Simulating T20 Matches: Pinching

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The debate on whether Sunil Narine should open is one of my favourite in T20 cricket. I stand resolutely on team ‘yes’… but standing on team ‘yes’ does not mean that I don’t still have doubt. It wouldn’t be a debate if I didn’t see merit to arguments on both sides. I have built a simulator that will play out T20 games ball-by-ball, thousands of times, so that we can see the impact of playing in a certain way, or with a certain line-up. This means that we can set up a game between the Kolkata Knight Riders and the Sunrisers Hyderabad (say) and simulate what would happen with Narine at different spots in the line-up

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Where should you play your best batsman?

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Rohit 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)

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T20 Player Value: Part III

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This 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

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T20 Player Value: Part II

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This 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

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Global T20 draft: Best picks

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This piece looks at some of the best picks on the second day of the Global T20 draft. A lot of different factors go into the draft process in any sport, and rational thought isn't always the most important. Here the aim is to identify the picks which give the most value in comparison to what was available at the time. Obviously, everybody mentioned here is likely to be a net contributor to their team but not everybody can select Chris Morris - salvaging an average player in the later rounds of the draft could be just as valuable

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Ageing Curves: Part II

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My 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

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Ageing curves: Part I

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For 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

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Predicting batting performance

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Even 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

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