In-Depth Analysis
or how to beat the bookies at their own numbers
A few months ago, I developed and wrote about an ML-free algorithm to predict the Premier League results using a simple Poisson process. The track record of the program was more impressive than I thought it would be, correctly predicting the results for 7/10 matches in the first Matchweek (3 of which with the exact scoreline).
In a world of too much information, how do you tell the signals from the noises?
Sometimes, I wake up and feel anxious to open my phone. Scrolling through all the social media news feed, glancing at the New York Times app, hoping around some Youtube new uploads, takes a lot of time.
The flood of information that swamps me daily produces more pain than gain. Every iota of information has been so well-optimized at ‘looking urgent/important’ that we have to constantly making choices in terms of what to process, knowing that little (if none) of them will remain relevant in the next 24 hours?
What if there existed a rule to identify what type of…
Or that time when I talked about being a benchwarmer in my high school soccer team.
I thought about sharing this essay as a reference/source of inspiration as I was giving advice to some of my friends who are applying in this year college admission cycle.
I always think that the best advice is to write about something something dear to you, something really shows who you are as a person.
And there’s no better example of that than me writing about being a long-term benchwarmer in my high school soccer team 😂
Disclaimer:
- This is not my Common App…
A comprehensive, no-nonsense guide to Collaborative Filtering and all the cool acronyms MF, SGD, ALS
I (re)-discovered reading in 2020.
As the world muddles through a deadly pandemic and I’m holed up at home, an old habit of mine, something I have long forgotten since college, rekindles: curling up with a good book and enjoying moments of peace in meditation books, learning about how the world operates and dysfunctions, and relieving the sense of uncertainty and exhaustion with some tragic Maupassant stories.
As I venture into 2021 with this new-found burning passion for reading, there is just a tiny logistical problem: What book should I read?
Hands-on Tutorials
How confident are we that blue states California, New York, etc. do not turn red in the next election?
Author’s note: I’m experimenting with a shorter form of articles, which aims to introduce interesting statistical facts and rules of thumbs. Let me know how you like them. For more in-depth analysis:
Another election cycle, another time we are bewildered by the overall results. There was no blowout for any side. The election was a nail biter. Both Democrats and Republicans made unexpected inroads in several races.
Facing the rising uncertainty each election cycles, a friend…
When everything comes down to a spot kick, who can you trust?
Arguably the most nervy moment of all during a football match, the penalty shot is psychological warfare: Two men, one ball and a clear chance to score a goal. A penalty is supposed to be finished at the professional level: period. Anything else is a failure.
Such a task should only be required of players made with the iciest of veins.
There are great penalty-takers, those we can always count on to deliver the ball to the back of the net with a staggering metronomic efficiency. …
Bayes’ theorem and the probabilistic answers to the most fundamental question of all: “Does God exist?”
This article focuses not on formula and numbers, but a fascinating story where Bayes’theorem establishes itself across the most controversial discussions in philosophy, epistemology and religions.
We Data Scientists and Statisticians love Bayes’ theorem.
A seemingly simple idea: we get updated and improved belief by updating our initial belief with newly acquired information, Bayes’ theorem has been touted as one of the most powerful method for generating knowledge.
How knowing some Statistical theory may make finding Mr. Right slightly easier?
Let me start with something most would agree: Dating is hard !!!
(If you don’t agree, that’s awesome!!! You probably don’t spend that much time reading and writing Medium posts like me T — T)
Nowadays, we spend countless hours every week clicking through profiles and messaging people we find attractive on Tinder or Subtle Asian Dating.
And when you finally ‘get it’, you know how to take the perfect selfies for your Tinder’s profile and you have no trouble inviting that cute girl in your Korean class to dinner, you would think that it shouldn’t be hard to find…
Detailed tutorial on how to derive valuable insights from the most competitive games
“The greatest value of a picture is when it forces us to notice what we never expected to see.”
You have seen it all in the news: media outlets raving about the Coming of Sports Analytics age, commercial ads picturing Big Data tools like a pocket calculator, punditry using multi-dimensional cameras to collect details of every single perspiration of sport players ***enter your childhood hero names: L.Messi, LeBron James, Tom Brady, etc*** and enhance their performance by 10x.
While obviously we are not quite there yet, Sports Analytics have come a long way in helping teams with respect to decision…
Spoiler: A little bit of randomness actually helps (and no, you don’t even need Machine learning)
O Jogo Bonito (The Beautiful Game)
“There is no point in making prediction. It’s not worth speculating because nothing is set in stone and things change all the time in football.”
- Cristiano Ronaldo
People loves football because of how unpredictable every game can be. Last season, West Bromwich Albion was relegated after a series of poor performances that landed them at rock bottom of the English Premier League.
Guess what?
They had the most impressive records against the top 6: undefeated against Tottenham (1 win, 1 draw) and Liverpool…
