Category Archives: Statistics

Vasaloppet 2018 – race time analysis

An analysis of race times for the ~11000 men and ~2000 women that participated in 2018 Vasaloppet. For explanations of the graphs, see earlier posts on Marcialonga or Tour de Ski. [Btw, the weird looking vertical orange/blue “spike” in the … Continue reading

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Tour de Ski Final climb – does age matter for performance ?

In an earlier post, I analyzed data from the Marcialonga Ski race. Marcialonga is one of the classic long distance ski races, where both elite’ as well as amateurs compete together. In fact, the vast majority of the competitors in … Continue reading

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Tour de Ski 2019 Final Climb Analysis

Just a quickie analysis on the just finished race, comparing the climb times for women vs men, the top-28 of both genders. Once again, the results are consistent with my earlier findings on this topic: at elite’ level, the difference … Continue reading

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Marcialonga Ski 2018 – some Analytics

Now, with the power grid finally – after 62 hours! – back in business, I’m able to continue my stats/analytics exploration of the past Marcialonga ski race. First, some basic stats about the race: Total number of participants: 5558, of … Continue reading

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Gender is not a social construct, but a biological reality, clearly demonstrated in sports

Just a quick demo to debunk the contemporary notion that “Gender is a social construct”. Data taken from today’s Tour the Ski sprint qualification times, for the top 30 women vs men, where both men & women used the same … Continue reading

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Bayesian Linear Regression with PYMC

Python, Pandas & PYMC example on Bayesian Linear Regression, adopted from Richard McElreath’s “Statistical Rethinking” class, where he uses R as modeling language instead of PYMC. Data in a csv-file describe various attributes such as weight, height, age, gender etc … Continue reading

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

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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Why (sample) size matters – Bayesian Inference

[The following example is adapted from Richard McElreath’s excellent “Statistical Rethinking”] Let’s say you have bought a bag of marbles. The marbles in the bag are either blue or white. But you don’t know the proportions, that is, the ratio … Continue reading

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Global Warming – soon in a place near you

Just downloaded hourly temperature data from SMHI, the Swedish Meteorological & Hydrological Institute, taken on Svenska Högarna, one of the islands in the remote Stockholm Archipelago, for the years 1949 – 2018. The plots below present max/min/mean daily temps for … Continue reading

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Using Bayesian Inference to predict and bet on Italian Serie A Fotball

As my old timer readers know, I’be been using Bayesian Inference to predict and bet on various sporting events, such as FIFA World Cup, and IIHF World Championships. With some success. When the Italian premier division started for about a … Continue reading

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