Lower order CC Division 2 runs – are they predictive of Test performance?

Jofra Archer is struggling with the bat in Test cricket, averaging eight and lengthening the tail. Yet he has a First Class average of 26. Is he getting an easy ride batting down the order for Sussex, then being found out at the highest level? Let’s find out.

Recap – Linking Division 2 and Test Batting

Previous workings showed that a played would expect to average 72% as much in Tests as they do in Division 2 (D2). There isn’t that much data though: most Test players are drawn from the top division. Just four players have over 20 completed innings at both levels over the last four years:

Not a bad fit – D2 averages do have reasonable predictive power of Test performance for batsmen (please take note Mo Bobat). You just need to play a decent number of games in both formats.

But what about tail enders in Tests?

Most of the overseas players in D2 are batsmen. There aren’t many bowlers in D2 to have also played Test cricket lately. Here’s the data for the five lower order batsmen to have eight or more completed innings in Tests & D2:

Remember none of these players has 20 completed innings in both formats, so expect volatility. Archer and Mohammad Abbas are the outliers: Archer averaged nearly four times as much in D2, while Abbas has a slightly higher Test average.

Across the five players, their Test average is 63% of their D2 batting average (for all players this figure is 72%).

Tail enders in D2 vs D1

Data is lacking on tail enders in D2 and Tests. Let’s answer a different question. If we are happy with the standard of D1, then all we need to do is demonstrate similar averages for the lower order in D2 and D1, and we can conclude that Jofra Archer is good at batting.

The above chart is for all batsmen that have >15 completed innings in D1 and D2. If anything the trend is for higher averages in D1. Can’t explain that, but at least that gives some comfort that the tail isn’t getting an easier ride in the lower division.

Conclusion

Jofra Archer would be a very unusual player if he continues to average under ten in Tests. I would expect him to average 17 in Tests based on all available red-ball innings. It just happens that the County Championship has seen the best of his batting, and Test cricket the worst.

County grounds ranked by ease of batting

In this piece I’ll look at which grounds are best for red ball batting, and use that to see what impact that has on averages: how much of a boost do Surrey’s batsmen get from playing at the Oval?

Fig 1 – County grounds ranked according to runs per wicket in County Championship matches over the period 2017-19. Grounds where fewer than 100 wickets fell in that time are excluded.

So what?

Beyond it being a spot of trivia, I can immediately see two reasons why this matters.

i. High scoring grounds harm the county’s league position

In County Cricket there are 16 points for a win, 5 for a draw and none for losing. A win and a loss is worth 16 points, while two draws is worth 10. Drawing is bad*.

Fig 2 – Runs per Wicket in the County Championship over 2017-19 plotted against the Draw percentage for that ground. Higher runs per wicket are associated with more draws.

And yet there are teams producing high scoring pitches, boosting the chances of a draw, and reducing their chances of picking up 16 points.

Compare Gloucestershire’s two home grounds since 2017: at Bristol (32 Runs per Wicket), W2 L4 D8. Cheltenham (28 Runs per Wicket), W4 L1 D2. Excluding bonus points, Cheltenham is worth an extra 5.4 points per match. While that’s an extreme example, and the festival only takes place in the summer months, there’s still the question “why make Bristol so good for batting”?

Maybe a deeper look at the data will reveal why Gloucestershire and Surrey don’t try to inject a bit more venom into Bristol and The Oval; for now it looks like an error.

*There’s an exception: a team that is targeting survival in Division 1 might choose to prepare a flat track and harvest batting points plus drawn match points in certain situations. For the other 15 counties, drawing is still bad.

ii. Averages should be adjusted to reflect where people play their Cricket.

When using data to rank county batsmen and bowlers, the one gap that I couldn’t quantify was the impact of how batting or bowling friendly each player’s home county is. With this data we can add an extra level of precision to each player’s ratings.

How would we do that? It would be wrong to simply take the difficulty of a player’s home ground as the adjustment – because there are also away games. The logical approach would be to take the average of that player’s home grounds (50%, weighted by the various home grounds that county uses) and the other teams in that division (50% weighting).

Fig 3 – Impact on batting average from the relative batting friendliness of that county’s grounds (2017-19).

For instance, Olly Pope’s average is artificially inflated by 10% from being based at The Oval. That takes his rating (expected Division 1 average) down to 54.6 from the suspiciously strong 60.7.

Fig 4 – Selected players’ expected averages, now we can adjust for each player’s home county

Equally, Tom Abell clambers up the ranks of 2019’s County batsmen: his rating jumps 7.1% to 35.6 from 33.2. Not an extreme move, but a nice boost to go from 50th to 31st on the list.

This takes us one step closer to a ratings system that captures everything quantifiable. Before next season I’ll adjust the ratings of batsmen and bowlers to reflect this factor.

Further reading

A summary from 2004 of the county grounds and how they play http://www.bookmakers1.com/englishcricketgrounds.html

Remarkable how many of the descriptions feel alien now – you wouldn’t believe that Taunton was “an absolutely stonking batting track”.

Underrated Bowlers – 2019 season

This is my first attempt at something difficult: finding the best players that aren’t regularly playing County Cricket, but that are good enough to do so. In theory there shouldn’t be very many players like this – because counties will know who their best players are.

I’ve used my database of bowling performances from 2016-19 in County Championship and 2nd XI Championship Cricket and picked out six that have promising data.

Time will tell how many of these players get regular first team cricket (and succeed) in 2020.

Fig 1 – Strongest bowlers that played three or fewer County Championship matches in 2019.

I’ve looked at players that have been selected for no more than three County Championship matches in 2019, for reasons other than injury.

Note that England’s Matt Parkinson only played four games for Lancashire in the 2019 County Championship, so might have made it onto a list like this, but he is unlikely to be under anyone’s radar now he’s in the Test squad.

Batting: All County Cricketers Rated

This page contains expected County Championship Division One batting averages for all County Cricketers to have i) played during 2019; and ii) batted in at least 20 completed innings since 2016.

Performances in the Second Eleven Championship, County Championship and Test Cricket are included, though each performance is weighted according to the level being played at (so averaging 30 in Test Cricket is much better than averaging 40 in the Second Eleven Championship).

To give a better indication of current ability, and to partly adjust for age, ratings are weighted more heavily towards recent performances.

Ratings are shown if each player were playing in Division One – this ensures bowlers are compared on an apples-to-apples basis.

I’ll update this page periodically, as more games are played and more information is available on each player.

This version includes matches up to 29th September 2019.

Top batsmen

Fig 1 – Top 50 Batsman in 2019 County Cricket. Min 40 completed innings since 2016.

Full list

Fig 2 – All Batsmen in 2019 County Cricket. Min 20 completed innings since 2016.

Key findings

Zak Crawley is an odd Test selection

  • Expected Division 1 average under 30
  • Only averaged 34 in 2019, after averaging 32 in Division 2 in 2018.
  • Even separately adjusting for age (he’s only 21), it’s hard to argue he’s currently better than Dent & Rhodes.

Ollie Pope is practically too good to be true

  • Expect his average to come down – he can’t possibly have an expected average exceeding 60.
  • Only 42 completed innings – barely a sufficient sample size to be included in the top 50 players.
  • Still, he’s easily worth a Test place.

Very few English batsmen are capable of consistently averaging over 40 in Division 1

  • Cook, Ballance, Northeast and Brown are the four England qualified batsmen who would be more likely than not to average over 40.

There’s more decent English openers than you may have been told elsewhere

Keaton Jennings, Mark Stoneman, Chris Dent and Will Rhodes could cover Burns and Sibley. And, if he could be coaxed out of Chelmesford, Cook.

England selectors might well be relieved that Cook has retired – imagine having to choose two out of Cook, Sibley and Burns to open the batting.

What do you think?

No doubt there’s plenty of themes and trends from the data that I’ve not mentioned – please do drop me a line through the contact page or @edmundbayliss on Twitter and let me know what you think.

Northamptonshire’s Promotion Drivers

Northamptonshire were at odds of 34-1 to win Division Two before the 2019 season began. They had a lot of work to do to get into the top three.

Things didn’t get any better when Ben Cotton was released after not managing to “reach fitness targets”.

I had them as the sixth best team in early April. Here’s what I said on the twitter:

Not a bad side, but off the pace of the top of Division 2. A batsman light, better balanced with Bavuma replacing Holder on 14 May. A shallow squad – @NorthantsCCC may have to prioritise the competitions where they have the best chance of progressing.

Now they are on the cusp of reaching Division One. Just four points from their game against Gloucestershire will secure promotion. What happened?

1.Batting outperformance

Fig 1 – Northants performance vs expectation, for an XI of the players to have featured in the most matches. Expectations based on 2016-18 red ball data.

Ricardo Vasconcelos, Adam Rossington, Rob Keogh, Nathan Buck all averaged ten or more runs above expectation.

The team as a whole averaged 53 runs per innings more than expected. I think that Rossington, Keogh and Buck had good years, and wouldn’t be expected to repeat that in 2020. Vasconcelos though. 21 years old, already has a First Class average of 37. How good could he be in a few years time?

It’s rare for a team to just have one player underperform with the bat (see the recent Ashes series). 35 batting points is the highest in the league.

2.Hutton

Ben Sanderson was always a candidate to dominate Division Two. His opening partner Brett Hutton has been the surprise package. A career average of 29 pre-summer, yet he picked up 35 wickets at 19.

Sanderson couldn’t do it on his own, Keogh, Procter & Buck bought their wickets at too high a price: without a second top bowler, it’s hard to see how Northants could have picked up five wins.

3.Sussex, Middlesex, Worcestershire

What happened guys? If time allows I’ll have a look at why these teams misfired. They are better than Northants.

What happens next?

If you believe Northamptonshire’s players have made technical changes, and they’ll play at the same level in 2020, then they could do OK in Division One. Maybe Rossington’s captaincy has made a difference.

Personally, I think there will be a lot of pressure on Sanderson, Hutton won’t repeat the heroics of this summer, and Northants won’t win many games next year.

Bowling: All County Cricketers rated

This page contains expected County Championship Division One bowling averages for all County Cricketers to have i) played during 2019; and ii) taken more than 20 wickets since 2016.

Performances in the Second Eleven Championship, County Championship and Test Cricket are included, though each performance is weighted according to the level being played at (so averaging 30 in Test Cricket is much better than averaging 40 in the Second Eleven Championship).

To give a better indication of current ability, and to partly adjust for age, ratings are weighted more heavily towards recent performances.

Ratings are shown if each player were playing in Division One – this ensures bowlers are compared on an apples-to-apples basis.

I’ll update this page periodically, as more games are played and more information is available on each player.

This version includes matches up to 23rd August 2019.

If you’d like to discuss, please feel free to contact me on twitter @edmundbayliss or use the contact page on this site.

Best bowlers:

Full list:

Preview: RLODC 2019 Semi Final 1

Nottinghamshire vs Somerset 12th May 2019

redballdata.com modelling: Nottinghamshire 51% – Somerset 49%

At first glance Notts look unstoppable: W6 L1 NR1, NRR +0.6. Two days of rest and home advantage.

Their batting is excellent: Hales and Duckett over their careers averaging high 30s at a run a ball mean more often than not a solid platform with runs on the board and wickets in hand for Mullaney, Moores, Fletcher to work with at the end of the innings. During the group stages scored over 400 twice in seven innings (Somerset’s highest is 358).

However – Somerset’s strength is their bowling – specifically taking wickets.

This makes for a rather unusual range of first innings scores if Notts bat first. Remember that Trent Bridge is a high scoring ground.

Fig 1: Notts projected runs.

Notts are just as likely to score 201-225 as they are 426-450! Such an even distribution is very rare. Nottinghamshire have a roughly 1500-1 chance of breaking the List A world record of 496.

Compare that to the more steady Somerset. Ali, Hildreth, Abell are dependable but not explosive batsmen. Batting deep means they can dig themselves out of trouble and find their way to a total. Thus Somerset have a 66% chance of scoring in the range 276-375.

Fig 2: Somerset projected runs

These are two evenly matched teams.

If you want an even contest that bubbles up over time, hope that Somerset bat first – they will get a reasonable score. Personally, I’d like to see Notts bat first because *cliche* anything could happen. Yes, I appreciate that means a good chance of a low score that Somerset fly past, or a high score that the visitors will get nowhere near.

The kids aren’t alright

Let’s look at the English First Class matches between Universities (technically the six University Centres of Cricketing Excellence) and Counties. These are vastly mismatched. The 2019 results make depressing reading for fans of university sport: UCCEs played 18 won 0 drawn 11 lost 7. County batsmen averaged 52 runs per wicket, while the students managed a paltry 15. If the UCCEs had been playing in the County Championship, they would have picked up a mere four batting points in over a season’s worth of matches.

It’s quite telling that over the last three years, only three student bowlers came out averaging under 35.

Fig 1- UCCE bowling performances against Counties in First Class Cricket, 2017-19. Overall bowling figures aggregated by player

Let’s not beat about the bush – the Universities were hazed by Counties that weren’t even at full strength. At first glance you might conclude that we can’t learn anything from these matches. Don’t be so defeatist! We have an opportunity to test how much better batsmen become when competing against players from a couple of rungs down the sporting ladder. It has always puzzled me: what should I model when an average player faces great bowling?

The method I’ve used is to compare individual batsmen’s performances in University matches against expected performance in County Championship Division 1. Since there aren’t that many University matches, we’ll need to group players by expected average to get meaningful sample sizes. We will also use three years’ worth of matches.

For the expected averages of each County batsman I’ve already done the legwork- see https://twitter.com/EdmundBayliss/status/1112335412658401280 and https://twitter.com/EdmundBayliss/status/1108509473591775233.

Here are the results:

Fig 2. The orange line represents the expected averages for each group of players (eg. “Very Low” are players who average below 20). The blue line shows the average vs Universities for that cohort, while the Grey bar (right hand scale) shows the ratio between actual and expected average.

Some interesting findings:

  • Overall “multiplier” (ie. boost to batsman’s average from facing University level bowling) 1.73 – a batsman who averages 30 in D1 would average 52 against UCCEs.
  • The University matches can distort First Class averages, especially for players with limited Caps. For instance, George Hankins averages 25 in FC Cricket, but strip out University matches and that drops to 23. Ateeq Javid’s 25 also drops to 23 when you exclude the 143 against Loughborough. Thus “First Class” average is reliable for county regulars, but fringe players will play a higher proportion of their innings against students. In these cases, “First Class” average should be disregarded in favour of a blended measure of County Championship & Second XI matches.
  • Batsmen with the lowest averages get the biggest boost– this could be because County Cricket pits them against deliveries which they aren’t good enough to defend. Put them against easier bowling and their technique is up to it, so they flourish.
  • Both the “Good” batsmen (who average 30-40 in D1) and the “Very Good” batsmen become excellent averaging 60+ against Universities. Why the plateau at 60? This is possibly caused by batsmen that “Retire Out”– which will affect the highest scoring (ie. best) players more. The concept of “Retired Out” is another reason UCCE matches distort FC averages.
  • Players ranked “Good” or above scored 29 hundreds in 131 completed innings. That’s a Century every 4.5 innings. Quite a mismatch between bat and ball.
  • It’s hard to appraise fringe County players, because of the low number of matches played. Ideally, scores from the University matches could be incorporated into my database in the same way 2nd XI matches have been (by adjusting for the difficulty of the opposition). However, the above tells us that the standard is too low and variable – so disregarding the data is the safest approach. This means that raw First Class averages are potentially suspect, and county selection should not be based on performances against the Universities – no matter how tempting it is. A fine example of selection being driven by University matches is Eddie Byrom being picked by Somerset on the back of 115* against Cardiff UCCE. He made 6 & 14 against Kent, and hasn’t played since.

Conclusion

Based on the above, there’s no evidence to say that top batsmen become impossible to get out when they play against weaker bowlers. A reasonable approximation is that Division 1 batsmen would average 72% more when playing against Universities.

When modelling expected average for a given batsman and bowler, the following rule of thumb is sufficient: Expected average = (batsman average / mean batsman average) * (mean bowler average / bowler average).

PS. Fitting the University Matches into the English summer

What place do the UCCE matches have in the cricketing calendar? Tradition is important. Personally, I would like these matches to continue. What’s needed is a window where the best players are unavailable (as these matches are of limited use to them).

In their wisdom, the ECB have established a 38 day window called “the Hundred”. I propose a change to the calendar – instead of the University matches, the 50 over competition should be the curtain raiser for summer. Half the group games could take place in early April, with the other half happening at the start of “the Hundred” window. This would be followed by two weeks of UCCE matches.

This would ease some of the congestion in the fixture calendar, and make a more logical use of county squads and grounds while we wait for “the Hundred” to finish. It would also mean full strength squads playing some 50 over Cricket, so England have some chance of being competitive in future World Cups.

Test vs County Cricket Averages

“Coach woulda put me in fourth quarter, we would’ve been state champions. No doubt. No doubt in my mind.”

Napoleon Dynamite (2004)

It’s often assumed that we cannot compare Test and first class batting performances – the old comparing ‘apples to oranges’ conundrum. But if we can quantify the relative values of the different formats, we can compare like with like.

Looking at batting performance of players who’ve played across multiple formats in English* domestic cricket (2016-2018), one can assess the relative difficulty of each tier. My analysis found that it’s 19% harder to bat in Test Cricket than it is in Division 1.

If a player averages 40 in Division 1 – the data says you could expect him to average 31 in Test cricket, 44 in Division 2, and 54 in the 2nd XI.

That tells us that you’d need to consistently average over 55 in Division 2 to average 40 in test cricket – hence so few England players being pulled from those ranks in recent years.

It also means that Hildreth (who I’ve previously thought of as an England option as he averages 41 in Division 1) would be expected to average 32 in Tests, and therefore isn’t the batsman we are looking for.

A few examples of 2016-2018 Division 1 and Test averages:

Note that only Root and Buttler underperformed in Division 1 relative to Test Cricket.

At this point its worth going into the assumptions – professionally I’m always keen to show where the data ends and the judgement begins. The data can tell us performances for each player who crosses tiers. Judgement needs to be applied to appraise that data and turn it into a single factor.

Some options:

  • Jonas (@cric_analytics) has looked at minimum 10 innings in both competitors – the downside of this is that it excludes valid data points. For instance, Ben Stokes scored 226 @ 28.3 in D1 in the last 3 years – 10 runs below his test average. That should count to the total, even if it’s a small sample. Jonas reckoned a 20% gap between Test and County cricket – slightly wider than my data suggests.
  • Include all overlap – the risk is that this is skewed by a few high/low scores from one-test wonders against weak/strong opponents. This gives a mere 2% difference between Test and D1.
  • Overseas players included: this gave an 8% gap between D1 and Test – but playing away from home knocks 10% off batting average, so this is not a fair comparison. To put it another way, Pujara playing for Yorkshire averaged 14, because every game was an away game.
  • I have used relative performance for English players with >4 completed innings in each format, and weighted the overall result according to the lower of the completed innings in each format. For instance, Ben Stokes has played 8 completed D1 innings, but 46 Test innings – so the overall result is weighted with a factor of 8 because of Stokes’ performances, while Dawid Malan played 36 D1, 26 Test innings, so is more useful for this exercise and receives a weighting of 26.

Adjusting for the level individuals are playing at, allows comparison of players in different tiers. In future posts I’ll look at some implications of this data:

  1. 2nd XI players with the potential to be First Class batsmen
  2. England’s best available batsmen
  3. Overseas players: who has & hasn’t succeeded – will look at any trends in the data.
  4. It’ll take more number crunching, but I’m interested in linking First Class / List A performance- to see how well correlated they are, and use that to gauge quality of players for which limited data is available (there are a lot of players with a handful of FC games behind them – too few completed innings to fairly appraise them

*I know it’s English and Welsh. Sorry Glamorgan. There isn’t an easy word for English and Welsh, so I’ll use English as shorthand for English and Welsh.