Dane Jessen

Data Scientist. Dabbles in sports data.

[Dane Jessen @jessen_dane]

I've been playing around with the doParallel package in R to speed up modelling. Here's an example of how ML models are trained faster by utilising more CPU cores.
#rstats #randomforest #MachineLearning

[Dane Jessen @jessen_dane]

The expected score from the Wallabies game isn’t very promising either. Decent first 25 minutes and not a whole lot a positive takeaways after that… 🫣
#RWC2023 #Rugby #rstats

[Gold Coast Suns @GoldCoastSUNS]

History made!

[Dane Jessen @jessen_dane]

@crow_data_sci @LeagueEyeTest I have seen @LeagueEyeTest’s expected scores in NRL. Some cool insights and definitely curious about their model!
I’ll have to reach out to them.

[Dane Jessen @jessen_dane]

Rugby World Cup Warm Up Games - Expected Scores

#RugbyWorldCup #Rugby #RWC2023

[Dane Jessen @jessen_dane]

At the end of the game, Expected Scores from the all the events in the game are added together to give a team their total total expected score.

[Dane Jessen @jessen_dane]

It takes into account game data such as, carries, kicks, penalties, field position, player, game time, and sin bin advantage to name a few.

For example, a carry by a tighthead 10m from the try line may have an expected score of 0.8.
This is added to the teams expected score.

[Dane Jessen @jessen_dane]

Bledisloe Cup Expected Scores:

NZL: 22.8 vs AUS 28.6

That was the Wallabies game to lose. First half dominance should have seen more points scored.

#BledisloeCup #Rugby #rstats #NZLvAUS

[Tim Newans @TNewans]

With Australia's trip to England for the Ashes complete, @chris_drovandi and I took a deep dive into Bazball to see how game-changing it has been for Test cricket from a stats perspective, see our @ConversationEDU article here: https://t.co/RgX7HHYymB

[Dane Jessen @jessen_dane]

Rugby Championship: Round 2 Expected Scores
NZL: 29.6 vs RSA: 20.2
AUS: 22 vs ARG: 42

#RugbyChampionship | #AUSvARG | #NZLvRSA | #rstats

[Dane Jessen @jessen_dane]

Rugby Championship: Round 1 Expected Scores
RSA: 39.1 vs AUS: 8.6
ARG: 18.2 vs NZL: 61

#RugbyChampionship | #RSAvAUS | #ARGvNZL | #Rugby

[Dane Jessen @jessen_dane]

This 🙌

[Albert Rapp @rappa753]

This book will give you superpowers:

R for Data Science

2 Years ago, I started my #rstats journey with this book. And since then, I've used what this book taught me every single day.

Absolutely best place to get started with R. And it's free. 🥳

https://t.co/BxBVrEehM1

[Dane Jessen @jessen_dane]

Update:
Tim English takes the average Fantasy market share lead 🐶 #AFLFantasy

[Dane Jessen @jessen_dane]

Top 20 market shares across the 2023 #AFLFantasy competition so far. Market share is the % of AF points a player scores from their team. @RoyDT @WarnieDT @CalvinDT

[Dane Jessen @jessen_dane]

📢 Market share update:
Harry Sheezel knocks Clayton Oliver off top spot to hold the highest market share in the competition.
Will Day has also made his way into the top 20. 💪
#AFLFantasy

[Dane Jessen @jessen_dane]

Nick Daicos, a second-year player, is absolutely killing it with his disposal efficiency numbers! 🤯 #AFL #AFLFantasy #rstats #ggplot2

[Dane Jessen @jessen_dane]

Love the context that violin plots add to box plots. A dynamic duo! 🎻📊 #dataviz #statistics #violinplot #rstats #SuperRugbyPacific

[Dane Jessen @jessen_dane]

Shoutout to @RowanTFL for the inspo for this viz. Check out his account for a deeper dive into AF markets shares.

[Dean Ritchie PhD @DeanRitchie26]

@mart1buch Great example, more isn’t always better.
Context key, +1km HSR for no greater impact on match could be considered inefficient.
However, preparing for worst case scenario & knowing an athlete can complete ↑ HSR if the game dictates is important.
Game demands dictate game output.