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Data and code for Fairly Random: The Effect of Winning the Toss on Winning the Match. Journal of Sports Analytics. 2023.

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Fairly Random: The Effect of Winning the Toss on Winning the Match

We analyze data from over 35,000 first-class men's cricket matches played over the course of more than one hundred fifty years---a near census of the relevant population---to estimate the effect of winning the toss on winning the match. We estimate the average effect of winning the toss on winning the match to be 1.8 percentage points: toss winners win 39.2% of the time and lose 37.4% of the time, with the remaining being drawn (mainly due test and first-class cricket). The effect of winning the toss is largest in tests, where it is 4.9 percentage points, and is lowest in ODIs and T20s, where it is essentially zero. That being said, in ODIs and T20s that are day/night matches, the effect of winning the toss is 3.3 percentage points, whereas in day-time matches the effect is a precise zero.

Scripts

  1. Helper Functions The file contains some helper functions that are sourced in the analysis script.

  2. Data preparation. Reads in data/rankings_odi.csv, data/rankings_test.csv and data/grounds.csv and produces data/regression_sample.rds

  3. Analysis Reads in data/regression_sample.rds and produces materials in the output folder.

  4. We explain the issues around using toss as IV at length in the manuscript. And that is why none of the analyses make it to the ms. But if you want to see how IV analysis would run, check out scripts/03_iv.R which produces materials in output/iv/ folder.

Manuscript

Authors

Apoorva Lal, Derek Willis, Gaurav Sood, and Avidit Acharya

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Data and code for Fairly Random: The Effect of Winning the Toss on Winning the Match. Journal of Sports Analytics. 2023.

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