Publications by Tinniam V Ganesh
Cricketr analyzes Ind-Aus faceoff in WTC 2023!!
“The unexamined life is not worth living.” – Socrates “There is no easy way from the earth to the stars.” – Seneca “If you want to go fast, go alone. If you want to go far, go together.” – African Proverb 1. Introduction In this post, I put my R package cricketr to analyze the Indian and Australia World Test Championship (WTC...
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“The unexamined life is not worth living.” - Socrates “There is no easy way from the earth to the stars.” - Seneca “If you want to go fast, go alone. If you want to go far, go together.” - African Proverb 1. Introduction In this post, I put my R package cricketr to analyze the Indian and Australia WTC squad ahead of the World Test Cham...
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IPL 2023:GooglyPlusPlus now with by AI/ML models, near real-time analytics!
It is carnival time again as IPL 2023 is underway!! The new GooglyPlusPlus now includes AI/ML models for computing ball-by-ball Win Probability of matches and each individual player’s Win Probability Contribution (WPC). GooglyPlusPlus uses 2 ML models Deep Learning (Tensorflow) – accuracy : 0.8584 Logistic Regression (glmnet-tidymodels) : 0.72...
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GooglyPlusPlus: Computing T20 player’s Win Probability Contribution
In this post, I compute each batsman’s or bowler’s Win Probability Contribution (WPC) in a T20 match. This metric captures by how much the player (batsman or bowler) changed/impacted the Win Probability of the T20 match. For this computation I use my machine learning models, I had created earlier, which predicts the ball-by-ball win probabilit...
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GooglyPlusPlus: Win Probability using Deep Learning and player embeddings
In my last post ‘GooglyPlusPlus now with Win Probability Analysis for all T20 matches‘ I had discussed the performance of my ML models, created with and without player embeddings, in computing the Win Probability of T20 matches. With batsman & bowler embeddings I got much better performance than without the embeddings glmnet – Accuracy �...
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Near Real-time Analytics of ICC Men’s T20 World Cup with GooglyPlusPlus
In my last post GooglyPlusPlus gets ready for ICC Men’s T20 World Cup, I had mentioned that GooglyPlusPlus was preparing for the big event the ICC Men’s T20 World cup. Now that the T20 World cup is underway, my Shiny app in R, GooglyPlusPlus ,will be generating near real-time analytics of matches completed the previous day. Besides the app c...
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Computing Win-Probability of T20 matches
I am late to the ‘Win probability’ computation for T20 matches, but managed to jump on to this bus with this post. Win Probability analysis and computation have been around for some time and are used in baseball, NFL, soccer hockey and others. On T20 cricket, the following posts from White Ball Analytics & Sports Data Science were good point...
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Boosting Win Probability accuracy with player embeddings
In my previous post Computing Win Probability of T20 matches I had discussed various approaches on computing Win Probability of T20 matches. I had created ML models with glmnet and random forest using TidyModels. This was what I had achieved glmnet : accuracy – 0.67 and sensitivity/specificity – 0.68/0.65 random forest : accuracy – 0.737...
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GooglyPlusPlus gets ready for ICC Men’s T20 World Cup
It is time!! So last weekend, I turned the wheels, moved the levers and listened to the hiss of steam, as I cranked up my Shiny app GooglyPlusPlus. The ICC Men’s T20 World Cup is just around the corner, and it was time to prepare for this event. This latest GooglyPlusPlus is current with the latest Intl. men’s T20 match data, give or take...
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IPL 2022: Near real-time analytics with GooglyPlusPlus!!!
It is that time of the year when there is “a song in the air, the lark’s on the wing, and the snail’s on the the thorn“. Yes, it is the that time of year when the grand gala event of IPL 2022 is underway. So, I managed to wake myself from my Covid-induced slumber, worked up my ‘creaking bones‘ and cranked up the GooglyPlusPlus machine...
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