43:["$","title",null,{"children":"ICC Men's Cricket World Cup - 2023 | Kartik Kataria's Workspace | Observable"}] 4b:T45f,

Insights

Experienced spin bowlers could become the new weapons for Bangladesh and India : Shakib Al Hasan from Bangladesh has lots of experience, bowling ~2000 Overs. The Ravindra Jadeja from Indis is 2nd on the list of most experienced spin bowler. Ashwin from India also in the top 5 experienced folks, which will make the case for India even more stronger.
Can Rashid Khan turn the tables for Afghanistan? In terms of Strike Rate, Rashid Khan from Afghanistan has to be the best (Liam Livingstone of England is a part time bowler and his data set(played only 16 matches) is not enough to say that he has the best strike rate). Other than Rashid Khan, Mujeeb Rahman and Nabi are not that great. If they can up their game and improve their Strike Rates, then it might be a different world cup for Afghanistan.
Kuldeep Yadav could be the dark horse for India : With a strike rate of 30, Kuldeep Yadav is the wickettaker spinner from India. He is the one who can be reliable as well because of his 2nd highest Wickets/match ratio of 1.7.

4c:T556,

Insights

102 players were tried by teams at no.4 combined together since 2019. Clearly, players like Rizwan, Labuschagne from PAK and AUS respetively have played at No. 4 positions and scored a lot of runs as well. On the other hand, Indian players are struggling at this position
It seems as if India tried too many options at number 4 position. 15 options to be precise. This might be because of change in management or injuries as well or players not performing well. But if you look closely at the graph, some of the players just played for 2-3 matches, which are not enough for a player to prove their worth at a specific position.
Shreyas Iyer has played the most number of matches for India at No.4. He also has scored the most number of runs at that position with a decent average of ~45.
The 2nd most experienced person is R Pant, who is injured and not a part of the world cup anymore. KL Rahul who is in the squad and has played 4th most number of matches for India can also be one of the options.
Another interesting observation is that KL Rahul's Average at No.4 is the highest among all Indian players at No.4
SV Samson just got once chance to play at No.4, in which he performed really well but suprisingly did not got a chance to play more at that position

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2023","cells":[{"id":0,"value":"

ICC Men's Cricket World Cup - 2023

","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":413,"value":"With the 2023 World cup happening in India, they are the favorites to win this world cup. They do have some big names in their 15 member squad, but lets see what does the data says and how do they compare with members of other teams as well. Moreover, the Indian team is also struggling to find answers to questions: \"Who should bat at No.4 for India\". I will also try to find answers to these questions. NOTE: All the data used in this notebook has been taken from Statsguru

","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":405,"value":"Plot.plot({\n color: { legend: true },\n title:\n \"Different team's performance position in the world cup since its beginning\",\n width,\n marginRight: 91,\n marginLeft: 91,\n marks: [\n Plot.frame({ strokeOpacity: 0.1 }),\n Plot.barX(data1, {\n fy: \"Stage\",\n x: \"Value\",\n y: \"Teams\",\n fill: \"Teams\",\n tip: true\n }),\n Plot.ruleX([0])\n ]\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2034,"value":"
","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":69,"value":"Vizualization showing performances of different teams and the stage they exited/their position at the end of the tournament. ","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":359,"value":"viewof xStage = Inputs.select(d3.group(data1, d => d.Teams), {label: \"Select team\"})","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":345,"value":"Plot.plot({\n color: { legend: true },\n title:\n \"Zooming in on individual teams to see at what position they finished. \",\n subtitle: \"Use the 'Select team' dropdown above to see a performance summary of different teams.\",\n width,\n x: {label: \"Different stages of tournament\"},\n marginRight: 91,\n marks: [\n Plot.frame({ strokeOpacity: 0.1 }),\n Plot.barY(xStage, {\n fx: \"Teams\",\n x: \"Stage\",\n y: \"Value\",\n fill: \"Stage\",\n tip: true\n }),\n Plot.ruleY([0])\n ]\n})","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2038,"value":"
","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":77,"value":"

Some insights from the visualization

","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":79,"value":"1. Australia is the best perfomer, winning 5 out of 12 times.\n2. Bangladesh, Netherlands and Afghanistan have struggled almost every single time and has failed to reach semi-finals even once.\n3. India has been the 2nd best, winning the cup 2 out of 12 times and reaching the semi-finals 4 times.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":2043,"value":"
","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":850,"value":"Now, lets dive into some batting and bowling stats to see how India compares with other teams. Considering the pitches in India(the host nation for 2023 World Cup), certain attributes that suit the pitch conditions become more important than others. For example: Indian pitches support spin bowlers more than the fast bowlers.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":857,"value":"Based on my understanding of the game and the scope of this project, I will be looking at the following key factors to compare different teams: ","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":1044,"value":"

1. How good is the opening batsmen pair for each nation?
2. How good are the spin bowling options in each team?

Opening batsmen Analysis

","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":924,"value":"Let's start by first looking at the total number of runs scored by opening batsmen of each team.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":782,"value":"viewof watching = Inputs.checkbox(openers, {label: \"Select player\", format: x => x.Player})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":985,"value":"Plot.plot({\n marginLeft: 130,\n color: { legend: true },\n grid: true,\n width,\n x: {type: \"sqrt\", label: \"Total Runs Scored\"},\n title: \"Total Runs by opening batsmen of each nation\",\n marks: [\n Plot.barX(watching, {\n x: \"Runs\",\n y: \"Player\",\n fill: \"Nation\",\n r: \"Runs\",\n sort: {y: \"x\", reverse: true},\n tip: true\n }),\n Plot.ruleX([0])\n ]\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1174,"value":"Plot.plot({\n marginLeft: 120,\n title: \"Opening batsmen Averages\",\n subtitle: \"Average is the number of runs scored per match. The more the better.\",\n x: { grid: true, type: \"sqrt\",label: \"Opening Batsmen Average\"},\n y: { grid: true },\n width,\n color: { legend: true },\n marks: [\n Plot.barX(watching, {\n x: \"Average\",\n y: \"Player\",\n fill: \"Nation\",\n sort: {y: \"x\", reverse: true},\n tip: true\n }),\n Plot.ruleX([0])\n ]\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2098,"value":"
","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":777,"value":" Plot.plot({\n color: { scheme: \"Blues\", legend: true, },\n title: \"Average vs Strike Rate comparison for Opening Batsmen of different teams compared side by side\",\n subtitle: \"\",\n grid: true,\n \n width,\n marks: [\n Plot.frame({ strokeOpacity: 0.1 }),\n Plot.dot(watching, {\n fx: \"Nation\",\n x: \"Average\",\n y: \"SR\",\n fill: \"Mat\",\n r: \"Runs\",\n tip: true\n })\n ]\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2103,"value":"
","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":1358,"value":"

Insights

Spin bowling analysis

I will be evaluating the spinners based on their experience, strike rate and wickets/match

1.Experience

In such a big tournament, every team needs experienced players who can take them out of difficult situations. One of the ways to see how experienced a bowler is to look at the number of overs they have bowled.","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":1642,"value":"Plot.plot({\n color: { legend: true },\n marginLeft: 140,\n title: \"Total Number of Overs bowled by spinners of different teams\",\n width,\n x: { grid: true, type: \"sqrt\"},\n y: { grid: true, },\n marks: [\n Plot.barX(watching2, {\n x: \"Overs\",\n y: \"Player\",\n fill: \"Nation\",\n sort: {y: \"x\", reverse: true},\n tip: true\n }),\n Plot.ruleX([0])\n ]\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2144,"value":"
","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":1661,"value":"

2. Strike Rate

While the number of overs definitely tell about the experience, it does not talks about the efficiency of a bowler. To understand the efficiency of a bowler, we need to look at the Strike Rate - No. of balls bowled per wicket. (Formula: Total balls bowled/Total wickets taken). Remember, a bowler with lower strike rate is better than the one with a higher strike rate.

3. Wickets per match

Another way to look at a players efficiency is by considering how many wickets they take in each match. This can be a good metric to see how reliable a player is. In the end, a captain wants their bowler to take wicket. A bowler with high Wickets per match will be more reliable. (Calculation method: Total wickets taken divided by Total matches played).

Who should bat at No. 4 for India

The number 4 position has been one of the main issues for India and could be said as one of the reasons behind India's loss in semi-final in the last world cup's edition. No. 4 position is very crucial for any team and you want one of your most experienced player to that spot. For ex: Tendulkar and Yuvraj Singh used to play at that position during their since 2019 for India.

Almost every nation(except Eng and NZ) has picked their No.4 as the one who has played the most number of matches at that position since 2019.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":2210,"value":"
","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":1977,"value":"Now let's compare all the indian players who have played at No. 4","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":1523,"value":"viewof teamBat = Inputs.select(d3.group(battingPosition4, d => d.Nation), {label: \"Select team\"})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1828,"value":"Plot.plot({\n width,\n title:\"Number of Matches played by Indian players at No.4 since 2019\",\n marginLeft: 140,\n color: { legend: true, scheme: \"Greens\" },\n x: { grid: true, type: \"sqrt\" },\n y: { grid: true },\n marks: [\n Plot.barX(teamBat, {\n x: \"Mat\",\n y: \"Player\",\n fill: \"Runs\",\n sort: {y: \"x\", reverse: true },\n tip: true\n }),\n Plot.ruleX([0])\n ]\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2362,"value":"For India, it was Shreyas Iyer before the world cup who has played the max. no. of matches at No.4 and that too after staying out of the game for almost 12 months due to a back injury. 2nd choice for India was RR pant, who is also injured at the moment. Luckily, SS Iyer recovered quickly and hence was included in the Indian World Cup squad.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":2358,"value":"

","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":1871,"value":"Plot.plot({\n title: \"Average of the players who played at No.4 for India since 2019\",\n width,\n marginLeft: 140,\n color: { legend: true, scheme: \"Greens\" },\n x: { grid: true, type: \"sqrt\" },\n y: { grid: true },\n marks: [\n Plot.barX(teamBat, {\n x: \"Ave\",\n y: \"Player\",\n fill: \"Ave\",\n sort: {y: \"x\", reverse: true},\n tip: true\n }),\n Plot.ruleX([0])\n ]\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2364,"value":"Before the world cup, doubts were being raised on how good KL Rahul is as a batsmen. Should he be given a chance in the world cup? This was primarily because he was being forced to play as an opener where he struggled with the new ball and hence he was being bullied on social media. Little did they knew that all of this will change once KL Rahul started getting more chances in the middle order. Look at his numbers at No.4: a massive avg of ~75. Rahul could be a perfect No.4 batsmen, having the skills to build a partnership when the team loses early wickets and also the power to hit long sixes when the requirement is to score the runs quickly.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":2366,"value":"

","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":1958,"value":"$4c","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":2228,"value":"
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","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":1311,"value":"
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Appendix

All the tables and charts that were used as the starting point to upload the data and experiment a bit to see which visualization works well. Note: These are not a part of the visualization. This section can be considered as a dump area where I have added all the extra viz/experiments I did while creating the visualization.

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