New Zealand vs Australia: Head-to-Head

I've heard a number of commentators say that man-for-man, Australia have better players, but New Zealand is a better team. This strikes me as a peculiar thing to say, given that there's often no analysis included of individual head-to-head.

So I've decided to do it myself, in order to see if there actually is a clear difference, man-for-man.

I've tried to line up the players by role. Both teams have players that do similar roles generally, with only a couple of exceptions.

I'm looking at their world cup so far, as well as their numbers since 1 Jan 2013 in New Zealand and Australia.

Role 1 - Slower opener

Player	Guptill	Finch
WC Average	76.00	40.00
WC S/R	108.79	93.64
2 year Average	43.00	37.00
2 year S/R	85.08	87.13

Guptill is in better form, but the 2 year numbers are very close. These are two players of similar ability who are both playing good cricket. Both tend to be slow to start, but are capable of increasing their scoring rate once established.

Role 2 - Fast opener

Player	McCullum	Warner
WC Average	41.00	50.00
WC S/R	191.81	124.48
2 year Average	38.00	40.75
2 year S/R	135.02	104.21

Again the numbers are very close. Warner has the higher average, but McCullum scores faster. Both are remarkably good at both scoring boundaries and finding singles, but both are prone to hitting bad balls straight to fielders. McCullum has shown a weakness against left-arm spin, so there's a chance that Clarke might bring himself on to bowl early on.

Role 3 - First drop

Player	Williamson	Smith
WC Average	37.00	57.66
WC S/R	83.14	94.02
2 year Average	51.08	60.92
2 year S/R	85.64	94.77

These two players are the best batsman for their team in recent times. Smith is ahead on these numbers, but it's wrong to say that Williamson is a weakness in the New Zealand side. Both manage to score at a good rate without looking like they're trying. Both also have a big impact on their team's chances of succeeding. New Zealand win 45% of the time when Williamson scores under 40 and 62% when he scores 40+. Australia have won 53% of the time when Smith's scored under 40 and 86% when he's scored 40+.

Role 4 - Innings builder

Player	Taylor	Clarke
WC Average	30.16	29.00
WC S/R	63.06	92.94
2 year Average	46.82	23.66
2 year S/R	79.30	80.49

Clarke's had a slightly better world cup, but Taylor has produced more quality innings' over the past 2 years, averaging almost twice what Clarke has. These two are both great players, who often play roles that allow others to shine. As a result, their numbers don't truly tell the story of their contributions. Both players' numbers are also a reflection of their battle with injuries.

Role 5 - rebuild or launch

Player	Elliott	Watson
WC Average	37.83	41.20
WC S/R	107.07	107.85
2 year Average	44.76	36.82
2 year S/R	94.63	94.70

A really interesting role in modern cricket is the number 5 batsman. Their role is sometimes to steady a rocking ship, and other times it's their role to attack, and build on the foundation of the players above them. It is difficult to separate the ability of Watson and Elliott to do this role.

They also both have a role to play with the ball as the extra bowler:

Player	Elliott	Watson
WC Average	34.00	74.00
WC E/R	8.5.0	6.72
2 year Average	25.88	101.50
2 year E/R	6.56	6.37

Elliott has been more expensive, but has also broken partnerships quite regularly.

Overall, it's really difficult to separate these two with bat and ball. I'd probably back Elliott as a batsman, but Watson with the ball, despite his numbers not being as good.

Role 6 - Agressive batsman

Player	Anderson	Maxwell
WC Average	38.50	64.80
WC S/R	109.47	182.02
2 year Average	41.77	33.42
2 year S/R	125.96	125.13

One of the dangers of comparing players like Anderson and Maxwell based on statistics is that they are often asked to do different jobs. Against South Africa, Anderson's job was not to come in and score at a massive strike rate. His job was to play sensibly and carry the innings through. Over a longer term it's difficult to separate Anderson and Maxwell. Both are capable of being absolutely breathtaking with the bat.

Both play quite different roles with the ball, so I'll look at them later.

Role 7 - Wicket-keeper batsman.

Player	Ronchi	Haddin
WC Average	14.60	42.00
WC S/R	125.86	157.50
2 year Average	38.88	41.11
2 year S/R	128.84	111.11

Haddin has had a much better world cup, but it would not be difficult to argue that Ronchi has been the most effective death batsman in the world in the past couple of years.

They're also difficult to separate with the gloves. Both are solid keepers who have made a couple of key mistakes, but in general, they've done the job required of them sufficiently.

Role 8 - Bowler who bats

Player	Vettori	Faulkner
WC Average	41.00	14.66
WC S/R	164.00	176.00
2 year Average	15.66	44.25
2 year S/R	123.68	114.56

Faulkner and Vettori have very different styles, but can both be very effective. Vettori has rediscovered his batting form of 2008-2012 in this world cup, during which time he was one of New Zealand's best batsmen as well as being an outstanding bowler. Contrastingly, Faulkner hasn't found his rhythm since returning from injury.

Role 9 - Right arm opening bowler

Player	Southee	Hazlewood
WC Average	27.13	20.85
WC E/R	5.57	4.19
2 year Average	28.97	20.44
2 year E/R	5.53	4.37

Hazlewood has the advantage here numerically, but some of that is due to Southee having a role bowling at the death. I don't think many selectors would pick Hazlewood over Southee, regardless of the difference in their stats.

Role 10 - left arm opening bowlers

Player	Boult	Starc
WC Average	15.76	10.20
WC E/R	4.41	3.65
2 year Average	22.09	14.37
2 year E/R	4.58	4.34

Starc and Boult probably been the two best bowlers in the tournament. They both offer different things. Starc bowls into the pitch with a high arm action that causes the ball to bounce higher, but it also gets less movement and arrives to the batsman later, despite the quicker speed through the air. Boult bowls over his front foot and tends to bowl more deliveries along the wicket than into the wicket. As a result, the ball swings more and arrives at the batsman faster. (Ed Cowan, after facing both, commented that Starc might bowl 5-10km/h faster but you have a lot more time to face the ball. Boult certainly feels faster.)

It's difficult to separate them, but not impossible. Starc has been the premier white ball bowler in the world recently.

Role 11 - 3rd seamer

Player	Henry	Johnson
WC Average	-	24.66
WC E/R	5.00	5.43
2 year Average	19.00	25.15
2 year E/R	4.26	5.04

Henry has only bowled 8 overs this world cup, as he wasn't even in New Zealand's original squad. His first 5 overs included 2 maidens and conceded only 9 runs against South Africa. He went the distance in his next 3 overs, but even then, a large proportion of his runs came through edges and mis-hits. Johnson is a master with the red ball, but hasn't had the success recently with the white ball that he had earlier in his career. It's still difficult to complain about an average of 25 and taking a wicket every 5 overs.

Role 12 - 4th seamer

Player	Anderson	Faulkner
WC Average	16.21	23.00
WC E/R	6.45	4.90
2 year Average	22.69	26.57
2 year E/R	6.42	5.45

This is a slightly more difficult comparison, as Anderson generally bowls at the death. His economy rate here is outstanding, and he's taken a lot of wickets. However, taking wickets with bad balls isn't necessarily a trait that is repeatable. Faulkner looks like a better bowler, despite his numbers not being quite as dramatic as Anderson's.

Role 13 - Spinner

Player	Vettori	Maxwell
WC Average	18.80	36.20
WC E/R	3.98	5.83
2 year Average	35.12	32.91
2 year E/R	4.10	5.24

Vettori is in a different class here. It's probably the only place where there's a clear difference in quality between players doing similar roles in the two teams.

Overall it's really difficult to separate the two teams. Both have a team full of good players in good form. They have players doing similar jobs, often in similar ways.

I don't think I can honestly say at this point which team has better players. The more you look at this match, the more mouth-watering it becomes.

Updated QF prediction chart

In my previous post I ran a simulation to find out potential quarter-final places. I received some criticism for having England so low, and Bangladesh so high, but events over the past 48 hours have shown that the respective probabilities of the two teams qualifying may not have been so far off.

The program that I wrote to do the simulation was corrupted when my computer crashed and I foolishly hadn't saved it, so I've written a different one to re-calculate. This time I made a couple of modifications. I moved from an additive model for run rates to a multiplicative one, as that seemed to be more sensible (teams are realistically a % better than other teams, rather than a fixed number of runs better. We would expect the margins to blow out more in terms of runs on better batting pitches than on difficult tracks).

I also slightly reduced the standard deviation of the simulation by moving it to one quarter of the mean rather than one third. This again made the results seem more sensible. There were too many teams scoring over 400 or under 100 previously.

Here are the new results. This table shows the probability of each team qualifying in position 1, 2, 3 or 4 in their group, and then the total probability of qualifying. Again I have not factored rain into this, and with Cyclone Pam heading towards New Zealand that may be a little optimistic.

Team	1st	2nd	3rd	4th	Quarters
New Zealand	1	0	0	0	1
Australia	0	0.976	0.024	0	1
Sri Lanka	0	0.024	0.9725	0.0035	1
Bangladesh	0	0	0.0035	0.9965	1
-	-	-	-	-	-
India	1	0	0	0	1
South Africa	0	0.976	0.024	0	1
Pakistan	0	0.017	0.664	0.1165	0.7975
Ireland	0	0.007	0.312	0.1405	0.4595
West Indies	0	0	0	0.743	0.743

The potential group results look like this:

Group A

NZ Aus SL Ban	0.9725
NZ SL Aus Ban	0.024
NZ Aus Ban SL	0.0035

Group B

Ind SA Pak WI	0.5295
Ind SA Ire WI	0.1985
Ind SA Pak Ire	0.1345
Ind SA Ire Pak	0.1135
Ind Pak SA WI	0.011
Ind Pak SA Ire	0.006
Ind Ire SA WI	0.004
Ind Ire SA Pak	0.003

The three interesting potential quarter final match-ups to watch for here are

SA vs Aus	4.7%
Ind vs SL	0.35%
Ire vs Ban	0.02%

In reality the probabilities of Ireland vs Bangladesh and Australia vs South Africa are higher, as they are both much more likely if rain starts to fall.

World-cup quarter finals simulation

After Pakistan's tremendous win over South Africa, and Ireland's remarkable victory over Zimbabwe, the make up of the quarter finals is not really much clearer.

They question as to who is likely to be going through, and who will play whom has been the subject of many, many twitter conversations.

I thought it might be helpful to run a simulation to look at some of the possibilities.

I used Microsoft Excel as it's quite convenient. I used the scores already made in this tournament to decide the probable scores. For each team I got their average rpo scored in relation to the overall group run rate, and their average conceded in relation to the overall. Hence if a team in group A averaged scoring 5.5 rpo and conceded 5.3 rpo, they got values of +0.4 for batting and +0.2 for bowling (as the average rpo in group A has been 5.1 so far). From that point I then used an inverse normal, with a random number between 0 and 1 for the area, the group run rate plus the batting run rate modifier and the other team's bowling run rate modifier as the mean. For the standard deviation, I used the smallest of one third of the mean and 1.6. This allowed me to make sure there was (almost) no chance of a team getting a negative score, but that the scores weren't going to blow out too much.  I used 1.6 as that's the standard deviation of all innings run rates this tournament..  This gave me a 50 over score for each team, and so which ever was ahead got the points for the win.

There are a few limitations with this method. I didn't take into account the quality of the teams that each side had faced. England has played Australia, New Zealand and Sri Lanka, but has yet to play Bangladesh or Afghanistan. Their numbers are not going to necessarily show how well they will do against less fancied opponents. Likewise no adjustments were made for the pitch that the match is being played on. We know that South Africa have tended to favour playing on bouncier tracks, so an innings at the 'Gaba won't necessarily tell us much about how they would go in Dunedin. I also haven't taken into account player strengths. Bangladesh's batsmen tend to struggle against tall bowlers, such as Finn and Woakes. England can expect that those two bowlers will perform better than average against Bangladesh, and hence their team is likely to do better than the numbers would suggest.

Another major limitation is that I haven't made provision for rain. That would obviously throw off all calculations. However, given the limited information I felt that a more simple model was best.

I decided to do 2000 trials, so that I could feel that the major source of uncertainly was the assumptions rather than the natural sampling variability.

First I found the probability of the different teams making the quarter finals with my simulation:

Team	Probabiity
New Zealand	100%
Australia	100%
Sri Lanka	99.95%
Bangladesh	82.51%
England	17.54%
-	-
India	100%
South Africa	100%
Pakistan	74.71%
Ireland	61.82%
West Indies	63.47%

We can see that Pool A has one crucial match (England vs Bangladesh)
Pool B, however, is still wide open. Ireland vs Pakistan is the last game of the round robin, and it's shaping up to potentially be one that has 3 team's fortunes riding on the result.

If West Indies make the final 8, they will almost definitely face New Zealand. It's very unlikely that New Zealand will not end up on top of Pool A, and impossible that West Indies will end up 3rd or higher in pool B.

Here's the full results for all possible matchups

Pool A	Pool B	Probability
New Zealand	Pakistan	14.99%
New Zealand	South Africa	0.35%
New Zealand	Ireland	21.23%
New Zealand	West Indies	63.44%
Australia	India	2.30%
Australia	Pakistan	43.11%
Australia	South Africa	27.57%
Australia	Ireland	27.02%
Sri Lanka	India	18.18%
Sri Lanka	Pakistan	15.83%
Sri Lanka	South Africa	53.75%
Sri Lanka	Ireland	12.19%
Bangladesh	India	64.74%
Bangladesh	Pakistan	0.75%
Bangladesh	South Africa	15.88%
Bangladesh	Ireland	1.15%
England	India	14.79%
England	Pakistan	0.05%
England	South Africa	2.45%
England	Ireland	0.25%

I'll redo this after tomorrow's results, and then again on Monday.

The most likely scenario at the moment is India to play Bangladesh, Australia to play Pakistan, South Africa to play Sri Lanka and New Zealand to play West Indies.

I've updated this here