I haven’t blogged for the last two weeks – partly because life has been busy, but also because I’ve struggled to come up with anything to say that provides particular insights about individual BBL or WBBL matches that are being played. I will return to this, and will continue to post key stats about various matches on the Strike Rate twitter account.

In this post, I’m posting my analysis of ‘par scores’ for T20, and how they vary between the men’s and women’s game, and in different parts of the world. This is useful for understanding what sort of score can be expected in particular conditions.

Par scores are calculated as run rates, which can be converted into total scores by multiplying by 20. This is more useful than raw total scores, since not all innings last for the full 20 overs. When a team wins in the second innings, they often win with overs remaining, and thus their total score is less than their potential score if the match had been fully played out. Run rates are adjusted to assume that a team which loses all its wickets played the full 20 overs. So if a team is bowled out in 17 overs, the run rate is calculated over 20 overs, not 17.

To get a sense of a normal range, for each category I have included the first quartile, median and third quartile figures. 50% of scores lie between the first quartile and the third quartile.

Gender Result 1st quartile Median 3rd quartile
Men loss 5.90 6.90 7.80
Men tie 6.95 7.60 8.20
Men win 7.25 8.18 9.10
Women loss 4.21 5.10 5.95
Women tie 5.20 5.48 5.95
Women win 5.70 6.45 7.38

Remember – to translate these run rates into a full innings, multiply the figure by 20.

Here’s the same figures as a chart.

runrate_par1

For men’s T20, a median winning score is around 164 runs, while a median losing score is more like 138. For 82 matches which ended in a tie, 50% of scores were between 139 and 164. It’s worth noting that 25% of losing scores are 156 or over, while 25% of winning scores are under 145.

For women’s T20, the whole range of scores is lower. The median winning score is around 129, while the median losing score is 102, and there is a big overlap between winning scores and losing scores.

Below the fold I’ll break this data down by year and host country.

Next, let’s examine the same figures based on host country. For men’s T20, I’ve included the thirteen countries where 25+ T20 matches have been played.

runrate_par2.png

Host country # of matches 1st quartile Median 3rd quartile
Australia 249 6.95 7.85 8.80
Bangladesh 200 6.49 7.53 8.55
England 1128 6.87 7.85 8.85
India 1028 6.50 7.50 8.50
Ireland 41 5.71 6.52 7.34
Namibia 36 6.10 7.85 9.21
New Zealand 267 7.15 8.05 9.08
Pakistan 425 6.41 7.50 8.54
South Africa 599 6.45 7.35 8.25
Sri Lanka 293 6.30 7.35 8.37
United Arab Emirates 225 6.10 6.93 7.90
West Indies 252 5.89 6.96 8.00
Zimbabwe 108 6.20 7.24 8.4

There’s not a great deal of variety – Namibia has the widest variety but also has the smallest number of matches – only 36. At the other end, Ireland’s scores tend to be lower, which likely reflects that most T20 matches played in that country were between different associate countries.

Now let’s get the same figures for the women. I included any country with over 20 matches in the database. India, Ireland, Pakistan and Thailand only just qualified with less than 30 matches each. Every single match in Thailand was from the 2015 women’s World Twenty20 qualifier.

runrate_par3.png

There’s a bit more diversity amongst the women, which could reflect the smaller sample size, and the fact that I have a complete set of domestic data for some countries, and no data for others.

Thailand has the lowest scores – three quarters of scores were lower than three quarters of scores in Australia. This might say more about the types of matches played there, rather than the grounds.

Australia, England and New Zealand stand out with the highest scores – all three have medians over 6 – the only other country with such a high median is India, but that’s based on only 21 matches and no domestic data.

On the other hand, we have a decent amount of data on Sri Lankan women’s cricket, and scores tend to be much lower there, with a median run rate of 5 runs per over (which translates to an innings of 100).

Host country # of matches 1st quartile Median 3rd quartile
Australia 274 5.44 6.21 7.10
Bangladesh 34 5.04 5.68 6.40
England 73 5.00 6.10 7.00
India 21 5.38 6.28 6.71
Ireland 27 4.09 5.02 6.46
New Zealand 154 5.10 6.06 6.80
Pakistan 22 4.49 5.14 5.73
South Africa 42 4.70 5.44 6.06
Sri Lanka 83 4.06 5.00 6.09
Thailand 23 3.86 4.82 5.25
West Indies 86 4.30 5.29 6.21

I’m going to return to par scores by analysing those scores for particular grounds in Australia

One other thing I want to mention is that I haven’t found any evidence of these par scores shifting over time. The following chart shows the men’s par scores by year – while they bounce around a little, the median has stayed between 7 and 8, with the first and third quartiles varying by about one run per over.

runrate_par4.png

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