {
"id": 231,
"name": "Both Teams To Score Probability",
"code": "both-teams-to-score-probability",
"developer_name": "BTTS_PROBABILITY",
"model_type": "prediction",