Saturday, 15 March 2014

Is it game over if you lose more than 2 wickets in the powerplay?

I recently observed this conversation on twitter:

It immediately made me wonder if Aakash was correct. Do you lose if you are more than 2 wickets in the power play of a T20 International.

I decided to find out. I felt that it was probably best to only look at situations where a team had batted first, as there is not any external scoreboard pressure (or lack thereof) interfering with the batsmen's mind sets.

I looked at every match where there was a result inside 20 overs (I ignored matches that had ended in a super-over or bowl-off) and looked at how many wickets down the team were after 6 overs. I didn't count "retired hurt" as a wicket, despite there being a change of batsmen and the batting team losing momentum similar to when a wicket falls.

Once I did that I came up with some quite interesting numbers.

Wickets DownWinsLosesWinning %

It's fairly clear here that losing wickets early hurts the probability of winning. This is not really a surprise, often teams bat their best batsmen at the top, and the subsequent batsmen have to take fewer risks if there are not many wickets left above them. However while there are a lot of incidents of teams losing 1 or 2 wickets, our sample size is quite small for the other number of wickets. I've graphed it, adding in a 95% confidence interval. This indicates what range we can expect the actual winning probability to lie in per wicket loss: The shorter the line, the more reliable the data.

We can clearly see the trend here. But we also notice the huge gap between being 2 down and being 3 down. There does seem to be a difference between losing 2 wickets or losing more than 2 wickets.

Accordingly I broke it down into 3 groups. Less than 2 wickets, 2 wickets or More than 2 wickets. Here's how that looks:

Roughly teams win two thirds of the matches where they lose less than 2 wickets, half of the matches where they lose two wickets and about a quarter of the matches where they lose more than 2 wickets.

I also broke it down further by team, and this holds true for almost every team. The only team that has won more than half of their matches when batting first and losing more than 2 wickets in the power play is Ireland. (Interestingly Ireland has the 4th best winning record of any team batting first, and then they are not far behind Pakistan, Sri Lanka and South Africa).

Sri Lanka win just under 80% of t20's when they lose 2 or less wickets in the power play, but 20% when they lose 2 or more wickets. England win just over 60% if they keep their wickets in hand, but only 20% when they lose 3 or more in the power play.

With the World T20 getting underway, how the teams approach the first 6 overs could be a fascinating thing to keep an eye on.

Sunday, 9 March 2014

Who are the most reliable 6 hitters

I noticed that the ICC have set up a new game, where you need to pick a player who is going to hit a 6.

This is an interesting option, as there are not many stats out there for how reliable batsmen are at hitting 6's. We know how many 6's a player has hit, but how regularly they hit them is another issue. For example, Aaron Finch has hit 21 sixes in the 9 matches he has played in the last 2 years. However those 21 sixes came in just 4 innings. In the other 5 matches he didn't hit any. Once he gets going he really starts to pepper the boundary. In comparison, Ziaur Rahman from Bangladesh has hit 10 sixes in the 11 matches he's played in that time. However he's hit those 10 sixes in 6 matches, meaning there are only 5 that he hasn't hit a six in. In other words Finch has hit more sixes per match, but Rahman is significantly more reliable.

As the ICC game is about either hitting a six or not, the most important stat is their reliability, not their sixes per match.

To help out anyone who is playing that game, I've compiled a list of the 6 hitting reliability of players who had played 5 or more matches in the last 2 years. I've listed everyone who has hit a 6 in 40% or more of the matches.

If you want to join my league - here's the link.

PlayerMatchesSixesInnings with a 6P(hits a 6)
SE Marsh (Aus)55480%
DR Smith (WI)916666.7%
Yuvraj Singh (India)1121763.6%
MDKJ Perera (SL)1114763.6%
AM Rahane (India)54360%
SR Watson (Aus)1430857.1%
RR Patel (Kenya)1417857.1%
MJ Guptill (NZ)1415857.1%
HD Rutherford (NZ)79457.1%
MN Waller (Zim)75457.1%
Gulbadin Naib (Afg)1112654.5%
Ziaur Rahman (Ban)1110654.5%
MEK Hussey (Aus)118654.5%
Mushfiqur Rahim (Ban)1311753.8%
BB McCullum (NZ)1726952.9%
KA Pollard (WI)1725952.9%
DJ Bravo (WI)19181052.6%
MN Samuels (WI)1626850%
MJ Lumb (Eng)1213650%
R Gunasekera (Can)84450%
JL Ontong (SA)66350%
MW Machan (Scot)64350%
CH Gayle (WI)1526746.7%
DA Warner (Aus)1522746.7%
LMP Simmons (WI)1112545.5%
MR Swart (Neth)1112545.5%
DA Miller (SA)117545.5%
AD Hales (Eng)2018945%
AJ Finch (Aus)921444.4%
Ahmed Shehzad (Pak)1614743.8%
Mahmudullah (Ban)1412642.9%
Mohammad Shahzad (Afg)1411642.9%
Asghar Stanikzai (Afg)75342.9%
LJ Wright (Eng)1920842.1%
DT Johnston (Ire)129541.7%
Shakib Al Hasan (Ban)127541.7%
Mohammad Hafeez (Pak)25201040%
GJ Bailey (Aus)2016840%
F du Plessis (SA)1511640%
RS Bopara (Eng)1010440%
NJ O'Brien (Ire)52240%

Thursday, 6 March 2014

Who should win the NZ cricket awards

I was asked by Tony Veitch to put together some stats for the different awards on offer for the New Zealand Cricket Awards tonight.

I could have just brought up a list of averages, but that's really not the CricketGeek style, so I decided to delve into things a little more closely.

One of the difficult things in cricket statistics is to compare bowling success with batting success. For example, which is better taking 5/84 or scoring 172? We need a device to compare the two disciplines.

I decided to compare each player's year with the historical averages for their position. For example, for batting I compared the batting average with year end batting averages throughout history. I had a cut off of 10 innings, as making a cut off much higher than that excludes too many players, as most teams play less than 10 tests per year. I then compared a player's average to the historical average of averages, and the standard deviation of averages to generate a z-score. (For more on Z-scores, see This NFL blog post)

I used batting average and bowling average for test cricket, as really what we care about is scoring runs and taking wickets. I wasn't totally happy with the results, as there was no advantage for the players who had maintained a high standard over a number of games, rather than just one. (James Neesham, for example, averaged 171 this season, but only over one match).  I first filtered out anyone who hadn't either batted in 10 matches or who had bowled less than 100 overs. Then I multiplied the z-score by the square root of the number of innings that they had applied their skill in, in order to get a fairer list. It only caused a couple of positional changes, but the new lists looked more appropriate.

Here's the test lists.

Player - SkillAverageRanking
LRPL Taylor - batting81.6012.3
BB McCullum - batting52.735.0
TG Southee - bowling20.073.8
TA Boult - bowling22.363.6
KS Williamson - batting47.213.4
BJ Watling - batting42.272.0
N Wagner - bowling30.421.1
CJ Anderson - bowling30.541.0
CJ Anderson - batting32.70-0.3
TA Boult - batting32.25-0.4

I would give the award to Ross Taylor. He scored 816 runs at an average of 81.60. He past 50 in half of his innings. McCullum, Southee, Boult and Williamson all had great years, but Taylor's average really makes his numbers stand out.

Next I looked at the ODI lists.

Here I decided to use the batting and bowling index developed by S Rajesh from Cricinfo (and me separately). Again I compared the players index to the historical data.

Here's the list:

Player - SkillIndexRanking
CJ Anderson - batting 84.4816.1
LRPL Taylor - batting 43.776.9
MJ Guptill - batting 44.226.4
KS Williamson - batting 39.044.7
MJ McClenaghan - bowling 23.871.1
NL McCullum - batting 26.230.9
JDS Neesham - bowling 23.690.8
CJ Anderson - bowling 24.850.7
KD Mills - bowling 25.970.7
L Ronchi - batting 22.93-0.1

Again a batsman takes the title. This, however was not particularly surprising. Anderson was immense with the bat, and generally the games were played on high-scoring pitches, which don't really flatter bowling statistics.

For the T20 award I used batting index, but my own metric for bowling. In a previous post I showed how each wicket worked out to roughly 5 runs in a t20. Accordingly we can take 5 runs off a bowler's total for every wicket they have taken. They then get a modified run rate. I used this to compare the NZ players' years to the historical data. This is a little less relevant, as there is not a lot of historical data (about 1/10 the quantity of test and ODI information) and also New Zealand only played 6 matches, so the sample size is very small.

Here is the list:

Player - SkillIndex/Modified run rateRanking
L Ronchi - batting221.1114.7
BB McCullum - batting101.084.1
AF Milne - bowling2.752.9
AP Devcich - batting73.341.7
C Munro - batting60.041.5
JDS Neesham - bowling5.000.5
JD Ryder - batting44.020.0
NL McCullum - batting42.25-0.1
NL McCullum - bowling5.64-0.3
HD Rutherford - batting40.02-0.3

Luke Ronchi is a bit of a surprise here, but I remember looking up his stats and being surprised as to how effective he has been in t20s recently. During the course of the year he averaged 133 at a strike rate of 166. Those are quite ridiculous numbers.

The last major prize left is the Sir Richard Hadlee Medal, for the best overall. For me that goes to Brendon McCullum. He managed to attract the attention of the whole nation with his 300, and he also captained the side particularly well across all the formats. There would be a fair argument for Taylor and Anderson, but for me, McCullum needs to be acknowledged some how, and that award seems appropriate.

Who would you give the overall award to?