Use Of Data Science In Cricket--Details |Analysis |, MVPI, | During Auctioning, | IPL, | Boost Performance.

In cricket, if you try to find out what angle was the cricket bat swung in and with what velocity or what

was the contact point of the bat. All of this is somewhat useless data because first, it is very difficult to

record it-where did the ball and the bat make contact and what velocity was the bat swing in and with

what velocity should the cricketer swing the bat the ext time- all of this is not realistic. But

What is Data? And Data Science

Data is basically information about anything.

Recording and studying of data and then using the information gathered to arrive at a decision is what

is called data science

The number of leaves on a tree or the flavor of your ice cream or even the number of stars in the

Universe. What percentage of the people like the government- all of this is data.

Goal Of Data Science In Cricket

The goal of Data Science in Cricket is not just to predict match outcomes but also help

Improve the game strategies for the teams. ... Data science is not merely helpful for

predicting the most favorable team for the tournaments but also helps glean valuable

Insights for other use cases.

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Use Of Data Science In Cricket Like IPL

 Data science can be made use of in cricket and IPL in a unique and interesting manner the

popularity of data science is soaring

How can you collect data in cricket so that it becomes useful to you?

This is the question that how can you collect data in cricket. In Earlier, Test matches were held back

in the time of test matches, the data collected would only be how many wickets has been taken by a

Bowler. 

For batsmen, it used to be how many runs have been scored by the batsmen. With the one set of

One-Day Internationals (ODIs), more indicators began to be used For example, strike rates for

batsmen and economy rates for bowlers 

How To Calculate Data Science In Cricket

So let's find how to calculate data science. The batting average, Number of times the batsman scored

More than 100 runs. The Highest scores of the batsman. Number of matches played

Data Collection In IPL

Then came T20 cricket and then in 2008, came IPL

Data collection and data analysis in IPL has breached the next level, With so much being spent on

procuring players, it has become necessary for IPL teams to find out that if they spend on a particular

Player, then how valuable is he going to be for the team.

How should they judge in detail which players should they buy and which ones

they shouldn't 

How much money should be spent on which player and what are the values of the different players.

You'd not believe, but IPL teams have started hiring proper companies. Who are experts in such data

analysis Performance analytical companies that analyze how good a player is and develop strategies

for the players.

Analysis Of Data by Most Valuable Player Index(MVPI)

These data analysis companies analyze data about players in detail to understand who is good at what

Aspect For example, a metric that they use is MVPI or the Most Valuable Player Index. Which is a

weighted composite score of the different attributes of a player

First- For a batsman, his Hard Hitting Ability.

To calculate how many sixes and fours a batsman scores, the following equation is used- (Fours +

Sixes) / Balls Played by Batsman.

How many fours and sixes has a batsman hit in his IPl career divided by the number of balls he has

Played.finishing. This calculates the Hard Hitting Ability of a player finishing ability of Out a year =

Not Out innings divided by the Total Innings played.

Consistency of a player = Total Runs divided by Number of Times Out

Running Between Wickets = (Total Runs – (Fours + Sixes)) divided by (Total Balls Played – Boundary

Balls).

If the last metric is better in a batsman than the hard hitting metric, Then you can guess that he is not

good at hitting boundaries but is good at getting singles, twos and threes on other balls

Similarly, there are bowling metrics- Economy = Runs Scored / (Number of balls bowled by bowler/6)

Crucial Wicket Taking Ability = Number of times four or five wickets taken / Number of innings played.

It helps us understand the weak and the strong areas of different players, this is data science.

Whether a player is good at hitting boundaries or at running in between the wickets this is data

Science. Whether a bowler performs better against left-handed batsmen or right-handed

Batsmen this is data science. Whether a batsman performs better against spinners or fast

Bowlers.

Analysis can also work out in what stadiums and in what weather does a player perform better

Virender Sewage encapsulated its importance very nicely. 

Every game you play, they will record your good performance, your bad performance you played

against which bowler, you scored against which team, which bowler, and that data will show you that

you are good against Pakistan but you're not good against Bangladesh you are good against South

Africa but you're not good against England.

During Auctioning Of Players

During the auctioning of players, the IPL teams that do not have a lot of money would definitely want to

know. Whether the player that they are buying is worth the money they spend for their team or not

because more often than not, it so happens that the most expensive players in the IPL auctioneer not

The top performing payers of IPL always.

How many matches were won by a team in every season. Whether the team decided to bat or field

upon winning the toss And outputs like how many matches have been won by the teams in all the

seasons can be calculated

Mumbai Indians is at the top, Chennai Super Kings is at number 2 This is a very simplified answer.

You can even analyze the decisions of the toss.

Using Data Science Is The best way to boost performance in IPL

Now, you may wonder that these things are very useful and can boost performances in IPL and the

best IPL team can be formed then why does no one do it?

 The answer to this is that they definitely do almost all the IPL teams today make use of data analytics

during team selection. In fact, when Kolkata Knight Riders won the trophy in 2014, the auction analysis

of SAP is given a lot of credit for that Kolkata Knight Riders had hired the SAP data analytics company

to analyze the data and to explain in detail of what kind of team should be formed, which player

should be sent where and when and what should the strategies be on the basis of which the

Kolkata Knight Riders won the trophy.

You can increase your chances of winning by taking these things into account but there's never a

100% guarantee. Because after all, all the IPL players are humans and not machines So no matter

how much historical data you mine, a human will remain a human there will always be some

randomness due to human error And that's how it should be- it ensures the fun in these games, If

everything could be predicted so easily, then there would be no entertainment while watching the IPL.

So here you read about Use of data science in cricket -- Details,  analysis, mvpi, during, auctioning,

ipl, boost performance