IPL at halfway

The match between Kolkata Knight Riders and Royal Challengers Bangalore was the 28th match, and represented the halfway point in this year's edition of the IPL. 

Every team has played every other team once, and there have been some interesting patterns emerge. I'm going to look at a few of those in this article.

The most obvious pattern is that teams have won more often by batting first than by chasing. This is somewhat unusual. In most T20 competitions the toss doesn't make much difference, and generally it's better to field first.

This pattern hasn't really been seen in other competitions, where the result has all been within the expected margin of error.

The most recent BBL was slightly biased towards batting first, and the CPL and PSL were similarly biased towards bowling first, but the difference in the IPL has been much more dramatic. If we were looking at throwing a coin multiple times, there would be a 12% chance of getting a result as extreme as the BBL and a 20% chance of getting a result as extreme as the CPL one.

The probability of getting as extreme a difference as this year's IPL from just randomness is less than 3%. Using technical language we can say that batting first makes a statistically significant difference to a team's probability of winning.

At the start of the tournament, pretty much every captain chose to field. Only one brave soul (David Warner) chose to bat first in the first 13 matches. However, since then teams have chosen to bowl first in all but 3 matches, and in 8 of the last 9. 

When teams have chosen to bat first, they've only won twice. That's a winning record of just 13.3%. When teams have chosen to field first, they've done much better - winning 7 out of 13. The best outcome at the toss seems to be to lose it, and have the opposition captain decide to field.

Breaking it down by location is interesting too. In Abu Dhabi, there is no clear advantage to batting first. At that ground the chasing team has won 4 out of the 10 matches. At the other two grounds, however, it is a different story. At Sharjah the chasing team has won only once out of 6, while at Dubai the chasing team has won twice out of 12. It's hard to know why this is, and it will be interesting to see if it continues throughout the tournament.

After about a quarter of the tournament was done, I noticed that there seemed to be a pattern that batsmen who turned the strike over quickly had a bigger impact on their team's chance of winning than players who scored extra boundaries, although I wondered if that was just a statistical anomaly from a small dataset.

It seems that it was just a product of a small dataset. Now that there's more data, it seems that neither activity rate nor boundary rate on their own from an individual batsman make a significant difference. They both seem to help - teams win more often when their batsmen score more boundaries and more run runs, but neither seems to explain enough to discount the other one anymore.

There is a noticeable difference in scoring rates of batsmen at the three grounds. They tend to score much quicker at Sharjah (probably due to the short boundary) than they do at the other grounds.

An interesting development is that recently teams have found it more difficult to turn over the strike at Dubai than at the other two grounds. 

The median strike rates for innings over 30 at each ground is:

This leads to a suggested good team score at each ground of 174,176 and 196 respectively.

Those are the team scores equivalent to an average set batsman batting the whole innings. I find that a good guide to reliable winning targets at grounds. They're possibly slightly high at the moment, due to the awful record of chasing sides, but that may change as the tournament progresses.

Looking at the bowling stats, I find it useful to group the attacks based on their styles.

This leads to this graph. It takes a while to understand, but the squares are all the pace bowlers combined and the triangles are all the spin bowlers combined.

It is possible to use these groupings to predict the success of the teams. The two key statistics to look at are the economy rate of spin bowlers and the strike rate of the pace bowlers.

Looking at these two statistics suggests that CSK are probably the team who have been underperforming the most with the bat, as their bowlers are doing a sufficient job to keep them in the matches.

Finally, I used the data to build a predictive model using logistic regression to assess how good the teams were. As every team has played each other exactly once, the basic model is fairly uninteresting, but the one where batting first is controlled for is much more interesting.

The difference in the coefficients of any two teams gives the log odds of the result for that match (and hence the probability can be calculated from it).

The batting advantage is added and subtracted from the teams. So for example if Mumbai bat first against RCB, they would have an expected value of 2.43 + 1.27, while RCB would have 2.04 -1.27. This means that for almost every match up, the team batting first would be favoured to win. The only exception is when Mumbai, Bangalore or Delhi are playing against Kings XI Punjab. There they would still be the favourites, even if batting second.

This model is only based on 28 matches, so is clearly not perfect. But it is an interesting guide to how well the teams have been playing, and I think somewhat informative.

Dominating

I don't often talk about my own cricket exploits on this page for the reason that this is normally reserved for elite cricketers, and I was anything but. In fact, it would be a great stretch to describe me as average, in reality I was no where near good enough to be described as average.

However, there was one batsman who really couldn't face me. It was like I turned into Shane Warne when I saw him at the other end. His name was John, and he was a reasonable quality batsman. Not the best I ever played with or against, but probably in the top 5-10% of guys that I had been on the field with. And yet I had the wood on him.

We played in a little competition every week where we would select captains every and they would pick their team using school yard rules. We played on a proper field, with proper equipment and every match was scored, but it wasn't part of an official competition. There were guys playing with us who had played top level club cricket, and other who would not have made the 6th grade sides. I was never first picked, but generally I was picked fairly quickly after John, by the opposite captain. 

John would often either open or bat at 3 or 4. I was normally the 4th or 5th bowler used, so he was often batting when I was given the ball. He was seldom batting at the end of that over. I had one tactic to John. I would bowl him a top-spinner on leg stump. He would almost always try and hit it out of the park, and get caught doing so. He would then kick over the stumps, say a lot of words that would get him fined in international cricket and/or throw his bat in anger at getting out to me again.

I managed to pick up a hat trick that season. He was the 3rd wicket. I got him with a top-spinner on leg stump, caught at short fine leg.

He found this very, very frustrating. Everyone else found it hilarious. 

What happened that season was a perfect storm of a flaw in his technique being exposed by one thing that I could do, combined with the psychological effect for both of us based on the experiences that we had had against each other. I felt like every ball was a wicket, and he felt like every ball was a chance for him to prove that I didn't have the wood on him. 

Match-ups have been a popular concept in cricket analytics, particularly for the players in the past few years. They want to know how well they match up against different players. Who have they been dominating, and who has the wood on them.

I was working on looking at something else, and generated a list of head to head match-ups over the past few years, and it made me wonder which match-ups were the most one sided.

These are from T20 matches since the start of 2017. They are taken from most of the matches in internationals, IPL, BBL, PSL, CPL and Natwest Blast (I don't yet have ball-by-ball data for every match played) and only feature match-ups that are more than 20 deliveries.

I found that the middle third of averages in the match-ups were between 25 and 50 (with a lot of infinite values, where a particular bowler had not dismissed that batsman) and the middle third of the strike rates were between 105 and 144. Looking at players where both values were at the respective third gave only 7 results for each.

Here are the 7 for each.

Most dominant batting match ups

There are two names appear three times there. Chris Jordan and Aaron Finch. Ahmed Shezhad vs Samuel Badree only makes the list by one run/one ball, so is probably a dubious addition, but the rest seem to clearly be a case of a batsman having the wood over their rival.

Going the other way, Sunil Narine is clearly able to get on top of some batsmen, and the Shadab Khan vs Kieron Pollard match-up is one that the big West Indian won't be too happy with.

There were 4 match-ups that only just missed out on this list. Babar Azam vs Ish Sodhi: average 25, strike rate 125; Babar Azam vs Carlos Brathwaite: average 22.5 strike rate 112.5, MS Dhoni vs Chris Jordan: average 15, strike rate 120 and Ahmed Shezad vs Imran Tahir: average 22, strike rate 110.

If they had been included, then Jordan, Shezad and Dhoni would have all featured on both lists. 

Babar Azam's slow strike rate comes to the fore here. Of the 12 bowlers that he has faced 20 or more balls from in the past 3 years, he's score at less than 7 rpo (116.67 strike rate) off 6 of them. 

Here's how he compares to others:

His median scoring rate against the bowlers he's faced the most often is below the average for all match-ups, and those that are above the median, are mostly not much above.

There's a risk with looking at match-ups of making big conclusions from very small sets of data. The strike rate and average can both change quite dramatically with one wicket or one six. But just because it can be misleading does not mean that it isn't interesting. For some of these, there will be a real phenomenon behind it, and so it is interesting to look at them and see if those battles are real in future. 

Solving the Super Over Situation

New Zealand have an issue with super overs. We play them much more than anyone else, and we're terrible at them.

We have played in 8 super overs in the past 12 years. We have lost 7 of them. There have only been 15 super overs in the history of international cricket. We play them ridiculously often, and we lose them ridiculously often.

Losing 7 out of 8 stops being bad luck, it start being something that needs to be dealt with.

Here's my solution: We play a single day domestic super over tournament on Waitangi Day every year.

We can either let association have a turn to host it, or pick one venue (possibly Whangarei for the proximity to Waitangi) to host it every year.

The day would work with every team playing a super over against every other team, (15 super overs) then semi-finals and a final.

It would take about 7 hours (shorter if there was quick hand overs between matches) - roughly the same as an ODI match, and could have a rugby 7's type festival feeling to it.

I can already hear the critics talking about shortening the game, and "what's next one ball matches" but this is an issue that needs to be addressed.

In most of those matches we should have won in regular time. We didn't generally get to a super over because we did well, and fought back. We almost invariably got into a super over because we were in a position to win the match, and did not manage to seal it.

Having our players playing those sort of pressure situations more often would tell us who is capable of handling that pressure. As such, we would want a variety of players involved. There should therefore be a rule that each bowler can only bowl in two matches, and each batsman can only be one of the three designated batsmen in three matches. That will mean that each team will have to use at least 3 bowlers and 6 batsmen. For the semi and final then they can pick whoever they want.

This seems to be the only option other than just hoping that we get better.

I'd rather do something, than nothing.

Over to you, New Zealand Cricket.

A new way to look at bowling economy rates for the IPL

Sunrisers Hyderabad had made a great start, but their innings had started to plateau. At 161/7 off 18 overs they had the opportunity to get a score of 190+, or, if things went really poorly 175. Andre Russell was running into bowl...

He bowled a very good over, removing Braithwaite before only conceding 7 in his final 5 balls. All thoughts of a big finish were gone.

A week later, the Sunrisers were in the qualification final, and things were not going well. After 8 overs they were on 54/4, going at less than 7 an over, and at serious risk of scoring less than 100.

Dwayne Bravo was the bowler this time. He bowled a wide, then a couple of deliveries that Yusuf Pathan managed to hit for 2 each, and ended with a couple of easy singles. It was an over where almost no pressure was put onto the batsmen. And yet, it only went for 7 runs, the same as Andre Russell's excellent over a week earlier.

There's something wrong with any statistic that rates those overs as being of the same value to the team, and yet that's exactly what the traditional Economy Rate does. 7 runs is 7 runs.

A closer look at Guptill's innings vs Sri Lanka

Yesterday, I witnessed one of the most unusual innings I've seen. Martin Guptill hit 58 off 34 balls opening the batting against Sri Lanka at the Bay Oval in Mt Maunganui.

It wasn't a particularly fast innings, nor a particularly slow one. It was a little faster than the average 50 in T20 internationals. (The median strike rate for 50's by openers in T20 internationals is 151.3, Guptill scored at 170.6. The upper quartile is 171.4, so Guptill's innings is in the second quartile). Here's a graph showing his innings compared to all fifties in T20I's scored by openers.

We can see that Guptill's innings doesn't really stand out from the pack. So why was it so interesting?

Bowling in the IPL

Last year I had a look at how much wickets cost in the IPL, and devised a formula to calculate the value of a bowler in a team. I used that formula in a number of other cases throughout last year, and it seemed to bring some fairly sensible results each time, so I've decided to try it again with this years IPL as the first stage draws to a close.

Here is the top 15 bowlers, with their modified run rates. This takes into account the benefit that they have provided to the other bowlers in the team through the wickets that they have taken. I limited it to who had bowled at least 10 overs.

	Name	Team	Overs	Wickets	Modified Run Rate
	Sandeep Sharma	Punjab	11	7	2.45
	VR Aaron	Bangalore	14.5	8	2.97
	SP Narine	Kolkata	20	9	3.10
	YS Chahal	Bangalore	19	7	3.47
	SL Malinga	Mumbai	15.3	7	3.61
	AR Patel	Punjab	18	6	4.06
	MM Sharma	Chennai	15.5	8	4.17
	KW Richardson	Rajasthan	15	6	4.40
	PV Tambe	Rajasthan	20	7	4.60
	R Dhawan	Punjab	13.2	4	4.65
	R Ashwin	Chennai	17.5	5	4.65
	B Kumar	Hyderabad	15.3	6	4.71
	MA Starc	Bangalore	20	7	4.80
	IC Pandey	Chennai	15	3	4.87
	R Bhatia	Rajasthan	16	6	4.94

Somewhat unsurprisingly the top name in the list is the current rising star of the IPL - Sandeep Sharma.

His heady medium pace bowling has been a big part of the success that Kings XI have enjoyed. Often medium pacers can enjoy good results in limited overs cricket through consistency, But Sharma offers something more than that.

Right arm inswinger is a style of bowling that is normally only seen at the junior grades. Top senior batsmen normally develop a technique that allows them to avoid being dismissed by it, and then they can just wait for the inevitable bad delivery that slips into the pads and can be dispatched.

Sharma has managed to bowl consistently enough that he has only been hit for one leg-side boundary in 11 overs. If players are having to look on the off side for their runs from an inswing bowler then they are at risk of leaving the gate open.

If Sharma manages to continue to bowl as consistently, he could be potentially be a real force, not just for Kings XI, but also for India. He could be particularly useful in the World Cup in Australia/New Zealand where the ability to move the ball in the air is a real asset.

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 Down	Wins	Loses	Winning %
0	41	18	69.5%
1	74	48	60.7%
2	52	51	50.5%
3	11	36	23.4%
4	5	10	33.3%
5	0	3	0%

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.

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.

Player	Matches	Sixes	Innings with a 6	P(hits a 6)
SE Marsh (Aus)	5	5	4	80%
DR Smith (WI)	9	16	6	66.7%
Yuvraj Singh (India)	11	21	7	63.6%
MDKJ Perera (SL)	11	14	7	63.6%
AM Rahane (India)	5	4	3	60%
SR Watson (Aus)	14	30	8	57.1%
RR Patel (Kenya)	14	17	8	57.1%
MJ Guptill (NZ)	14	15	8	57.1%
HD Rutherford (NZ)	7	9	4	57.1%
MN Waller (Zim)	7	5	4	57.1%
Gulbadin Naib (Afg)	11	12	6	54.5%
Ziaur Rahman (Ban)	11	10	6	54.5%
MEK Hussey (Aus)	11	8	6	54.5%
Mushfiqur Rahim (Ban)	13	11	7	53.8%
BB McCullum (NZ)	17	26	9	52.9%
KA Pollard (WI)	17	25	9	52.9%
DJ Bravo (WI)	19	18	10	52.6%
MN Samuels (WI)	16	26	8	50%
MJ Lumb (Eng)	12	13	6	50%
R Gunasekera (Can)	8	4	4	50%
JL Ontong (SA)	6	6	3	50%
MW Machan (Scot)	6	4	3	50%
CH Gayle (WI)	15	26	7	46.7%
DA Warner (Aus)	15	22	7	46.7%
LMP Simmons (WI)	11	12	5	45.5%
MR Swart (Neth)	11	12	5	45.5%
DA Miller (SA)	11	7	5	45.5%
AD Hales (Eng)	20	18	9	45%
AJ Finch (Aus)	9	21	4	44.4%
Ahmed Shehzad (Pak)	16	14	7	43.8%
Mahmudullah (Ban)	14	12	6	42.9%
Mohammad Shahzad (Afg)	14	11	6	42.9%
Asghar Stanikzai (Afg)	7	5	3	42.9%
LJ Wright (Eng)	19	20	8	42.1%
DT Johnston (Ire)	12	9	5	41.7%
Shakib Al Hasan (Ban)	12	7	5	41.7%
Mohammad Hafeez (Pak)	25	20	10	40%
GJ Bailey (Aus)	20	16	8	40%
F du Plessis (SA)	15	11	6	40%
RS Bopara (Eng)	10	10	4	40%
NJ O'Brien (Ire)	5	2	2	40%

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 - Skill	Average	Ranking
LRPL Taylor - batting	81.60	12.3
BB McCullum - batting	52.73	5.0
TG Southee - bowling	20.07	3.8
TA Boult - bowling	22.36	3.6
KS Williamson - batting	47.21	3.4
BJ Watling - batting	42.27	2.0
N Wagner - bowling	30.42	1.1
CJ Anderson - bowling	30.54	1.0
CJ Anderson - batting	32.70	-0.3
TA Boult - batting	32.25	-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 - Skill	Index	Ranking
CJ Anderson - batting	84.48	16.1
LRPL Taylor - batting	43.77	6.9
MJ Guptill - batting	44.22	6.4
KS Williamson - batting	39.04	4.7
MJ McClenaghan - bowling	23.87	1.1
NL McCullum - batting	26.23	0.9
JDS Neesham - bowling	23.69	0.8
CJ Anderson - bowling	24.85	0.7
KD Mills - bowling	25.97	0.7
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 - Skill	Index/Modified run rate	Ranking
L Ronchi - batting	221.11	14.7
BB McCullum - batting	101.08	4.1
AF Milne - bowling	2.75	2.9
AP Devcich - batting	73.34	1.7
C Munro - batting	60.04	1.5
JDS Neesham - bowling	5.00	0.5
JD Ryder - batting	44.02	0.0
NL McCullum - batting	42.25	-0.1
NL McCullum - bowling	5.64	-0.3
HD Rutherford - batting	40.02	-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?

2013 Champions League T20 Net Run Rate calculator

Here's are some Net Run Rate calculators. I've tried to make them so that only relevant cells can be edited, but it's a shared document so please don't vandalise it if your team loses.

Group A


Group B

How good was Gayle's demolition of Pune

Chris Gayle, picture from RCB's Flickr stream

Chris Gayle played one of the most incredible innings on Tuesday night. His 175* (66) broke all sorts of records, both for the IPL and for t20 and cricket in general.

He is without question an incredible player, and is an absolute phenomenon in the IPL.

But how good was that innings in the context of the rest of the IPL? I heard some people say that it was meaningless, because the pitches and grounds in India are so easy to score runs on, and the bowlers in the IPL aren't up to much. I heartily disagree with both of these statements, but the only real way to look at the innings is to look at how others have gone in similar conditions.

To do this I'm using my modified batting index for each innings. This system rewards scoring runs, and being not out, but adjusts it for the number of deliveries faced. To put these scores in context an index of 100 would be 70*(49) or 60(33). It doesn't take into account the context of the match, so there can be some high scores that cost a team, and low ones that win a match, but I think it's better than just looking at the runs scored or the strike rate by themselves.

Here's the top 20 innings in the IPL so far this year:

Name	Score	For	Against	At	Index
CH Gayle	175* (66)	RCB	Warriors	Bangalore	464.02
V Kohli	93* (47)	RCB	Sunrisers	Bangalore	184.02
SR Watson	101 (61)	Royals	Super Kings	Chennai	158.95
V Sehwag	95* (57)	Daredevils	Mum Indians	Delhi	158.33
DA Miller	80* (41)	Kings XI	Warriors	Mohali	156.1
CH Gayle	92* (58)	RCB	Mum Indians	Bangalore	145.93
KD Karthik	86 (48)	Mum Indians	Daredevils	Mumbai	145.13
CH Gayle	85* (50)	RCB	KKR	Bangalore	144.5
MEK Hussey	88 (51)	Super Kings	Royals	Chennai	143.22
MEK Hussey	86* (54)	Super Kings	Kings XI	Mohali	136.96
RG Sharma	62* (32)	Mum Indians	Warriors	Mumbai	120.13
AB de Villiers	64 (32)	RCB	Super Kings	Chennai	118
RG Sharma	73 (43)	Mum Indians	Daredevils	Delhi	115.44
RG Sharma	74* (50)	Mum Indians	Daredevils	Mumbai	109.52
Mandeep Singh	77* (58)	Kings XI	Warriors	Mohali	102.22
AB de Villiers	31 (8)	RCB	Warriors	Bangalore	100.75
DA Warner	77 (56)	Daredevils	Royals	Delhi	99
LJ Wright	34 (10)	Warriors	Kings XI	Mohali	98.6
SPD Smith	39* (16)	Warriors	Super Kings	Chennai	95.06
EJG Morgan	47 (21)	KKR	Sunrisers	Kolkata	94

There's a significant distance between Gayle and the next best innings.

Another way to look at it is to look at what percentage of Gayle's index each innings got. Here's the top 10:

Name	Score	Gayle points
CH Gayle	175* (66)	100
V Kohli	93* (47)	40
SR Watson	101 (61)	34
V Sehwag	95* (57)	34
DA Miller	80* (41)	34
CH Gayle	92* (58)	31
KD Karthik	86 (48)	31
CH Gayle	85* (50)	31
MEK Hussey	88 (51)	31
MEK Hussey	86* (54)	30

How about how it stacks up against all T20 innings anywhere:

Name	Score	For	Against	At	Index
CH Gayle	175* (66)	RCB	Warriors	Bangalore	464.02
LP van der Westhuizen	145 (50)	Namibia	Kenya	Windhoek	406
GR Napier	152* (58)	Essex	Sussex	Chelmsford	398.34
BB McCullum	158* (73)	KKR	RCB	Bangalore	341.97
CL White	141* (70)	Somerset	Worcs	Worcester	284.01
A Symonds	112 (43)	Kent	Middlesex	Maidstone	278.7
M Vijay	127 (56)	Super Kings	Royals	Chennai	276.68
ST Jayasuriya	114* (48)	Mum Indians	Super Kings	Mumbai	270.75
SB Styris	100* (37)	Sussex	Gloucs	Hove	270.27
RE Levi	117* (51)	South Africa	New Zealand	Hamilton	268.41
CG Williams	116 (48)	Namibia	Scotland	Windhoek	268.25
CH Gayle	128* (62)	RCB	Daredevils	Delhi	264.26
DA Warner	135* (69)	NSW	Super Kings	Chennai	264.13
H Davids	112* (48)	Cape Cobras	Warriors	Cape Town	261.33
KJ O'Brien	119 (52)	Gloucs	Middlesex	Uxbridge	260.88
Ahmed Shehzad	113* (49)	Barisal	Rajshahi	Dhaka	260.59
A Symonds	117* (53)	Chargers	Royals	Hyderabad (Deccan)	258.28
YK Pathan	100 (37)	Royals	Mum Indians	Mumbai (BS)	256.76
CL White	116* (53)	Somerset	Gloucs	Taunton	253.89
AC Gilchrist	109* (47)	Chargers	Mum Indians	Mumbai	252.79

And then the "Gayle Points" for the top 20 innings of all time:

Name	Score	Gayle points
CH Gayle	175* (66)	100
LP van der Westhuizen	145 (50)	87
GR Napier	152* (58)	86
BB McCullum	158* (73)	74
CL White	141* (70)	61
A Symonds	112 (43)	60
M Vijay	127 (56)	60
ST Jayasuriya	114* (48)	58
SB Styris	100* (37)	58
RE Levi	117* (51)	58
CG Williams	116 (48)	58
CH Gayle	128* (62)	57
DA Warner	135* (69)	57
H Davids	112* (48)	56
KJ O'Brien	119 (52)	56
Ahmed Shehzad	113* (49)	56
A Symonds	117* (53)	56
YK Pathan	100 (37)	55
CL White	116* (53)	55
AC Gilchrist	109* (47)	54

How good was Gayle's innings? It was about 14% better than the next best innings ever. That's how good it was.

24 IPL moneyball players, and one other

The IPL is almost here, and a lot of people will be playing the fantasy competitions.

I've been working on developing a "Moneyball" type system of analyzing cricket statistics to make sensible predictions about how well players will go at the next level. My system is not nearly finished, but I've used some of the things that I've learned to have a look at some of the players who I didn't know much about in the IPL.

As the system isn't completed yet, I can't give too much justification, other than to say here are the players:

Name	Team
Imtiaz Ahmed	CSK
Ankit Rajpoot	CSK
Manprit Juneja	DD
Kedar Jadhav	DD
Sidarth Kaul	DD
Shahbaz Nadeem	DD
Pawan Negi	DD
Siddharth Chitnis	KXIP
Debabrata Das	KKR
Iqbal Abdulla	KKR
Laxmi Shukla	KKR
Amitoze Singh	MI
Yuzvendra Chahal	MI
Sushant Marathe	MI
Stuart Binny	RR
Ajit Chandila	RR
Mayank Agarawal	RCB
Arun Karthik	RCB
Karun Nair	RCB
Vijay Zol	RCB
Anand Rajan	SH
Sachin Rana	SH
Eklavya Dwivedi	PWI
Ali Murtaza	PWI

There is one other player that I would add into the list as players who I think might succeed, and that's Harmeet Singh from Rajastan Royals. I add him in, because I saw him play, and thought he was phenomenal, despite his numbers not being particularly impressive.

A number of these players my never play a game, but those that do are probably going to be worth watching. They have all shown (to me) that they are likely to be able to step up and succeed at the next level.

CricketGeek Player Profile: James Harris

James Harris

I recently had an interesting email arrive advising me to have a look at the newest addition to the English squad: the young Welsh bowler, James Harris.

When I first looked at his numbers they were not particularly impressive. However the English selectors have recently made a habit of picking players with poor domestic records, and those players being a real success. (for more info on that see this post on the The Declaration Game.) So I felt his numbers demanded looking at more closely.

As someone who occasionally enjoys cricket betting I like looking out for some patterns in players performance to see if there is anything that can inform my betting.

The first thing I looked at with Harris was to see if there was a positive trend in his performances. He started playing domestic cricket when he was very young, so I assumed that he would be improving. However, if anything, his performances have been getting worse as the batsmen have figured him out. Here is a graph of his 15 innings average and economy rates in T20 cricket.

These are hardly the sort of thing that suggest that he is going to set the world on fire. However sometimes there is more to a player than their average.

There has been a distinct pattern to his good performances and his bad ones. He is outstanding with the new ball, but not unconvincing with the old one. For example in the English PPP tour to India he took 3/19 off 7 overs when he opened the bowling (in a 50 over match), but 0/42 off 4 in the match where he came in later on.

Roughly 2/3 of his wickets have been against top 3 batsmen, and more than half of his wickets have been taken in the first 5 overs of a match. As a result he is far more valuable than his raw figures indicate, particularly in a team with a couple of batting all-rounders, who would allow his captain the luxury of only bowling him when he was most effective (at the start of the innings).

If I was betting on a match involving Harris, I would probably look to bet on him going for few runs early in the innings, but bet on him going for a lot at the end of the innings.

Additional research by Celia Roche

2012 Activity rates

A batsman's activity rate is the runs scored per delivery not hit to the fence.

For example two batsmen have 10 off 10. One has hit two 4's, two singles and faced out 6 dot balls. He would have an activity rate of 0.25 because he hit 2 runs off the 8 balls that he didn't hit a boundary off. The second batsman hit one 4, two 2's and two singles. He would have an activity rate of 0.67 because he hit 6 runs off 9 balls that didn't go to the fence.

Here are the batsmen with the highest activity rates:

Test Matches (min 100 balls faced, average of 20)

Player	Matches	Boundry Runs	Run Runs	Activity Rate
NLTC Perera (SL)	2	54	56	0.434
MG Johnson (Aus)	2	28	74	0.416
Shakib Al Hasan (Ban)	2	104	101	0.391
V Sehwag (India)	9	322	183	0.368
MA Starc (Aus)	4	88	56	0.364
RJ Harris (Aus)	4	46	83	0.362
MJ Clarke (Aus)	11	792	803	0.361
DA Warner (Aus)	11	446	342	0.361
Mahmudullah (Ban)	2	80	89	0.353
RT Ponting (Aus)	9	232	368	0.341

This year the trend is that there are lots of Australians in the list, and particularly a lot of Australia bowlers. Two names that might surprise a lot of people are Warner and Sehwag. Sehwag certainly doesn't have a reputation for speed between the wickets, and does seem rather loathe to try for a 3, but he and Gambhir have made a real effort to step up their quick singles in the last year. It has certainly been shown out in Sehwag's numbers. Likewise Warner has scored almost as many runs by running as by hitting boundaries. His 50 at the MCG was remarkable for both the speed, but also for how well he ran between wickets. His 50 came up in 34 balls, but it only included four 4's and one 6. It meant that he had scored 28 runs off the 29 balls he didn't hit to the fence.

One Day Internationals (min 100 balls faced, average of 20)

Player	Matches	Boundry Runs	Run Runs	Activity Rate
AB de Villiers (SA)	13	276	369	0.695
Shakib Al Hasan (Ban)	4	110	127	0.672
GJ Maxwell (Aus)	4	60	64	0.66
AD Mathews (SL)	27	180	354	0.659
V Kohli (India)	17	398	628	0.63
DJ Hussey (Aus)	25	264	464	0.629
SK Raina (India)	17	204	288	0.623
R Ashwin (India)	16	44	91	0.619
EJG Morgan (Eng)	15	164	200	0.599
Sarfraz Ahmed (Pak)	8	24	61	0.598

Last year almost the whole list was made up of spin bowlers (which is unsurprising, given that spin bowlers are generally smarter (and better looking) than most other players). This year the spinners still make their presence felt. Shakib is the only player on the Test and ODI list.

Twenty20 Internationals (min 100 balls faced, average of 15)

Player	Matches	Boundry Runs	Run Runs	Activity Rate
AN Kervezee (Neth)	4	44	110	0.873
LRPL Taylor (NZ)	8	86	100	0.82
KC Sangakkara (SL)	10	94	103	0.78
DJ Bravo (WI)	10	128	132	0.776
JP Duminy (SA)	10	94	143	0.765
F du Plessis (SA)	7	102	90	0.763
SK Raina (India)	14	128	129	0.75
JC Buttler (Eng)	14	74	69	0.75
AD Hales (Eng)	10	188	155	0.745
MS Dhoni (India)	14	132	136	0.743

There was certainly a surprising name at the top of this list. Alex Kervezee was actually the highest averaging batsman in T20 Internationals too. Ross Taylor is also a surprise, as he had previously been someone who tended to score in multiples of 4. Suresh Raina is the only player in the top 10 for both ODI's and T20's.

The Block-Bash players:

At the other end of the spectrum are the players who specialise in blocking the good balls and cashing in on the bad ones. These players don't see a lot of value in singles, and prefer to get their runs in multiples of 4 or 6.

Test Matches (min 100 balls faced, average of 20)

Player	Matches	Boundry Runs	Run Runs	Activity Rate
AB Fudadin (WI)	3	60	62	0.17
F du Plessis (SA)	2	178	115	0.171
JL Pattinson (Aus)	4	72	31	0.173
Mohammad Ayub (Pak)	1	16	31	0.189
Mushfiqur Rahim (Ban)	2	66	41	0.19
DR Flynn (NZ)	6	174	153	0.199
SR Tendulkar (India)	9	220	137	0.199
Taufeeq Umar (Pak)	6	164	82	0.2
N Deonarine (WI)	6	116	102	0.204
MJ Guptill (NZ)	10	306	261	0.208

Suprisingly, Martin Guptill makes this list again this year, despite improving his activity rate by quite a margin. Generally this is a list of batsmen who are not in great form, and with an average in the twenties despite his obvious talent, this is probably a fair reflection. Daniel Flynn is also on the list, but this possibly has more to do with the way that bowlers have often been trying to get him out playing at wide balls, so have been bowling a 7th stump line to him, trying to get him to give in and have a slash at one. It's hard to hit a single off a ball that you really shouldn't be playing at.

One Day Internationals (min 100 balls faced, average of 20)

Player	Matches	Boundry Runs	Run Runs	Activity Rate
AB Barath (WI)	2	60	23	0.256
CH Gayle (WI)	11	252	93	0.279
CS Baugh (WI)	5	34	30	0.297
DM Bravo (WI)	11	104	113	0.298
MR Swart (Neth)	2	60	34	0.306
KJ O'Brien (Ire)	4	54	35	0.307
Anamul Haque (Ban)	5	110	85	0.343
Imran Farhat (Pak)	5	104	70	0.348
Mohammad Nabi (Afg)	5	62	67	0.358
MN Samuels (WI)	17	248	234	0.373

There are a lot of West Indians in this list. However, if I could hit the ball like Chris Gayle, I probably wouldn't bother running too much either.

Twenty20 Internationals (min 60 balls faced)

Player	Matches	Boundry Runs	Run Runs	Activity Rate
DR Smith (WI)	7	152	47	0.412
J Charles (WI)	11	176	75	0.434
C Kieswetter (Eng)	11	108	72	0.474
Imran Nazir (Pak)	9	126	50	0.476
CH Gayle (WI)	11	270	98	0.492
RE Levi (SA)	13	170	66	0.5
RJ Nicol (NZ)	17	194	121	0.515
WTS Porterfield (Ire)	13	148	64	0.516
Mohammad Ashraful (Ban)	6	60	58	0.527
KJ O'Brien (Ire)	13	78	64	0.533

It turns out that being a West Indian opener means that you are unlikely to be very good at running between wickets. Johnson Charles' numbers are even worse than last year when he had the lowest activity rate of any player. It's just that this year another West Indian has been even lazier than him. Rob Nicol is an interesting name there, because he's generally a very busy player in domestic cricket.