# Cricket Moneyball, pt 2

Hello readers, today we have part 2 of this cricket moneyball series. If you missed the first one its here: https://wordpress.com/view/theparttimeanalyst.com In it I looked at calculating the Pythagorean win percentage for each team in the IPL and then moving that forward to calculating the how many extra runs are needed to win one extra […]

# The Most Unpredictable League?

Hello, I watch a lot of football in the championship and often the commentators on sky sports will say “this is the most unpredictable league in the world”. The thought occurred to me that this is actually quite easy to test. All you need is a model which predicts a range of league. The model […]

# Cricket Moneyball?

Moneyball. That horrific word coined by the book written by Michael Lewis and later hammered further into the public consciousness with the film starring Brad Pitt. Now anything in sport using stats is termed Moneyball when the truth couldnâ€™t be further from that. In this blog I am going to look at some concepts of […]

# F1 Drivers Rated

Hello, welcome to today’s blog and in it I’m going to be developing methods to evaluate F1 drivers. Currently there is no real way to tell if an F1 driver is any good. It seems sort of arbitrary how a racing driver is decided if they are good or not. Being a data fan I […]

# Finding Undervalued Air Bnb’s

Hello, today I am going to do an EDA (exploratory data analysis) on AirBnB in the New York area. This data set is available here on Kaggle https://www.kaggle.com/dgomonov/new-york-city-airbnb-open-data Lets read the data into R and take a look of it So I can see there are 17 columns and over 48000 records with information covering […]

# Predicting Qualifying — 2

In the last blog I outlined creating a model which predicts the fastest time for each driver in F1 qualifying. theparttimeanalyst.com/2019/07/10/predicting-f1-qualifying/ Today I am going to be dissecting the model to understands its strengths and weaknesses and to look if their is any bias within the model. First lets look at the importance matrix The […]

# 1st Ashes Test — My Team

Hello welcome to today’s blog looking at something a bit different. The first ashes test starts on 1st August and England will imminently name their squad. In this piece I look at what the team for the first game might look like. First things first this is the team that played the last test match […]

# Predicting F1 Qualifying

Hello, welcome to this blog a few days ago I tweeted the below graph in a tweet It was the output from the model I have created which predicts the qualifying time for each driver. I will get into the review of the outputs of the model in the next blog but today im going […]

# The Value of a Wicket

Hello, today I am going to be looking a the value of a wicket. In one daya cricket be it 20 over of 50 over you have 2 resources. The amount of balls remaining and the amount of wickets remaining. The balls remaining influences what risks the batsman takes however how much does taking a […]

# Replacing Nikita — 3

Hello, Welcome to the third and final part of my replacing Nikita Parris series. If you haven’t caught the first 2 blogs go check out before this one as they take you through the various parts of the process. We identified our 3 best candidates to replace Nikita Parris: Francesca Kirby, Millie Farrow and Vivianne […]