Category Archives: Data Driven Management

Bayesian Inference – the dangers of “small data” combined with a mis-informed Prior

Posted on October 6, 2018 by swdevperestroika

Continuing on my previous example of trying to figure out the true proportion of blue marbles in a bag: Previously, we used a non-informative, uniform prior for our inference. This time, let’s compare that non-informed prior with an informed prior – … Continue reading →

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Bayesian Multi-predictor Regression – Valet2018

Posted on September 18, 2018 by swdevperestroika

[Continuing my exploration of the Swedish election results, but I thought this might be of interest also for those of you not very interested in the Swedish elections, simply because the potential MatStat’s  insights – thus, the text is in … Continue reading →

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Making a living as a Professional Scientific Gambler using Bayesian Inference…?

Posted on May 21, 2018 by swdevperestroika

As my readers know, over the past few weeks I’ve been conducting an experiment: Applying scientific betting on the just finished Ice Hockey World Championships.  By “scientific”, I’m referring to the exclusive use of statistical and mathematical models, simulation, and … Continue reading →

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Scientific Gambling – Ice Hockey World Championships starting tomorrow

Posted on May 3, 2018 by swdevperestroika

The tournament is starting tomorrow with four games. From now on, future posts on this topic on the public Facebook group Scientific Gambling on Ice Hockey World Championships 2018 only. So, I you want to continue following how my Bayesian Inference engine … Continue reading →

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Scientific gambling – How to identify potentially profitable odds/plays ?

Posted on April 30, 2018 by swdevperestroika

In all sports gambling, success or failure is determined by a number of factors, luck not being the least of them, since in any sport there are loads of “Unknown Unknowns“, which we could also call “Uncertainty”. And then there … Continue reading →

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Scientific Gambling on Ice Hockey Worlds – identifying potentially exploitable games

Posted on April 30, 2018 by swdevperestroika

One of the most difficult aspects of dealing with lots of data, is to present the information obtained from various computations in a clear and meaningful way. For instance, in order to identify games where there is a potentially exploitable … Continue reading →

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Scientific Gambling on Hockey Worlds – Expected profits from games of day 1 & 2

Posted on April 27, 2018 by swdevperestroika

An Expected Value-calculation gives the expected gains from my bets on the games played during the first two days of the tournament as follows: OUTCOME U_ODDS U_P P P_DELTA EV_PER_UNIT HOME AWAY CZE SVK DRAW 5.20 0.192308 0.243738 0.051430 0.267438 … Continue reading →

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Scientific Gambling on Ice Hockey Worlds – Bets for games of May 5th

Posted on April 26, 2018 by swdevperestroika

Summary I’m using mathematical & statistical methods, more specifically, Bayesian Inference, Markov Chain Monte Carlo, simulation and Probabilistic Programming, attempting to predict the game outcomes of the upcoming Ice Hockey World Championships, starting May 4th. Based on the findings of … Continue reading →

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Bayesian Prediction – wanna bet…? Putting your money where your mouth is…

Posted on April 24, 2018 by swdevperestroika

[A disclaimer: I know virtually nothing about contemporary ice hockey, my interest faded when Börje Salming decided to put his skates on the shelf for a couple of decades ago, so I have not included any personal hockey insights into … Continue reading →

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Bayesian Inference 2018 Ice Hockey World Cup outcomes

Posted on April 15, 2018 by swdevperestroika

I’ve tuned my Bayesian model a bit. Previously, it used the cumulative sum of historical results point spread as its data input, now it uses each individual game spread. Perhaps an example can make this clearer: Consider two teams, A … Continue reading →

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