Sports Analytics Weekly by kubeia.io - 46/2025
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đČ Betting
Turkish football betting scandal: 1,024 players, 149 referees and âdraining the swampâ
nytimes.com - Tom Burrows
Now, it is the turn of the players to be at the centre of the storm, after 1,024 of them were suspended by the Turkish Football Federation (TFF) as part of the same investigation.
In a statement, the TFF said the players were found to have participated in betting activities and had been referred to its Professional Football Disciplinary Board.The Athletic breaks down the latest developments, and what the implications could be.
đ Sports Analytics
The Myth of the Two-Goal Lead
substack.com - Alex Marin Felices
The following summary critically reviews the research paper titled âBeware the Two-Goal Lead: The Truth Behind the Legend of the Most Dangerous Lead in Soccerâ by Jonathan Kent and Ulrik Brandes. All data, figures, and analysis presented here are drawn from their original work; I do not claim any authorship or ownership of the content. This summary has been written to provide a concise and technically informed synthesis of the paperâs findings, methodologies, and implications, while maintaining fidelity to the authorsâ intellectual contributions.
How Soon Can You Trust the League Table?
pythonfootball.com - MartinOnData
A few weeks back, Aurel Nazmiu shared a great visual showing when the Premier League table stabilises during the season. I loved it for three reasons:
- It shows you donât need fancy, complicated charts to do good analytics.
- This seemingly simple graph hides a surprising (to a beginner) amount of data wrangling beneath the surface.
- And when you try to recreate it yourself, you naturally start asking deeper questions you never considered when you first saw the figure â like what type of correlation should I use, and why does that matter? (more on that below).
đ° Quantitative Finance
Tackling estimation risk in Kelly investing using options
arxiv.org - Fabrizio Lillo, Piero Mazzarisi, Ioanna-Yvonni Tsaknaki
Abstract:The Kelly criterion provides a general framework for optimizing the growth rate of an investment portfolio over time by maximizing the expected logarithmic utility of wealth. However, the optimality condition of the Kelly criterion is highly sensitive to accurate estimates of the probabilities and investment payoffs. Estimation risk can lead to greatly suboptimal portfolios. In a simple binomial model, we show that the introduction of a European option in the Kelly framework can be used to construct a class of growth optimal portfolios that are robust to estimation risk.
How Hudson River Trading Actually Uses AI (Odd Lots Podcasts)
apple.com - Joe Weisenthal, Tracy Alloway
Unfortunately, it doesn't seem as though you can get great stock picks just by going to ChatGPT and asking it to recommend some investments. And yet financial firms of all sorts â including trading firms â say they're increasingly using AI. But are the tools actually being deployed? And how do these tools differ from traditional machine learning or algorithmic approaches to trading, the likes of which have been used by quant firms for decades now. On this episode of the podcast, we speak with Iain Dunning, the head of AI research at Hudson River Trading, a major US market maker. We discuss the firm's attempts to use AI not just for more efficient trading, but also to make short-term predictions about price, which further gives its traders an edge. Dunning walks us through his work, his views on the main constraints facing the space (labor, power, chips, etc.) and how his work is both different and similar to what's happening at the major cutting edge research labs like ChatGPT.
đ°ïž Blast From the Past
Round Two of âGamble Expectation and the Ergodicity Conundrumâ
medium.com - Michael Harris
Specifically, I claim that the example of a gamble Ole Peters has provided in his papers, seminars and lectures that supposedly refutes CM actually does not. In my first article, I offered an introduction to the reasons I believe this is the case. In this article I attack the validity of both the simulations and analytical results Ole Peters has presented in support of his argument that the particular example of a gamble he has offered has divergent expectation and that the CM statement as shown below does not hold.