Champions League SemiFinals predictions (2nd leg)

Hi football fans,

This is it, tonight’s game will decide which teams will go to Kiev for the Champions League Final on May 26th.

Real Madrid and Liverpool are both in good position to pass this round, thanks to some away goals (Real Madrid beat Bayern Munich 1-2 in Munich), or to a comfortable lead (Liverpool beat Roma 5-2 at home). But we know better than to think the game is over, especially after Juventus and Roma’s 3 goals “remontadas” after losing the first leg in the Quarter Finals. Munich and Rome have not much to lose and are expected to be offensive tomorrow.

Both games are expected to be close, despite the first leg’s results. Tomorrow we will bet on a win for Real Madrid and from AS Roma (on this last one Bing disagrees and favours a Liverpool win instead).

Enjoy the games!

AnalystMaster

Champions League Semi-Final AnalystMaster Bing
Home Away H D A H D A
Real Madrid Bayern Munich 44% 23% 33% 39% 27% 34%
Roma Liverpool 42% 23% 36% 28% 30% 42%

Champions League SemiFinal Predictions

Hi Football fans,

Here are our predictions for the First leg of the Champions League Semi-Finals.

As Bing, we foresee Bayern Munich taking full advantage of their Home Advantage to win that first game with a 51% / 52% chance.

On the other game between the two challengers who defeated favourites Man City and Barcelona in the Quarter Finals, we also give Liverpool the better odds (45%), but we are not as optimistic as Bing (58%), and give Roma a 55% chance of upsetting the Home team with a draw or a defeat.

Champions League Semi-Final AnalystMaster Bing
Home Away H D A H D A
Liverpool Roma 45% 25% 31% 58% 24% 18%
Bayern Munich Real Madrid 52% 21% 27% 51% 27% 22%

Enjoy the games !

AnalystMaster

Weekly Football Predictions

Man United vs. City, Real vs. Atletico Madrid… who will win this weekend big games? Find our latest predictions below!

AnalystMaster

Premier League Week 33

Premier League Week 33 AnalystMaster Bing
Home Away H D A H D A
Everton Liverpool 38% 24% 39% 8% 16% 76%
Watford Burnley 37% 26% 36% 21% 46% 33%
Leicester Newcastle 48% 25% 27% 48% 24% 28%
Brighton Huddersfield 51% 25% 24% 56% 28% 16%
Stoke Tottenham 24% 24% 53% 17% 16% 67%
Bournemouth Crystal Palace 45% 25% 30% 81% 15% 4%
West Brom Swansea 44% 27% 29% 21% 36% 43%
Man City Man United 56% 22% 22% 33% 36% 31%
Arsenal Southampton 61% 21% 18% 89% 5% 6%
Chelsea West Ham 60% 21% 19% 89% 5% 6%

La Liga Week 31

La Liga Week 31 AnalystMaster Bing
Home Away H D A H D A
La Coruna Malaga 45% 27% 27% 45% 23% 32%
Alaves Getafe 37% 30% 33% 21% 46% 33%
Celta Sevilla 47% 24% 28% 58% 28% 14%
Betis Eibar 46% 24% 30% 89% 5% 6%
Barcelona Leganes 75% 17% 9% 89% 5% 6%
Levante Las Palmas 48% 25% 28% 50% 42% 8%
Real Madrid Atl Madrid 46% 23% 31% 41% 29% 30%
Sociedad Girona 42% 24% 34% 56% 28% 16%
Valencia Espanyol 56% 23% 21% 89% 5% 6%
Villarreal Bilbao 53% 24% 23% 89% 5% 6%

Serie A Week 31

Serie A Week 31 AnalystMaster Bing
Home Away H D A H D A
Benevento Juventus 15% 20% 65% 17% 16% 67%
Roma Fiorentina 48% 24% 28% 81% 15% 4%
Spal Atalanta 28% 25% 47% 8% 16% 76%
Sampdoria Genoa 51% 27% 22% 64% 20% 16%
Torino Inter 37% 26% 37% 8% 16% 76%
Crotone Bologna 39% 27% 33% 28% 32% 40%
Napoli Chievo 66% 20% 14% 89% 5% 6%
Verona Cagliari 32% 25% 42% 12% 25% 63%
Udinese Lazio 33% 23% 44% 8% 16% 76%
Milan Sassuolo 53% 24% 23% 64% 20% 16%

Ligue 1 Week 32

Ligue 1 Week 32 AnalystMaster Bing
Home Away H D A H D A
St Etienne Paris SG 24% 23% 53% 8% 16% 76%
Monaco Nantes 63% 20% 17% 89% 5% 6%
Toulouse Dijon 56% 23% 21% 45% 23% 32%
Guingamp Troyes 51% 26% 24% 37% 33% 30%
Amiens Caen 47% 29% 24% 45% 23% 32%
Angers Strasbourg 52% 24% 25% 58% 28% 14%
Bordeaux Lille 47% 27% 26% 81% 15% 4%
Nice Rennes 43% 26% 31% 55% 31% 14%
Metz Lyon 22% 22% 56% 17% 16% 67%
Marseille Montpellier 55% 24% 21% 39% 28% 33%

Bundesliga Week 29

Bundesliga Week 29 AnalystMaster Bing
Home Away H D A H D A
Hannover  Werder Bremen 43% 29% 28% 50% 42% 8%
Freiburg Wolfsburg 40% 30% 30% 48% 24% 28%
Koln Mainz 46% 25% 29% 22% 28% 50%
Mgladbach Hertha 42% 27% 31% 45% 23% 32%
Augsburg Bayern Munich 25% 25% 50% 6% 19% 75%
Hamburger Schalke 32% 28% 40% 21% 36% 43%
Dortmund Stuttgart 59% 22% 19% 55% 31% 14%
Frankfurt Hoffenheim 44% 24% 31% 33% 38% 29%
RB Leipzig Leverkysen 46% 24% 31% 45% 23% 32%

Champions League Quarter Final Predictions (1st leg)

The end of the season is coming up and so are the big games! You will find below our predictions as well as Bing’s for the first leg games of the Champions League Quarter Final.

Our predictions are pretty similar, only Barcelona seeming to have a strong chance of winning against Roma and the other games are projected to be very close.

Despite statistics give Liverpool a slightly stronger chance of winning, Guardiola’s team’s chances are almost equivalent so even a draw would not be an unlikely outcome.

As Bing, we are also betting on a Juventus win, however Real Madrid is coming strong in this end of season and has always performed well in Champions League (won back to back titles and beat PSG twice in the previous round). Their chances here are probably under estimated by our algorithms.

Enjoy the games and bet responsibly!

AnalystMaster

  AnalystMaster Bing
Home Away H D A H D A
Sevilla Bayern Munich 32% 25% 43% 28% 31% 41%
Juventus Real Madrid 47% 23% 30% 43% 31% 26%
Liverpool Man City 40% 24% 36% 41% 32% 27%
Barcelona Roma 53% 23% 24% 72% 17% 11%

Decision Making: why you need to know about the Bayes Theorem

In this section of the blog we will take you into the process of decision making, and we will start with introducing you the Bayes Theorem and why it is so important in the decision making process.

But let’s start with the beginning: how do you make a decision?

Decision Making and Probabilities

If you decide to go out without an umbrella, it could be because you just forgot it, but a more likely reason is that you think it will not rain. The weather is quite impossible to forecast with a 100% certainty (especially in my hometown in Ireland), but somehow you have evaluated that the probability of rain was low (let’s say <10%) and that carrying an umbrella with you was not worth the trouble compared to the benefit of having it in the unlikely event of rain.

We are used to make such decisions unconsciously and this is the basis of Risk Management and Decision Making.

Let’s take another example: you are a Retailer and need to decide how many pieces of Item X you need to carry in your store to avoid running out of stock and losing sales. If you decide to carry 5 pcs of Item X (for which you receive replenishment every day) in Stock, it is (or at least it should be) because you have evaluated that you almost never sell more than 5 pcs a day, and that if you do this happens so rarely (let’s say less than 1% of the time) that you are willing to accept the risk of running out of Stock 1% of the time vs. the cost of carrying additional Inventory to prevent against all the possible odds.

This probabilistic decision making process requires a deep understanding about the events of this world (such as rain or making more than 5 sales per day), now how do we evaluate them?

Rethinking Reality: nothing is certain!

Evaluate or Estimate the probabilities about the events of the world are carefully chosen words. This probabilistic approach invites us to rethink Reality and what we hold for certain.

A prediction like The Sun will rise tomorrow sounds so obvious that most of us would hold it as a universal truth. The probabilistic decision maker would instead say The Sun will rise tomorrow with a 99% chance. Then, every day, as the Sun rises, the probabilistic decision maker refines his estimate which eventually becomes The Sun will rise tomorrow with 99.9% chance, then 99.99% chance, then 99.99999% chance. However the probabilistic decision maker will never give into the certainty of holding The Sun will rise tomorrow statement as an absolute truth. For him, nothing is certain in this world and 100% probability does not exist! (as a matter of fact we now know that in about 5 billion years from now the Sun will begin to die, so eventually one day The Sun will NOT rise tomorrow!)

Therefore we will never know for sure the real probabilities necessary for evaluating risks and making decisions like carrying an umbrella, selling more than 5 pcs per day, or seeing the Sun rise tomorrow. However what we can do is Estimate them through Observations and Tests.

It is very important to make the distinction between Tests and Absolute Reality as they are not the same thing and Tests incorporate a risk of error:

  • Tests and Reality are not the same thing: for example being tested positive for Cancer and having Cancer are not the same thing
  • Tests are flawed: Tests can be wrong. For example you can be tested positive for Cancer and not have Cancer at all (this is called a false positive) or being tested negative for Cancer and have it (this is called a false negative)

The Bayes Theorem and its applications

Instead of holding Universal Truths, we are now invited to think the world (even the most certain things like the Sun rising every day) in terms of probabilities, and to evaluate these probabilities through Objective Tests and Observations, and continuously refine these estimates as new evidence comes up.

In a probabilistic world, this translates into the Bayes Theorem:

Bayes Theorem:

P(A¦X) = P(X¦A) * P(A)  /  P(X)

i.e. probability of A happening knowing X happened = probability of X happened knowing A as true (true positive) * probability of A happening / probability of X happening

or its equivalent form

P(A¦X) = P(X¦A) * P(A) / ( P(X¦A) * P(A) + P(X¦not A) * P(not A) )

Now let’s see how the Bayes Theorem works on a practical example. Let’s try to evaluate P(A¦X) the probability of having Cancer (A), following the result of a positive test X

Prior probability of having Cancer before the test P(A) = 1%

We know that P(not A) = 1 – P(A) = 99%

New Event occurs: tested positive for Cancer

  • P(X¦A) is the true-positive probability of having Cancer knowing that you have been tested positive = 80%
  • P(X¦notA) is the false-positive probability of being tested positive if you do not have cancer have cancer:  = 10%

Posterior probability

P(A¦X) = P(X¦A) * P(A) / ( P(X¦A) * P(A) + P(X¦not A) * P(not A) ) = 7.5%

The Bayes Theorem invites us to start with an initial estimate of 1% chance of having cancer, which will increase to 7.5% after having being tested positive, incorporating the risks of true and false positive.

A second positive test would increase the probability of having cancer further

Prior probability of having Cancer before the test P(A) = 7.5%

We know that P(not A) = 1 – P(A) = 92.5%

New Event occurs: tested positive for Cancer

  • P(X¦A) is the true-positive probability of having Cancer knowing that you have been tested positive = 80%
  • P(X¦notA) is the false-positive probability of being tested positive if you do not have cancer have cancer:  = 10%

Posterior probability

P(A¦X) = P(X¦A) * P(A) / ( P(X¦A) * P(A) + P(X¦not A) * P(not A) ) = 41%

After this second positive test we know have 41% chance of having cancer.

Bottom Line

The Bayes theorem is all about acknowledging that we do not know for sure about the events in the world, that we need to think about them probabilistically and that we need to refine our estimates of these probabilities as new data becomes available

Old Forecast + New & Objective data = New Forecast

This sounds obvious but it is the core of Forecasting, Risk Management and Decision Making

AnalystMaster

Football Predictions for Premier League, La Liga and Serie A

Let’s kick off 2018 with our latest Football Predictions!

Premier League Week 22

On the contrary to Bing, we prefer to bet on Brighton vs. Bournemouth in a game that we expect to be close.

After 3 consecutive games without winning, we believe than Manchester United will continue to have a difficult time at Everton in a game too close to call.

Finally in the Arsenal – Chelsea derby we believe that the Gunners will make good use of their Home Advantage and we give them slightly favourable odds.

Premier League Week 22 AnalystMaster Bing
Home Away H D A H D A
Brighton Bournemouth 45% 28% 27% 22% 28% 50%
Burnley Liverpool 32% 25% 43% 29% 21% 50%
Leicester Huddersfield 52% 24% 24% 58% 28% 14%
Stoke Newcastle 40% 25% 35% 46% 36% 18%
Everton Man United 37% 25% 39% 12% 25% 63%
Southampton Crystal Palace 45% 28% 28% 58% 28% 14%
West Ham West Brom 39% 28% 33% 40% 27% 33%
Swansea Tottenham 21% 24% 54% 17% 16% 67%
Man City Watford 66% 18% 16% 89% 5% 6%
Arsenal Chelsea 42% 25% 33% 32% 25% 43%

La Liga Week 18

Despite benefiting from the Home Advantage, we believe that Valencia will be challenged by Girona, with a win % of 49%, much lower than Bing’s 81%.

We agree with Bing that the Leganes-Socidedad game is too close to call, with each side having equal winning probabilities.

La Liga Week 18 AnalystMaster Bing
Home Away H D A H D A
Ath Madrid Getafe 50% 29% 21% 58% 28% 14%
Valencia Girona 49% 24% 27% 81% 15% 4%
Las Palmas Eibar 43% 24% 34% 45% 23% 32%
Sevilla Betis 64% 21% 14% 89% 5% 6%
Leganes Real Sociedad 36% 27% 36% 25% 39% 36%
Barcelona Levante 72% 18% 10% 89% 5% 6%
Ath Bilbao Alaves 46% 30% 24% 58% 28% 14%
Vilarreal La Coruna 63% 21% 16% 89% 5% 6%
Celta Vigo Real Madrid 25% 23% 51% 12% 25% 63%
Malaga Espanyol 44% 25% 31% 64% 20% 16%

Serie A Week 20

We have some differences here with Bing, as we predict the games Chievo vs. Udinese and Fiorentina vs. Inter Milan too close too call

Genoa-Sassuolo is also expected to be a very close game, with the home side having slightly favourable odds.

As usual our odds are lower than Bing for the Napoli, AC Milan, Roma and Juventus games, although we both agree that a win from these top teams is the most likely outcome.

Serie A Week 20 AnalystMaster Bing
Home Away H D A H D A
Chievo Udinese 36% 25% 39% 56% 28% 16%
Fiorentina Inter 37% 26% 37% 8% 16% 76%
Torino Bologna 42% 26% 32% 56% 28% 16%
Benevento Sampdoria 29% 23% 48% 17% 16% 67%
Genoa Sassuolo 40% 25% 35% 25% 39% 36%
Spal Lazio 27% 23% 50% 17% 16% 67%
Napoli Verona 67% 19% 14% 89% 5% 6%
AC Milan Crotone 59% 23% 18% 89% 5% 6%
Roma Atalanta 52% 24% 24% 89% 5% 6%
Cagliari Juventus 24% 21% 56% 8% 16% 76%

Happy New Year 2018 everyone!!

AnalystMaster

Year End Football Predictions

 

Premier League Week 21

The notable difference with Bing Predicts is on the Watford-Swansea and Huddersfield-Burnley games that we predict too close to call, whereas Bing seems to see a pretty clear victory of the Home side for both games.

Bing Predictions for the last 3 games on Dec 31st are not available at this time.

Premier League Week 21 AnalystMaster Bing
Home Away H D A H D A
Chelsea Stoke 64% 20% 16% 81% 15% 4%
Bournemouth Everton 45% 26% 29% 55% 31% 14%
Liverpool Leicester 55% 24% 22% 45% 25% 30%
Watford Swansea 37% 26% 38% 52% 25% 23%
Huddersfield Burnley 37% 29% 34% 46% 36% 18%
Newcastle Brighton 39% 30% 30% 55% 31% 14%
Man United Southampton 64% 23% 13% 89% 5% 6%
Crystal Palace Man City 18% 21% 61% N/A N/A N/A
West Brom Arsenal 35% 26% 39% N/A N/A N/A
Tottenham West Ham 64% 21% 15% N/A N/A N/A

Serie A Week 19

Overall our predictions are similar to Bing, with the notable exception of the Bologna-Udinese game which we think will be very close whereas Bing foresees an easy Bologna victory. We also believe that the game between Inter and Lazio will be very challenging to predict as well, Inter only having a 43% victory odd vs. 55% for Bing.

As usual we believe the 89% that Bing predicts for Sampdoria, Atalanta and Roma wins is too high and our victory probability is in the 60s %

Serie A Week 19 AnalystMaster Bing
Home Away H D A H D A
Crotone Napoli 17% 22% 61% 17% 16% 67%
Fiorentina Milan 47% 23% 30% 55% 31% 14%
Bologna Udinese 36% 25% 40% 81% 15% 4%
Benevento Chievo 28% 25% 48% 12% 25% 63%
Sampdoria SPAL 63% 21% 16% 89% 5% 6%
Atalanta Cagliari 60% 23% 17% 89% 5% 6%
Roma Sassuolo 60% 22% 18% 89% 5% 6%
Torino Genoa 45% 27% 28% 42% 28% 30%
Inter Lazio 43% 22% 35% 55% 31% 14%
Verona Juventus 17% 20% 64% 17% 16% 67%

We hope you all enjoy these last 2017 games, we will come back strong in 2018 with more Football articles and predictions!

Happy New Year everyone!

AnalystMaster