CSK vs MI, IPL 2020, Match 1: Criclytics Talking Points

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20 Sep 2020 | 06:36 AM
authorKartik Kannan

CSK vs MI, IPL 2020, Match 1: Criclytics Talking Points

Join us on a number-driven cricket narrative of match 1 of IPL 2020, through the eyes of Criclytics

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The first game of a big tournament and there were bound to be butterflies in the stomach for both sides, but MI started off with a bang with a first-ball boundary by Rohit Sharma. Criclytics too got off to a good start in the IPL 2020 when it came to getting the predictions right. The boundary-fest followed for 4 overs, where MI were 45 without loss. Criclytics seemed to trust CSK’s bowling strength and predicted that Mumbai may end up only with a 160-162 range total at multiple points in the game. Criclytics added only 10 more total runs (Final score 170), despite an 18-run fourth over.

In the middle-overs, Criclytics detected that a possible projected score for MI was around 161/162 since they had lost wickets in the middle overs and their lower order was about to be exposed, to a strong death bowling unit of Lungi Ngidi/Sam Curran/Deepak Chahar and Piyush Chawla. You could check it out in our Match Reel section.

How good was Piyush Chawla?

Chawla’s bowling figures read 4-0-21-1, with an economy of 5.25 runs per over in a game where the average runs per over was 8.1. His impact was the doubt he created in the batsmen's minds. 

Every time Chawla bowled an over he reduced Mumbai’s win% momentum, and shaved a few runs off the projected total, which had a lasting impact on Mumbai’s momentum in the Powerplay and middle-overs. 

Jadeja’s Twin-strikes derail Mumbai

Chawla’s 14th over, created enough pressure on Mumbai to up the ante, that they decided to target Jadeja (3-0-37-0 till then) and lost the plot in the 15th over with two big strikes, reducing the win% and shaving a few runs off the projected score. This over made it to our ‘Game-Changing Overs’ list.

Mumbai’s best player of spin (for the ball turning away from the right-hander) was Ishan Kishan, who was not playing this game. Given Mumbai were finding Chawla tough to score off, they would target Jadeja with left-handers (Saurabh Tiwary/Krunal Pandya) or use Hardik Pandya to unleash since he was their next best option to attack spin. The below pre-match graphic gives a good idea of why Mumbai chose to target Jadeja.

Lungi Ngidi’s comeback

Criclytics Win predictor had Mumbai ahead (more than 50% chance of winning) for 90% of Mumbai’s innings, and things changed with Ngidi’s 19th over with the big strike of Kieron Pollard and subsequently the lower order. It meant Mumbai had to just play out the last 2 overs with their tail, instead of being able to create opportunities for the savage scoring they usually target with Pollard. The last 2 overs yielded 11/3 and it made a huge difference. Ngidi’s first 2 overs went for 29, and the next went for just 9 runs, proving once again that CSK have done their ‘horses for courses’ strategy well for the death overs.

Bowling Impact

Criclytics measures the overall match impact through bowling and batting, and among the CSK bowlers Chawla had the best impact for the way he controlled the game, ably supported by Ngidi’s admirable death bowling. 

Despite Mumbai losing the game, a couple of positives for them was the way their bowlers kept CSK quiet in the first 9 overs, and moved the win% towards them. A couple of let-offs for Mumbai happened in the 6th over when Jasprit Bumrah bowled a no-ball, which was dispatched for a boundary and then leaked a six off a free hit. It allowed Chennai to come back from an 18% win probability to 30% on account of that “One long legal ball”. Also, post the 9th over, Chennai found run-scoring relatively easy, consistently moving up their win%. But the first 9 overs was all about Trent Boult and James Pattinson, in a way they created pressure on CSK’s top order with a wicket each.

So, Boult and Pattinson (also on the account of their batting chances) move up in the top 5 performances of the match, which can be seen as part of our Match Report Card.

Was Faf’s batting really impactful than Chawla’s bowling?

A popular perception was that Faf du Plessis was stat-padding his way to scoring over run-a-ball, but it was his presence at the crease along with Ambati Rayudu that started to release the pressure. Till the 14th over, most of the win% increases came from Rayudu’s boundary hits, while Faf played second fiddle. Faf’s real value was his ability to stay till the end and not let panic grip as Rayudu and Jadeja’s wickets pulled the win% down to an almost even game. In the end, Faf had a strike rate of 132 in a chase where the average strike rate was 136. His boundary off Bumrah, added insult to injury after Sam Curran had done the damage earlier in the 19th over. The South African's twin boundaries in the 20th over killed any chances of a last-minute heist by Mumbai. A knock like this would be under-rated purely by perception, but Criclytics felt it was the next best performance after Rayudu and Curran, and better than the bowling performances of Pattinson, Boult and Chawla, for the silent impact it had.

CSK’s measured template resembled the way Trinbago recently played on the slow wickets at CPL 2020. Despite a Powerplay where they were 23/2 in 5 overs responding to a 163 chase, CSK managed to find their way in the middle overs having their power-hitting intact for the end. 

What else did Criclytics predict correctly?

The Criclytics win predictor predicted correctly for CSK to win by 5 wickets ( from the 11th over of CSK’s chase), despite requiring 82 off 54 balls.

Despite Mumbai’s great start with Rohit and Quinton de Kock, an iffy middle and death over phase did the damage to their chances. It shows that on pitches like these, the instinct to assess the pitch, the conditions (dew), the short boundaries plays a bigger role. CSK scored a 4 and a 6 more than MI, and had 4 fewer dot balls, despite the slow start. So as they say, the old adage of ’IPL being a competition where 7 teams compete to play CSK in the final’, still holds true, as CSK’s playoff’s probability increased from 56% to 66%. 

If you liked the Criclytics Viewpoint, do like the article, and share it with your cricket watching friends. If you have a counter view, please use the #CricketLikeNeverBefore hashtag on Twitter and let’s have a conversation!

You can watch Criclytics Machine Learning driven coverage of all IPL games, this season. We also have our stats team covering interesting passages of play in our Live Blog Match report and Quick Byes on Commentary

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Piyush Pramod ChawlaFrancois du PlessisLungisani True-man NgidiAmbati Thirupathi RayuduIndian Premier League, 2020Mumbai Indians vs Chennai Super Kings - Match 1 - Indian Premier League, 2020MI vs CSK

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