🚀 New Video Release! | Cricket Analytics Meets Machine Learning 🏏🤖

 As a lifelong cricket lover and a researcher in data analytics, I'm excited to share my latest work that digs deep into a long-held belief in T20 cricket — Do extra deliveries (wides & no-balls) really give a major advantage to the batting side?

Using data from 269 T20 matches across international & franchise formats (both men’s and women’s cricket), I applied multiple machine learning models and feature selection techniques to uncover the truth.
📊 Key Insight:
Despite what many experts say, the outcomes of extra deliveries are highly unpredictable — behaving more like random events than strategic advantages.
🔍 What the study reveals:
73% of extra deliveries have low or no positive impact
9 ML models could not reliably predict outcomes (<40% accuracy)
Only a few parameters (match stage, batsman strike rate, bowler runs conceded) showed weak influence
Expert intuition doesn’t always match data-driven reality
🎥 I have prepared a YouTube cover/thumbnail summarizing the findings visually.
Full video: https://lnkd.in/gYib62QY
Full Paper : https://lnkd.in/gWrcX9Xg
Always happy to connect with others who love cricket, analytics, or both! 🏏📈
hashtag#Cricket hashtag#T20Cricket hashtag#MachineLearning hashtag#SportsAnalytics hashtag#DataScience hashtag#Research hashtag#BigData hashtag#CricketLover hashtag#AzureML hashtag#OrangeDataMining hashtag#LinkedInResearch hashtag#DataDrivenInsights

Dataset : T20 Outcome of Extra Delivery & Free Hit

 

Cricket is a fascinating game as it provides much entertainment for spectators worldwide. With the instruction of the T20 format, most countries except New Zealand and Zimbabwe other countries have franchise cricket. Franchise cricket has spanned the global mark of T20 cricket. 

With cricket, there are common beliefs such as extra delivery that would be delivered once a bowler sends a wide or no ball, a free hit will have a very high impact, etc. 

The following dataset is collected to verify these hypotheses. Data collection is not yet completed as well are you need to wait for results for a couple of months. 

T20 OutComeofthe ExtraDelivery FreeHit | Kaggle

Predictions Went Wrong

Predictions are part and parcel of our life. With more available data, we are looking at driven predictions rather than sense-driven predictions. Predication has expanded many domains such as ecomics, productions, sports etc. However, last week, we saw two of such predictions went wrong. 

1. Whether predictions at T20I worldcup

First of all, pre-world cup favorites, India couldn't win the semi final while another pre tournmennt favorite, hosts, Aurtralia couldn't make even to the semi final. I am not going to consider that a wrong predictions as win/loss prediction in sports should fail in order to sport become more attractive. 

However, when England - Pakistan lock horns with each other at the Melbourne for the final, there were predictions that match will not be possible to stage due to rain. There was 95% probability for rain. Playing conditions were altered in order to accommodate rain. Additonal day was already announced even before the tournament. But with the prediction of rain, match duration was increased by two hours and ten overs were set to constitute a match.  However, match was played without any interruptions. There was a harmless drizzle for five to ten minutes.

What was Predicted

What was Actual

2. USA Mid Term Elections

Then the next prediction in USA mid term elections. It was expected to trump led republican to take over the senate, house and even the govenership easily. There was prediction of "red - wave" and trump's come back.. But at the end of the election, demoract was able to hold the power of senete with 50/50. (With the vice president twi breaker, they are narrowly holding the senete by one vote. Predications were expecting republicans to win 55 seats in senete. On the House, republicans were expecting to get 235 seats but they got 218 which is the cut of margin to win the state. (five seats yet to be called). Now many media organizations are calling to review the pre-election predictions.

Source: US midterm elections results 2022: live | US midterm elections 2022 | The Guardian

Finaly,we need to understand that every thing under the sun cannot be predicted even with the sofiticated technologies that are around. 

Hasan Ali & Tweets

As they say in Cricket, "Catches win matches". It will be more relevant when you missed a catch in the WorldCup semi-final.  During the T20I world cup when Hasan Ali dropped the catch, the match turned to head to tail. As cricket is a great game of uncertainty, the crowd don't believe in that. After the dropped catch, there were a lot of allegations against Hasan Ali. It went to an extent that his wife and his religion also are part of these allegations. 

Let us analyse tweets against Hasan Ali using Tweet Sentiment Visualization App. 

Though there were a lot of hate comments against Hasan Ali on Facebook, Instagram etc, Twitter users are seems to be more professional as we see a lot of positive tweets against him. Some tweets wishing him success as well. 

When you look at the topics, catch, stay strong are the common topics. 

Then let us look at the Tag Cloud in different quadrants. 

Extra Delivery, Free Hit and IPL

Less than a week away from the Universe Cricket Carnival, IPL 2021. This post is not to do any prediction analytics as Cricket is the great game of uncertainties. 

A Research was carried in in 2014 to find out the outcome of the extra deliveries in Cricket. As there is a common belief when there No ball or wide ball is delivered, extra delivery will cost heavily for the fielding team. This research was done in order to validate the claim and with the above research, the claim was rejected. However, since the data was captured for matches played at different venues and times, there were questions of the research credibility. 

New validation research will be done on IPL 2021 data. 

These are the guidelines for the data collection. 

1. Full completed innings are considered. In the case of rain, the number of overs will be reduced and that will have a different impact hence those matches/innings are ignored. 

2. If there are two extra deliveries in one over that over will not be considered for extra delivery analysis but will be considered for the free hit analysis. 

3. Half completed overs will not be considered for Extra Delivery Analysis and will be considered for the Free hit. 

Parameters to Consider

There are many parameters to be considered. Name of the Bowler, Team of the Bowler, Name of the Batsmen, Team of the Batsmen, Runs scored by the Batsmen at time of facing the delivery, Number of Deliveries faced by the Batsmen at the time of facing the delivery, Ball Number, Runs in the Previous Over, Runs in After Over, Runs of the overs, Is Batsmen Changed, Score in Free Hit, Scores in the Extra Delivery, Power Play Partnership, Partnership Runs, Partnership Deliveries Wicket in Same Over, Over Number, Ground, T20 Stas of the Bowler and the Batsmen data will be collected. 

Still, the model is at the development stage and will be released next week. Any other data to be considered? Let me know. 

Research - Outcome of the Extra Delivery in Cricket

One of the Famous No-Ball in the History of Cricket source: SBS

There is a common belief in cricket that extra delivery that is resulted in from No-Ball or Wide in an over will cost more than to the bowling team than to the batting team. This research paper is to verify the above statement. By employing data warehousing techniques, it was proved that there is no basis for this claim. 

You can visit the research paper at ResearchGate

This is the outcome of the extra delivery.

You will see that more than 70% of extra delivery has cost no runs or only one run. only 17% are accounted for boundaries. 

This was done in 2014 and cricket has evolved for half a decade. Therefore, this has to be verified against new data. IPL 2021 data will be used to further verification. Stay tuned!