BEST VALUE the new era of data feed REPORT 2018-19 AND 2019-20 1 Abstract The goal of the work done to build Best Value, was to create an operating model which, trough the application of specific algorithms, allowed to build odds in line with the market, but more performing. In this report we will show the results obtained through the application of our mathematical algorithms on the following football leagues: Italian Serie A, French Ligue 1,German BundesLiga, Premier League and Liga (final result). In the following seasons: 2018-19 and 2019-20 (partial). Best Value vs Avg or Pinnacle day by day Used methodology: For the calculations we have adopted the following procedure: 1. For each match analyzed, we determined the gain or loss (in terms of accuracy) of our odds compared to both the average odds of all the bookmakers who provided indications for that specific match (Avg) and those of Pinnacle. This result called R LG where G=gain and L=loss, takes into account the difference in terms of margin proposed by us compared to that offered by competitors, summed up with the ratio between our odds and our competitors’ odds.The values for Avg and Pinnacle are obtained from the website: http://www.football-data.co.uk/ The adopted formula is the following: R LG = M B B − M Av g + ∆ ¡ OB B ¢ O Av g where: M B B = Best Bet margin. M Av g = Avg or Pinnacle margin. ∆ = Ratio of the odds from Best Bet and the ones from competitors (Avg or Pinnacle). 2 2. Each game on each league day, the following averages were calculated: Average book value Avg, Pinnacle average book value, Best Bet average book value and the average gain or loss values of Best Bet vs Avg and Best Bet vs Pinnacle odds ratio, indicated with R LG Avg and R LG Pinnacle. 3. Of these average values we subsequently calculated the average. Therefore Avg represents the seasonal average of the average book value of each match day, while Pinnacle represents the seasonal average of the average book value of each match day proposed by Pinnacle. Best Bet describes the seasonal average of the average value recorded by Best Bet and ∆ Avg together with ∆ Pinnacle are the seasonal average value of the daily average value of R LG Avg and R LG Pinnacle. Avg Pinnacle Best Bet ∆ Avg ∆ Pinnacle Avg Pinnacle Best Bet ∆ Avg ∆ Pinnacle Serie A 4,81% 2,83% 2,00% 2,50% 1,00% Serie A 5,08% 3,18% 2,28% 1,51% 0,69% Season 2018-19 Ligue 1 5,04% 2,50% 2,50% 2,50% 0,91% Premier League 4,16% 2,30% 2,50% 1,06% 0,51% Season 2019-20 Ligue 1 5,21% 3,18% 2,00% 2,62% 1,36% Premier League 4,23% 2,93% 3,00% 0,87% 0,57% BundesLiga 4,70% 2,83% 2,00% 2,32% 1,01% LIGA 4,74% 2,75% 2,00% 2,72% 1,32% BundesLiga 4,86% 3,27% 3,00% 1,58% 0,71% LIGA 4,85% 3,18% 2,98% 1,63% 0,42% The tables above show the results obtained. 3 How are our odds obtained? The values of our odds are calculated on the basis of the results we get from our calculation algorithms. The answer provided is then translated operationally into a matrix of weights. This matrix has the purpose of filtering the incoming odds, so that the output odds are in line with the market, but, over time, the performance obtained is significantly better. In this way we are able to filter, given the matrix of the weights, the variation of the oddss operated by the market, fixed the margin of book. The diagram below illustrates the operating sequence. Figure 1: Logical block diagram Best Vaue vs Avg or Pinnacle seasonal segmentation. Seasonal segmentation into three sections. Let us consider dividing the championship into three phases; phase A: from 1st to 12th matchday, phase B: from 13th to 25th, and finally from 26th until the end of the tournament is phase C. This is how the calculation process works: first of all it needs to be computed the difference between the average annual value of Avg(or that of Pinnacle) and the weekly average values that have been calculated for both Avg and Pinnacle. Our goal is to see if we have been better than the whole season or if in some areas we have achieved particular results. This is the analysis: In the 4 2018-19 season compared to Avg our models performed better by more than 2%, in 2019-20 the performance was even better: 2.5% in the two phases that have currently been completed. These values are due to the fact that, in general, the data of the applied margin for Avg is about double, if not more, than that proposed by us. The matter changes if we compare our results with those of Pinnacle. In 2018-19 the results varied from a minimum of 0.03% for the second phase of Serie A (it means that our odds were substantially equally performing to the ones of Pinnacle),to a maximum of 2.06% obtained in the first phase of the Premier League. This result was probably due to a series of surprises that the bookmaker was unable to catch. For 2019-20 the situation in general has improved, given that Pinnacle books at a value of about 1% higher than last year, with one exception:the Premier League, where we book at 3% while Pinnacle books at 2,97%, and in this situation, the proposed odds were equal or slightly higher. Tables below show the results obtained. A B C Serie A 0,72% 0.03% 0,22% Season 2018-19 Best Value vs Pinnacle Ligue 1 1,34% 1,47% 1,91% Premier League 2,06% 1,74% 1,65% BundesLiga 1,79% 2,03% 1,67% Season 2019-20 Best Value vs Pinnacle Ligue 1 1,84% 2,03% 1,38% Premier League 0,36% 0,00% -0,64% BundesLiga 2,42% 2,72% 2,49% Serie A 2,38% 2,68% 2,18% A B C A B C Serie A 2,87% 1,92% 2,20% Season 2018-19 Best Value vs Avg Ligue 1 2,35% 2,43% 2,81% Premier League 2,53% 2,77% 2,65% BundesLiga 2,35% 2,39% 2,39% 5 LIGA 1,54% 1,28% 1,50% LIGA 2,52% 2,98% 2,65% LIGA 2,36% 2,38% 2,39% A B C Serie A 3,16% 3,80% 4,58% Season 2019-20 Best Value vs Avg Ligue 1 2,58 % 2,92% 1,71% Premier League 3,40% 3,47% 2,70% BundesLiga 3,17% 3,63% 2,67% LIGA 3,07% 3,51% 2,68% Conclusions: Best Value performs better than Avg ( ~3%) both throughout the year and in seasonal segmentation. Comparing the results with Pinnacle during the year, thr performance of Best Value remains the better, about 1- 2%. Instead in seasonal segmentation in there are differenes, due to particular events and the lack of statistical rilevance (2019-20 phase C) Pros and Cons Let’s briefly analyze the pros and cons of the product: Pros: ability to catch surprises, from which you get better results than the competition, remaining in line with the market. Cons: possibility to follow only the most important European markets, for instance. B EST VALUE PROVED SUPERIOR TO BOTH AVG AND P INNACLE . B OTH WEEK BY WEEK AND THROUGHOUT THE SEASON . 6
