Sri Lanka vs England “Preview” January 2021

Here’s some brief notes written ahead of the first Test. I really should have put this up before the Test started. Anyway:

I give England only a 31% chance in the first Test. The betting markets say 39%. Why the difference? The toss is vital and England’s batting isn’t at full strength.

  • Batting first is key. SL are W7 L1 D1 batting first, W3 L4 D0 batting second recently. Batting first is worth 148 runs (runs per wicket by innings over the last 10 years: 40, 28, 29, 26). A 400 pitch becomes a 280 one after the successful tossers have had their fun with it.
    • Note spin is no good in first innings (average 42, SR 77). If you field first and get nowhere in 20 overs, you are in very deep trouble.

  • England have a lot of right handers. A tasty matchup for a leg spinner or SLA bowler. There are two in the Sri Lanka squad: Lasith Embuldeniya averages five wickets per FC game, PWH de Silva is more an all rounder who averages two per game. Embuldeniya averages 40 after seven Tests, but with a FC average of 25 in Sri Lankan conditions, he has a great opportunity. Surprised to see Embuldeniya’s odds 25-1 for Man of the Match. Oh, and he’s Sri Lanka’s leading wicket taker over the last two years.

  • On the topic of Sri Lankan FC averages, there’s a gulf between Test Cricket and the Sri Lanka Premier League Tier A. It’s hard to estimate because there are few (if any) overseas players for calibration, but I make the increase in bowling average 70%: a 25 average in Tier A translates to a Test average of 43. Here’s the expected averages for Sri Lanka’s attack:
Expected averages for Sri Lanka’s attack. Lakmal will be missed in the first Test. Fernando looks useful.
  • Away teams pick too many spinners (over the last ten years away spinners average 35 at Galle) likely because teams pick more spinners than are Test standard. The relevant decision is “who will do better, our third spinner or our first change pace bowler”?
    • In England’s case they that’s not a question of spinning ability, more the balance of the side. With Ali unavailable, England don’t have the batting depth to pick a third specialist spinner. Expect Curran+Bess+Leach+Two Pacers+Root. Sri Lanka will know this, so have an incentive to prepare a spinning pitch and nullify England’s pace attack. Unclear what the pitch will be like as has to be good enough to take back-to-back Tests.

  • Curran and Bess may not offer enough in either batting or bowling to balance the team. Maybe in a couple of years, but today England look beatable.
  • Put all that together, England have the better bowlers, but the toss is so important that it’s a great leveller. Win the toss, bat, win the game.

Changing conditions

I hadn’t noticed this change – it used to be that the 2nd innings was the time to bat in Sri Lanka. Now it’s the 1st innings. See below the difference in runs per wicket from batting first/third versus second/fourth. A big advantage to winning the toss and batting.

Why should that change happen? Different groundsmen? Different grass? Playing at a different time of year? Either way it shows the importance of “live” queries feeding models rather than fixed assumptions.

  • PS. Reflecting after the first day’s play I need to think about specific matchups. Bairstow and Root are good against spin, even when it turns away from them.
  • PPS. There’s a lot of Test series happening right now – will December/January become the annual window of international red ball cricket?
  • PPPS. The comments about the importance of the toss look silly when spin took 6-85 in the first innings. Was I wrong or were Sri Lanka’s batsmen wrong? Hard to gauge without xW data.

Tenth wicket partnerships: Monsters and Modelling

Sri Lanka won a thriller last week (link), chasing down a target of 304 with one wicket in hand. The unbroken last wicket stand of 78 came out of nowhere. If they had been opening the batting for England, this would have been the ninth highest of the last 100 partnerships.

How common are these monster scores?

Considering tenth wicket partnerships since 2000, the Mean score is 14.5 runs, the Median eight, and the mean duration is 25 balls. The chance of scoring 78 or more is roughly 100-1. [1] 

Figure 1

That tells us that very high scores are rare, but what about the big scores – are there any patterns here?

  • Bias towards the first innings of the match
  • Most involve a top order batsman with the number eleven
  • Three blisteringly fast run-a-ball partnerships; most are significantly faster than the average 3.0 runs per over for Test Cricket in this era.
Figure 2

Modelling tenth wicket partnerships

If you have two openers that average 40, you can model the partnership as if it is one batsman that averages 40 – the distribution of scores will be the same. This holds true until you have batsmen with wildly different averages. What would you expect a partnership to yield when a top order batsman is left with a number eleven for company?

A model of expected average for a tenth wicket partnership was created, using the following inputs: each Batsman’s Career Average, Home/Away and the innings number within the match. Various combinations of the two batsmen’s averages were tested against the data since 2000. [2]

Results were tested in two ways. I) Measuring the mean square difference between expected and actual partnership, and II) Seeking a distribution where half the scores are above and half below the expected distribution

The best fit was that the partnership average is: Weaker batsman’s average + 20% of the difference between both batsmen’s averages.

Returning to Sri Lanka’s match winning partnership, Perera (Avg 35) and Fernando (Avg 7) would be expected to average (7) + (35-7)*0.2 = 12.6 for the tenth wicket. Adjust for it being the fourth innings, and being away from home, and the expected average drops below 10. Something else is missing – or that 78 partnership is still a miracle!

Figure 3 – Least likely tenth wicket partnerships

Strategy and Strike Rate

If the number eleven bats defensively, that gives more time for the senior batsman to score runs: the partnership for the tenth wicket is likely to be more lucrative.

Think Chris Martin – he averaged 2.5, but at a Strike Rate of 20 runs per 100 balls. Martin could expect to stick around for 12.5 balls. If he scored at a Strike Rate of 50, he would only last an average of 5.0 balls, and there would quickly be a marooned batsman at the other end.

Ignore Strike Rate and the 84 Chris Martin put on with Tim Southee in 2008 (link) was a one-in-27 million event. Adjust for bludgeoning Southee and circumspect Martin and that drops to 1,500-1.

There is an unquantified boost to the expected partnership through farming the strike to ensure the senior batsman faces more balls. Another increase comes through aggressive batting by the senior batsman. I will consider adding those factors to my Test Match Cricket Model, so it better reflects the reality of occasional monster last stands.

Conclusion

  • Expected value of the tenth wicket: Weaker batsman average + 20% of the difference between both batsmen’s averages.
  • A last wicket partnership is more successful if the number eleven defends, leaving the attacking batting to the senior batsman. If numbers ten and eleven are batting together, they should bat naturally.
  • More very high partnerships than my model expects, driven by attacking batting.

Further reading on batting partnerships

A powerful story, NSFW (because it is something of a tearjerker) https://www.cricketcountry.com/articles/bert-sutcliffe-and-bob-blair-at-ellis-park-a-fairytale-bigger-than-cricket-287471

A paper on batting strategy and partnerships in Tests. Limited in that it covers the general case, rather than a player-specific model. https://pdfs.semanticscholar.org/786b/fa723eb721b66fd6023b4a6f56394968087c.pdf


[1] 100-1 odds for an average last wicket pair. The 600-1 for Sri Lanka reflected the fourth innings, against a fantastic South African bowling attack.

[2] Note that only batsmen with more than 30 career innings were included and matches involving Bangladesh are excluded.