# Pole Position Prediction- A tidymodels Example

Hello readers, today’s blog I will be looking at predicting the formula 1 grid using the Tidymodels collection of R packages. The idea is to use data from the practice sessions on a Friday, to give an idea of what the grid is expected to be for the race on Sunday before qualifying on Saturday. […]

# Twenty20 Win Probability Added

Hello readers, welcome to today’s blog. I am going to implement a win probability added model for twenty 20 cricket. Now this is nothing new a quick google and there are many sources for it. Cricviz is possibly the most famous version which you may have seen on the app. The idea is the model […]

# 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 […]

# 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 1

Today I have a challenge go through. Done by FC Rstats however the submission was a few weeks ago and I did it in a rush and I don’t think it was my best work. Therefore this is a re hash of my submission so could end up with different results. The challenge is simple […]

# Copying the plot – 1

Hello, today i’m going to try something different, it’s not going to be original content. I am going to be having a go at copying a data visualisation. The data visualisation comes from latest tidy Tuesday data set and is taken from the Economist. See the plot below: The key parts of this plot: Faceted […]