There are currently two pages available on this website which contain advanced statistics for batsmen and bowlers, based on the records of my ball-by-ball database, which covers over 1 million deliveries in T20 cricket. Each page houses a table powered by Tableau that allows the user to interact with the data and see which players my system ranks highly
Read MoreRohit Sharma is the captain and assumed best batsman of the Mumbai Indians. He seems likely to bat at number 3 or 4 this season, unchanged from last year, when Buttler and Patel were generally preferred as the opening pair. Whilst those two are now gone, Mumbai did acquire another well-established opener at auction in the form of Evin Lewis, Ishan Kishan may also get the chance to impress
Last year, Sharma suggested that “probably three, four is the best position” for him but the stats emphatically disagree. In 52 matches as an opener, he averages 39.5 runs at a strike rate of 142. Both numbers drop noticeably when he arrives between 4-6, falling to an average of 32.4 runs at 132 (in 130 matches)
Read MoreT20 cricket needs new metrics. Batting averages and strike rates are out-dated in a game where strategies change ball-by-ball. White Ball Analytics discusses what these new metrics could look like and how they needed to be communicated well to influence decision-makers
Read MoreIt has been a couple weeks since posting my thoughts on a single catch-all measure of player value. Here is the approach in action, my rankings of the top players globally, in terms of batting performance and bowling performance
Read MoreThis is the third post in a series, in which I outline my approach to assessing player value. This post walks-through an example and then adds a further three considerations on top of the ones explained previously: weighting, regression to the mean, and ageing
Read MoreThis is the second post in a series, in which I outline my approach to assessing player value. The first explains the overall objective: to measure the expected contribution of each player in runs. This post then details four main adjustments that I make to historic performances to remove any obvious biases in the data
Read MoreIn this and subsequent posts, I aim to explain my methods for T20 player evaluation. They are not set in stone. Any time I sit down to analyse a player, team, tournament, strategy, there is a decent chance that they will change. I would love to hear other people’s feedback and ideas. If nothing else, writing down my thoughts has forced me to be critical of my own work. Indeed, the methods changed several times even as I documented them
Read MoreMy last post used historic data from over 1,500 players to construct ageing curves that show how batting performances improves and declines with age. In this post we will see how these curves change depending on the players included in the analysis. In some cases, it reveals genuine differences between player types and, in other cases, potential limitations in what was originally quite a naive approach
Read MoreFor teams looking to acquire new players, having a solid understanding of their value is vital. Measuring past performance in T20 can be difficult and measuring future performance is even more challenging. One reason for this is that we need to account for the unrelenting passage of time: younger players improve and older players decline
Ageing curves allow us to understand the overall shape of a typical T20 batsman's career. This post walks through the methodology I have used to calculate an approximate ageing curve for T20 batsmen
Read MoreEven as a fairly well-informed fan, it can be hard to find stats in T20 that are as reliable and informative as batting and bowling averages in Test cricket. Mostly, I am guided by strike rates and economy but I still need to contextualise these due to variable scoring rates over the course of a T20 match, as we progress from the Powerplay, through the middle overs, and into the death overs
My aim in this article is to explore which statistics in T20 are most consistent and predictive indicators of future value. On this website, Runs Added and Win Probability Added are often used to evaluate performances but whilst they are good descriptive statistics, they may not be the best predictive statistics
Read MoreThe world's oldest T20 competition starts again on Friday. The Twenty20 Cup may have been around the longest, but it has since been surpassed by the rest of the world in viewership numbers, attendance, and sponsorship. The ECB have made moves to catch-up, investing a new city-based T20 competition by 2020 but, for now, it is almost certainly true that the T20 Blast also attracts fewer stars than its bigger rivals
Read MoreThe concepts of win probability in sports fascinates me. I use it frequently when trying to understand the value of players or the impact of events within a cricket match. Here I try to remove the black-box nature of my win probability models
Read More9 of the top 10 scores in T20 cricket have been posted by opening batsman. David Warner has often single handedly dragged Sunrisers Hyderabad to victories in the last two IPL seasons as an opening batsman. The average match will feature an opening batsman spending the most time at the crease and their performances stick most in the minds of fans
In contrast, the middle order batsman are often tasked with the dirty work: maximising their teams chances of winning from the situation they inherit when they come into the game. They must be versatile and their role could be wildly different from game to game
Read MoreIf you had asked a few years ago, Narine would have been one of my top two picks for best player in the IPL: Gayle with the bat, Narine with the ball. His performance with the ball has slipped in recent seasons but could he possibly have reclaimed his status as one of the most valuable players in T20 having re-invented himself as an all-rounder?
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