Video recording of PhD defense
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A quantitative pedagogical approach to the residency education in radiology. Data collection from 200 shifts worth of data, and basic analyses to gauge learning progression and gaps in knowledge and experience, as well as effect of Covid-19 pandemic on residency education.
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Through an example I show some analyses that can be used to illustrate how a skill is learned.
It can be used to compare individuals, each person’s speed of skill learning, the expected time taken to reach a certain goal, as well as identify the optimal time for each training session.
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Knowing the number of balls the team has in possession is crucial information as it heavily influences how to plan an attack. I have calculated the expected number of eliminated players with each given ball possession, both for teams and for individual players, and show how these stats can be used by the playmaker to improve success when attacking.
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How does the possession of a defensive blocking ball influence the ability to avoid elimination for defenders, and the probability of hitting the opponents for throwers?
I show individual and team stats for when the defender has and doesn’t have a blocking ball in possession.
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This is the first post to go deeper into some more abstract data, and presents an analysis from the upper-most layer of analysis. I show how one can illustrate and quantify whether a player is capable of recognising when they have a good game, and make efficient use of it, and when they should back down.
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Who doesn’t like a little organised chaos…
Quantification of individual player effect, example using playing speed as the variable.
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The Swedish Mixed Team broke convention by playing a type of Blitz-Dodgeball during the 2019 Central European Championships, almost landing them a gold medal. In this post I explain how one can quantify playing speed, how a fast speed of play influences game outcome, and why it can be an important adaptive tactic to have in the team arsenal.
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Many aspects of dodgeball – such as positioning, decision-making, speed and agility, ability to read the game – are hard to identify, record, and analyse. These obscure, qualitative skills can be collected under the umbrella-term “Tactical Skill”.
Using a player’s point scoring and technical skill, one can calculate their tactical skill, and even use it to quantify total skill. The total skill may be used to allowing direct comparison between different players and can be used as an objective method for ranking players by their ability to score and win games.
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Points scored per minute has a high correlation with the technical skills of individual players. In this post I show how it relates to the technical skill of the whole team, and how predictive it is regarding wins, draws and losses.
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Is it better to play on the wings or in the middle? I use stats from players that have played both positions to make an objective comparison in order to answer this question.
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Are you bored of taking regular photos and viewing them at home?
Do you want to re-experience your vacations as if you are there again?
Missing a loved one and want to feel as though they are sitting right in front of you?
Well, now you can! Using a Do-It-Yourself method called Stereography you can take regular photos with any camera and view them in 3D.
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Technical skill is a measure of a player’s ability to hit opponents and dodge incoming balls. One can estimate the technical skills of players by calculating their hit and defence percentages, and this measure has a high correlation with the ability to score points and win matches. Regression analysis indicates that throwing skill determines about 50% of how good a dodgeball player is, dodging ability determines around 25%, while the last 25% are determined by tactical skills.
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Dodging and throwing are essential basic skills in the game of Dodgeball. They are the technical skills that determine how good a player is at scoring points for the team. This post outlines what determines each skill, and in particular how throwing relates to game outcome and other statistical parameters. What happens if you throw a lot? What happens if you don’t throw enough? How can you compare the point scoring efficiency or players? How can you compare attacking skill between players with different throwing percentages and number of throws? All of these questions are discussed in the post.
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In this post I outline some of the statistics that I include in my Dodgeball analyses and hint at what these mean and how they can be used for further analyses and how they can guide decision-making regarding pre-game line-up selection and in-game playing tactics.
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An outline of my data science approach to Dodgeball. I explain the data I’ve collected and the analyses I’ve done, which will be presented, together with results, in future posts.
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Do you want to maximise muscle growth in the gym? Have you reached a plateau in terms of muscle growth? This post outlines why the concept of training periodisation, and including periods of maximal strength training, is crucial to maximising hypertrophy and breaking through a training plateu.
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A description of my PhD project in psychiatry: “Neurophysiological markers in autism - A magnetoencephalographic study”. It is a cross-disciplinary PhD within child and adolescent neuropsychiatry, neurophysiology and neuroradiology. I outline the methods, aims, and preliminary results of the project.
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I outline the rationale and results of my bachelor thesis in psychology where I investigated autistic-like traits in a population of Swedish students, and compared males and females, as well as students enrolled in technical and non-technical programs.
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