BSports League Projections – COMING SOON!!

As the European domestic seasons approach, the BSports team is putting together the final touches for our European League Projections.

We will use our unparalleled data analytics technology to create our own European football projections, aimed at calculating the percentage probabilities for each team’s league finish in the top five European leagues. These will be based on analysing multiple data points associated with previous years of performance for each club, supplemented by Bloomberg algorithms that incorporate the additional value that clubs gained from the transfer window, including our unique BSports Rating used in the Power 50.

The League Projections will be updated on a weekly basis to show the effects of match results whether your team is involved or not.

For an idea of how accurate our match-by-match forecasting is, please head over to our accuracy report.

View the league projections from last season.



BSports developed an objective analysis that creates a performance rating for teams based on numerous data points and factors in previous performance. These rankings are not based solely on previous team performance however; they also factor in the importance of players and managers joining and leaving their clubs throughout the summer in a proprietary model built by Bloomberg Sports mathematicians and engineers.

A great example of this is Monaco, who have moved directly from recently-promoted Ligue 1 club to a UEFA Champions League contender. The performance value of their new players (Falcao, Joao Moutinho and James Rodriguez) significantly increased Monaco’s value. More specifically Falcao’s move will be integral to Monaco’s ability to score goals; increasing their ‘Goals For’ tally, pushing them towards the top of Ligue 1 and challenging PSG for the title. These individual performance ratings are developed using the same methodology that powered our Power 50 ratings at the end of the 2012/2013 season.

Once each team is given its Bloomberg Sports distinctive rating, we simulate each match of the season 100,000 times in order to provide an accurate projection for how each team will finish. The simulation eliminates ambiguity in the league table, and provides an accurate projection as a result of its large sample size.

The tables provide a purely objective projection for all European clubs, and projects their finish based on the results of our simulations.

These simulations help answer an infinite range of questions, such as:

  • What are the chances Barcelona wins La Liga this year?
  • What are the chances that Liverpool will finish in the Top 4 (earning a Champions League spot) this season?
  • What are the chances Crystal Palace is relegated just a season after being promoted to the EPL?
  • How did Monaco’s chances of winning Ligue 1 change after receiving a -2 point penalty before the season began?
  • What is the average number of League Points needed to survive relegation in Serie A?
  • What are the chances each of the 3 promoted teams in the Premier League end in the bottom three?


All of these questions, and more, can be answered from our simulations. Each league table will be updated throughout the season so you can see how all of these probabilities change throughout the season based on team’s current records, updated season ratings based on their remaining fixtures, form, major injuries, and any penalties given to teams throughout the season.

Champions League Methodology

The BSports (Bloomberg Sports) data system ingested and examined ten years of data for Champions League matches as well as the domestic matches in every European league that has clubs participating this year. The analysis also included historical performance of each league’s representatives in Champions League matches over that time period. Based on this analysis, we developed a regression-driven model that set ratings for each of the respective leagues relative to each other, and for each team within each league, supplemented by some minor adjustments based on summer developments (transfers, coaching staff etc.). Once the rankings were set, we simulated the tournament 10,000 times to determine the probabilities associated with each team’s chances to qualify for the Round of 16, to win their group and to win the overall tournament. The algorithms underlying the model are designed to update the rankings as the season goes along. Bloomberg Sports will incorporate data from each week’s matches throughout Europe, as well as the domestic form of competing teams, resulting in up to date adjustments for the Champions League projections each week.

*Data provided by