It is time!! So last weekend, I turned the wheels, moved the levers and listened to the hiss of steam, as I cranked up my Shiny app GooglyPlusPlus. The ICC Men’s T20 World Cup is just around the corner, and it was time to prepare for this event. This latest GooglyPlusPlus is current with the latest Intl. men’s T20 match data, give or take a few. GooglyPlusPlus can analyze batsmen, bowlers, matches, team-vs-team, team-vs-all teams, besides also ranking batsmen, bowlers and plot performances in Powerplay, middle and death overs.
In this post, I include a quick refresher of some of features of my app GooglyPlusPlus. Note: This is a random sampling of the functions available. There are more than 120+ features available in the app.
Check out your favourite players and your country’s team with GooglyPlusPlus
Note 1: All charts are interactive
Note 2: You can choose a date range for your analysis
Note 3: The data for this app is taken from Cricsheet
T20Batsman tab
This tab includes functions pertaining to individual batsmen. Functions include Runs vs Deliveries, moving average runs, cumulative average run, cumulative average strike rate, runs against opposition, runs at venue etc.
For e.g.
a) Suryakumar Yadav’s (India) cumulative strike rate
b) Mohammed Rizwan’s (Pakistan) performance against opposition
2. T20 Bowler’s Tab
The bowlers tab has functions for computing mean economy rate, moving average wickets, cumulative average wicks, cumulative economy rate, bowlers performance against opposition, bowlers performance in venue, predict wickets and others
A random function is shown below
a) Predict wickets for Wanindu Hasaranga of Sri Lanka
3. T20 Match tab
The match tab has functions that can compute match batting & bowling scorecard, batting partnerships, batsmen performance vs bowlers, bowler’s wicket kind, bowler’s wicket match, match worm graph, match worm wicket graph, team runs across 20 overs, team wickets in 20 overs, teams runs or wickets in powerplay, middle and death overs
Here are a couple of functions from this tab
a) Afghanistan vs Ireland – 2022-08-15
b) Australia vs Sri Lanka – 2019-11-01 – Runs across 20 overs
4. T20 Head-to-head tab
This tab provides the analysis of all combination of T20 teams (countries) in different aspects. This tab can compute the overall batting, bowling scorecard in all matches between 2 countries, batsmen partnerships, performances against bowlers, bowlers vs batsmen, runs, strike rate, wickets, economy rate across 20 overs, runs vs SR plot and wicket vs ER plot in all matches between team and so on. Here are a couple of examples from this tab
a) Bangladesh vs West Indies – Batting scorecard from 2019-01-01 to 2022-07-07
b) Wickets vs ER plot – England vs New Zealand – 2019-01-01 to 2021-11-10
5. T20 Team performance overalltab
This tab provides detailed analysis of the team’s performance against all other teams. As in the previous tab there are functions to compute the overall batting, bowling scorecard of a team against all other teams for any specific interval of time. This can help in picking out the most consistent batsmen, bowlers. Besides there are functions to compute overall batting partnerships, bowler vs batsmen, runs, wickets across 20 overs, run vs SR and wickets vs ER etc.
a) Batsmen vs Bowlers (Rank 1- V Kohli 2019-01-01 to 2022-09-25)
b) team Runs vs SR in Death overs (India) (2019-01-01 to 2022-09-25)
6) Optimisation tab
In the optimisation tab we can check the performance of a specific batsmen against specific bowlers or bowlers against batsmen
a) Batsmen vs Bowlers
b) Bowlers vs batsmen
7) T20 Batting Performancetab
This tab performs various analytics like ranking batsmen based on Run over SR and SR over Runs. Also you can plot overall Runs vs SR, and more specifically Runs vs SR in Powerplay, Middle and Death overs. All of this can be done for a specific date range. Here are some examples. The data includes all of T20 (all countries all matches)
a) Rank batsmen (Runs over SR, minimum matches played=33, date range=2019-01-01 to 2022-09-27)
The top 3 batsmen are Mohamen Rizwan, V Kohli and Babar Azam
b) Overall runs vs SR plot (2019-01-01 to 2022-09-27)
c) Overall Runs vs SR in Powerplay (all teams- 2019-01-01-2022-09-27)
This plot will be crowded. However, we can zoom into an area of interest. The controls for interacting with the plot are in the top of the plot as shown
Zooming in and panning to the area we can see the best performers in powerplay are as below
8) T20 Bowling Performancetab
This tab computes and ranks bowlers on Wickets over Economy and Economy rate over wickets. We can also compute and plot the Wickets vs ER in all matches , besides the Wickets vs ER in powerplay, middle and death overs with data from all countries
a) Rank Bowlers (Wickets over ER, minimum matches=28, 2019-01-01 to 2022-09-27)
b) Wickets vs ER plot
S Lamichhane (NEP), Hasaranga (SL) and Shamsi (SA) are excellent bowlers with high wickets and low ER as seen in the plot below
c) Wickets vs ER in death overs (2019-01-01 to 2022-09-27, min matches=24)
Zooming in and panning we see the best performers in death overs are MR Adair (IRE), Haris Rauf(PAK) and Chris Jordan (ENG)
With the excitement building up, it is time you checked out how your country will perform and the players who will do well.
IPL 2022 has just concluded and yet again, it is has thrown a lot of promising and potential youngsters in its wake, while established players have fallen! With IPL 2022, we realise that “Sceptre and Crownmusttumble down” and that ‘theglories‘ of form and class like everything else are “shadows not substantial things” (Death the Leveller by James Shirley).
So King Kohli had to kneel, and hitman’ himself got hit. Rishabh Pant, Jadeja also had a poor season. On the contrary there were several youngsters who shone like Abhishek Sharma, Tilak Verma, Umran Malik or a Mohsin Khan
This post is about my potential T20 Indian players for the World Cup 2022 and beyond.
The post below includes my own analysis and thoughts. Feel free to try out my Shiny app GooglyPlusPlus and draw your own conclusions.
How often we hear that data by itself is useless, unless we can draw insights from it? This is a prevailing theme in the corporate world and everybody uses all sorts of tools to analyse and subsequently draw insights. Data analysis can be done in many ways as data can be sliced, diced, chopped in a zillion ways. There are many facets and perspectives to analysing data. Creating insights is easy, but arriving at actionable insights is anything but. So, the problem of selecting the best 11 is difficult as there are so many ways to look at the analysis. My Shiny app GooglyPlusPlus based on my R package yorkr can analyse data in several ways namely
Batsman analysis
Bowler analysis
Match analysis
Team vs team analysis
Team vs all teams analysis
Batsman vs bowler and vice versa
Analysis of in 3,4,5 in power play, middle and death overs
GooglyPlusPlus uses my R package yorkr which has ~ 160 functions some which have several options. So, we can say roughly there are ~500 different ways that analysis can be done or in other words we can gather almost roughly 500+ different insights, not to mention that there are so many combinations of head-on matches and one-vs-all matches.
So generating insights or different ways of analysis data alone is not enough. The question is whether we can get a consolidated view from the different insights. In this post, I try to identify the best contenders for the Indian T20 team. This is far more difficult than it looks. Do you select players on past historical performance or do you choose from the newer crop of players, who have excelled in the recent IPL season. I think this boils down the typical situation in any domain. In engineering, we have tradeoffs – processing power vs memory tradeoff, throughput vs latency tradeoff or in the financial domain it is cost vs benefit or risk vs reward tradeoff. For team selection, the quandary is, whether to choose seasoned players with good historical performance but a poor performances in recent times or go with youngsters who have played with great courage and flair in this latest episode of IPL 2022. Hence there is a tradeoff between reliable but below average performance or risky but superlative performances of new players.
For this I base my potential list from
Then (past history of batsmen & bowlers) – I have chosen the performance of batsmen and bowlers in the last 3 years. With we can arrive at those who have had reasonably reliable performance for the last 3 years
Now (IPL 2022) – Performance in the current season IPL 2022
A. Then (Jan 2020 – May 2022) – Batsmen analysis
In this section I analyse the performances of batsmen and bowlers from Jan 2022 – May 2022. This is done based on ranking, and plots of Runs vs Strike Rate in Power Play, Middle and Death overs
Also I analyse bowlers based on the overall rank from Jan 2022- May 2022. Further more analysis is done on Wickets vs Economy Rate overall and in Power Play, Middle and Death overs
a. Ranks of batsmen (Runs over Strike Rate) : Jan 2020 – May 2022
IPL 2022 just finished and clearly brings out the batsmen who are in great nick. It is always going to be a judgment call of whether to go for ‘old reliable’ or ‘new and awesome’.
a. Ranks of batsmen (Runs over Strike Rate) : IPL 2022
The best batsmen this season in Runs over Strike rate are
f. Best batsmen Runs vs SR in Death overs:IPL 2022
Top batsmen in death overs in IPL 2022
[Dinesh Karthik, Rahul Tewatia, MS Dhoni, KL Rahul, Azar Patel, Washington Sundar, R Ashwin, Hardik Pandya, Ayush Badoni, Shivam Dube, Suryakumar Yadav, Ravindra Jadeja, Sanju Samson]
OverallBattingPerformance in season
Kohli peaked in 2016 and from then on it has been a downward slide (see below)
Taking a look at Kohli’s moving average it is clear that he is past his prime and it will take a herculean effort to regain his lost glory
Similarly, Rohit Sharma’s moving average is constantly around ~30 as seen below
The cumulative average of Rohit Sharma is shown below
Comparing KL Rahul, Shikhar Dhawan, Rohit Sharma and V Kohli we see that KL Rahul and Shikhar Dhawan have had a much superior performance in the last 2-3 years. Rohit has averaged about ~25 runs every season.
Comparing the 4 wicket-keeper batsmen Sanju Samson, Rishabh Pant, Ishan Kishan and Dinesh Karthik from 2016
i) Runs over Strike Rate
We see that Pant peaked in 2018 but has not performed as well since. In the last 2 years Sanju Samson and Ishan Kishan have done well
ii) Strike Rate over Runs
For the last couple of seasons Rishabh Pant and Dinesh Kartik top the strike rate over the other 2
Similar analysis can be done other combinations of batsmen
Choosing the best batsmen from the above, my top 5 batsmen would be
Personally, I feel Ishan Kishan and Shreyas Iyer are a little tardy while playing express speeds, as compared to Sanju Samson or Rishabh Pant.
If you notice, I have not included both Virat Kohli or Rohit Sharma who have been below par for some time
C.Then (Jan 2020 – May 2022) – Bowler analysis
This section I analyse the performances of bowlers from Jan 2022 – May 2022. This is done based on ranking, and plots of Wickets vs Economy Rate in Power Play, Middle and Death overs
a. Ranks of bowlers (Wickets over Economy Rate) : Jan 2020 – May 2022
The most consistent bowlers Wickets over Economy Rate for the last 3 years are
[YS Chahal, Jasprit Bumrah, Mohammed Dhami, Harshal Patel, Shardul Thakur, Arshdeep Singh, Rahul Chahar, Varun Chakravarthy, Ravi Bishnoi, Prasidh Krishna, R Ashwon, Axar Patel, Mohammed Siraj, Ravindra Jadeja, Krunal Pandya, Rahul Tewatia]
b. Ranks of bowlers (Economy Rate over Wickets) : Jan 2020 – May 2022
The most economical bowlers since 2020 are
[Axar Patel, Krunal Pandya, Jasprit Bumrah, CV Varun, R Ashwin, Ravi Bishnoi, Rahul Chahar, YS Chahal, Ravindra Jadeja, Harshal Patel, Mohammed Shami, Mohammed Siraj, Rahul Tewatia, Arshdeep Singh, Prasidh Krishna, Shardul Thakur]
c.BestBowlers Wickets vs ER :Jan 2020 – May 2022
The best bowlers Wickets vs ER will be in the bottom right quadrant. The most consistent and reliable bowlers are
[YS Chahal, Jasprit Bumrah, Mohammed Shami, Harshal Patel, CV Arun, Ravi Bishnoi, Rahul Chahar, R Ashwin, Axar Patel]
d. Best bowlers Wickets vs ER in Powerplay:Jan 2020 – May 2022
The best bowlers in Powerplay are
[Mohammed Shami, Deepak Chahar, Mohammed Siraj, Arshdeep Singh, Jasprit Bumrah, Avesh Khan, Mukesh Choudhary, Shardul Thakur, T Natarajan, Bhuvaneshwar Kumar, WashingtonSundar, Shivam Mavi]
e. Best bowlers Wickets vs ER in Middle overs : Jan 2020 – May 2022
The most reliable performers in middle overs from 2020-2022 are
[YS Chahal, Rahul Chahr, Ravi Bishnoi, Harshal Patel, Axar Patel, Jasprit Bumrah, Umran Malik, R Ashwin, Avesh Khan, Shardul Thakur, Kuldeep Yadav]
f. Best bowlers Wickets vs ER in Death overs : Jan 2020 – May 2022
The most reliable bowlers are
[Harshal Patel, Mohammed Shami, Jasprit Bumrah, Arshdeep Singh, T Natarajan, Avesh Khan, Shardul Thakur, Bhuvaneshwar Kumar, Shivam Mavi, YS Chahal, Prasidh Krishna, Mohammed Siraj, Chetan Sakariya]
B) Now (IPL 2022)– Bowler analysis
a. Ranks of bowlers (Wickets over Economy Rate) : IPL 2022
The best bowlers in IPL 2022 when considering Wickets over Economy Rate
[YS Chahal, Umran Malik, Prasidh Krishna, Mohammed Shami, Kuldeep Yadav, Harshal Patel, T Natarajan, Avesh Khan, Shardul Thakur, Mukesh Choudhary, Jasprit Bumrah, Ravi Bishnoi]
a. Ranks of bowlers (Economy Rate over Wickets) : IPL 2022
The most economical bowlers in IPL 2022 are
[Axar Patel, Jasprit Bumrah, Krunal Pandya, Umesh Yadav, Bhuvaneshwar Kumar, Rahul Chahr, Harshal Patel, Arshdeep Singh, R Ashwion, Umran Malik, Kuldeep Yadav, YS Chahal, Mohammed Shami, Avesh Khan, Prasidh Krishna]
c.BestBowlers Wickets vs ER :IPL 2022
The overall best bowlers in IPL 2022 are
[YS Chahal, Umran Malik, Harshal Patel, Prasidh Krishna, Mohammed Shami, Kuldeep Yadav, Avesh Khan, Jasprit Bumrah, Umesh Yadav, Bhuvaneshwar Kumar, Arshdeep Singh, R Ashwin, Rahul Chahar, Krunal Pandya]
d. Best bowlers Wickets vs ER in Powerplay: IPL 2022
The best bowlers in IPL 2022 in Power play are
[Mukesh Choudhary, Mohammed Shami, Prasidh Krishna, Umesh Yadav, Avesh Khan, Mohsin Khan, T Natarajan, Jasprit Bumrah, Yash Dayal, Mohammed Siraj]
d. Best bowlers Wickets vs ER in Middle overs: IPL 2022
The best bowlers in IPL 2022 during middle overs
The best bowlers are
[YS Chahal, Umran Malik, Kuldeep Yadav, Harshal Patel, Ravi Bishnoi, R Ashwin]
e. Best bowlers Wickets vs ER in Death overs: IPL 2022
The best bowlers in death overs in IPL 2022 are
[T Natarajan, Harshal Patel, Bhuvaneshwar Kumar, Mohammed Shami, Jasprit Bumrah, Shardul Thakur, YS Chahal, Prasidh Krishna, Avesh Khan, Mohsin Khan, Yash Dayal, Umran Malik, Arshdeep Singh]
Typically in a team we would need a combination of 4 bowlers (2 fast & 2 spinner or 3 fast and 1 spinner) with an additional player who is all rounder.
For 4 bowlers we could have
JJ Bumrah
Mohammed Shami, Umran Malik, Bhuvaneshwar Kumar, Umesh Yadav
Arshdeep Singh, Avesh Khan, Mohsin Khan, Harshal Patel
YS Chahal, Ravi Bishnoi, Rahul Chahar, Axar Patel
Ravindra Jadeja, Hardik Pandya, Rahul Tewathia, R Ashwin
i) Performance comparison (Wickets over Economy Rate)
Bumrah had the best season in 2020. He has been doing quite well and has been among the wickets
ii) Performance comparison (Economy Rate over Wickets)
Bumrah has the best Economy Rate
We can do a wicket prediction of bowlers. So for example for Bumrah it is
iii) Performance evaluation(Wickets over Economy Rate)
Harshal Patel followed by Avesh Khan had a good season last year, but Umran Malik pipped them this year (see below)
iv) Performance analysis of spinners
a. Wickets over Economy Rate: 2022
Chahal has the best season followed by Bishnoi and Chahar this season
b) Economy Rate over WIckets
Axar Patel has the best economy rate followed by Rahul Chahar
Conclusion
The above post identified the best candidates for the Indian team in the future and beyond. In my T20 list, I have neither included Virat Kohli or Rohit Sharma. The data in T20 clearly indicates that they have had their days. There is a lot more talent around. The tradeoff is a little risk for a greater potential performance. My list would be
It is that time of the year when there is “a song in the air, the lark’s on the wing, and the snail’s on the the thorn“. Yes, it is the that time of year when the grand gala event of IPL 2022 is underway. So, I managed to wake myself from my Covid-induced slumber, worked up my ‘creaking bones‘ and cranked up the GooglyPlusPlus machinery.
So now, every morning, a scheduled CRON tab entry will automatically download the previous night’s match data from Cricsheet, unzip, process and transform it into the necessary format required by my R package yorkr, and make it available to my Shiny app GooglyPlusPlus. Hence the data is current and you have access to ‘analytics-in-the-now’!.
As you know in 2021, I added a lot of new features to GooglyPlusPlus, new tabs to do even more. analytics – or in other words there is “more GooglyPlusPlus per click!!”. So now, you have the following
Batsman tab: For detailed analysis of batsmen
Bowler tab: For detailed analysis of bowlers
Match tab: Analysis of individual matches, plot of Runs vs SR, Wickets vs ER in power play, middle and death overs
Head-to-head tab: Detailed analysis of team-vs-team batting/bowling scorecard, batting, bowling performances, performances in power play, middle and death overs
Team performance tab: Analysis of team-vs-all other teams with batting /bowling scorecard, batting, bowling performances, performances in power play, middle and death overs
Optimisation tab: Allows one to pit batsmen vs bowlers and vice-versa. This tab also uses integer programming to optimise batting and bowling lineup
Batting analysis tab: Ranks batsmen using Runs or SR. Also plots performances of batsmen in power play, middle and death overs and plots them in a 4×4 grid
Bowling analysis tab: Ranks bowlers based on Wickets or ER. Also plots performances of bowlers in power play, middle and death overs and plots them in a 4×4 grid
Also note all these tabs and features are available for all T20 formats namely IPL, Intl. T20 (men, women), BBL, NTB, PSL, CPL, SSM.
Note: All charts are interactive, which means that you can hover, zoom-in, zoom-out, pan etc on the charts
The latest avatar of GooglyPlusPlus2022 is based on my R package yorkr with data from Cricsheet.
Here are some random analysis that can be done by GooglyPlusPlus across the tabs. Note the app will be updated daily and the analytics will be current throughout the season of IPL 2022
A) Match tab
a) GT vs DC – 2 Apr 2022
Runs vs SR – Gujarat Titans
b) CSK vs LSG – 31 Mar 2022
Runs across 20 overs
c) KKR vs PBKS -Match wicket worm chart – 1 Apr 2022
B) Batsmen tab
a) Faf Du Plessis – Runs vs Deliveries
b) Sanju Samson – Runs against opposition
C) Bowler’s tab
a) D J Bravo – No of deliveries to wicket
b) Trent Boult – Wickets at Venues
D) Head-to-head tab
a) DC vs MI – Mar -2019 till date : Batting scorecard
b) CSK vs KKR – Jan 2019 till date : Runs vs SR
E) Team vs All Teams tab
a) Punjab Kings vs all Teams – Wickets vs ER in Power play
b) Rajasthan Royals vs all Teams : Jan 2019 till date : Runs vs SR in Power play
F) Optimisation tab
a) Batsmen vs Bowlers
b) Bowlers vs batsmen
G) Batting analysis
This tab is for ranking batsmen
a) Batsmen rank from 2019 till date (Runs over SR)
This post continues the analysis of IPL and T20 (men) batsmen and bowlers through animated charts. In my last post Analyzing player performance with animated charts! I had used animated horizontal bars to display the totalRuns or totalWickets over a 3 year ‘sliding window’. While that was cool, the only drawback of that animation was the batsman and bowler performance was measured in a single dimension of either total(mean) runs or total(mean) wickets.
I think to fairly describe batsmen and bowlers we need at least the following 2 attributes
Runs and Strike rate for batsmen and
Wickets and Economy rate for bowlers
So, I have created new animation charts which use these attributes for batsmen and bowlers.
The animated charts are
Based on a sliding window of 3 years (Jan 2008- Dec 2010, Jan 2009-Dec 2010,…, Jan 2019-Dec 2021)
I have taken the top 10 percentile and sometimes the top 5 percentile of batsmen and bowlers to keep the charts more manageable
The charts are based on gganimate().
Note 1: I tried several options for the animation before settling on this one. The animation may seem a bit jerky but, we can follow the progress of players more easily through the years
Note 2: Some charts may display points, without the corresponding names. I think this may be because the animation tries to create intermediate points between the charts.
Analytics is by definition, the science (& art) of identifying, discovering and interpreting patterns in data. There are different ways of capturing these patterns through charts (bar, pie, cumulative data, moving average etc.). One such way is the motion or animated chart which captures the changes in data across different time periods. This was made famous by Hans Rosling in his Gapminder charts.
In this post, I use animated charts, based on gganimate(), to display the rise and fall of batsmen and bowlers in IPL and Intl. T20 (men). I only did this for these 2 formats as they have sufficient data over at least 10+ years.
To construct these animated charts, I use a ‘sliding window’ of 3 years, so that we get a clearer view of batsman and bowler consistency. The animated charts show the performance of players for this moving window for e.g. Jan 2008- Dec 2010, Jan 2009-Dec 2011, Jan 2010- Dec 2012 and so on till Jan 2019- Dec 2021. This is done for both batting( total runs) and bowling (total wickets). If you would like to analyse the performance of particular batsmen, bowler during specific periods or for a team vs another team or in the overall T20 format, check out my post GooglyPlusPlus2021: Towards more picturesque analytics!
You clone/fork the code from Github here animation.
Important note: The year which is displayed on the side actually represents the last 3 years, for e.g. 2015 (2013, 2014, 2015) or 2019 (2017, 2018, 2019)
IPL Batting performance
We can see that Kohli stays in the top 3 from 2015-2019
2. IPL Bowling performance
Malinga ruled from 2010- 2015. Bumrah is in top 3 from 2019-2021
3. IPL Batting in Power play
Adam Gilchrist, Tendulkar, Warner, KL Rahul, Shikhar Dhawan have a stay at the top
4. IPL Batting in Middle overs
Rohit Sharma, Kohli, Pant have their stay at the top
5. IPL Batting Death overs
MS Dhoni is lord and master of the death overs in IPL for a rolling period of 10 years from 2011-2020. No wonder, he is the best finisher of T20 cricket
6. IPL Bowling Power Play
Bhuvanesh Kumar is in top 3 from 2014-2018 and then Deepak Chahar
7. IPL Bowling Middle overs
Toppers Harbhajan Singh, YS Chahal, Rashid Khan
8. IPL Bowling Death overs
SL Malinga, B. Kumar, JJ Bumrah and Rabada top the list across the years
9. T20 (men) Batting performance
Kohli, Babar Azam, P R Stirling are best performers
10. T20 (men) bowling performance
Saaed Ajmal tops from 2010-2014 and Rashid Khan 2018-2020
11. T20 (men) batting Power play
Shahzad, D Warner, Rohit Sharma, PR Stirling best performers
12. T20 (men) batting middle overs
Babar Azam is the best middle overs player from 2018-2021
13. T20(men) batting death overs
MS Dhoni, Shoaib Malik, V Kohli, David Miller are the best death over players
14. T20 (men) bowling Power play
Mohammad Nabi, Mujeeb ur Rahman, TG Southee are the best bowlers in power play
15. T20 (men) bowling middle overs
Imran Tahir from 2015-2017, Shadab Khan from 2018-2020, T Shamsi in 2021 top the tables
16. T20 (men) bowling death overs
Saaed Ajmal, A J Tye, Bumrah, Haris Rauf occupy the top slot in different periods
This latest update to GooglyPlusPlus2021 includes the following changes
a) All the functions in the ‘Batsman’ and ‘Bowler ‘tabs now include a date range, which allows you specify a period of interest.
b) The ‘Rank Batsman’ and ‘Rank Bowler’ tabs also include a date range selector, against the earlier version which had a ‘Since year’ slider see GooglyPlusPlus2021 bubbles up top T20 players in all formats!. The earlier ‘Since year’ slider option could only rank for the latest year or for all years up to the current year. Now with the new ‘date range’ picker we can check the batsman and bowler ranks in any IPL season or (any T20 format) or for a range of years.
c) Note: The Head-to-head and Overall performance tabs already include a date range selector.
There are 10 batsman functions and 9 bowler function that have changed for the following T20 and ODI formats and Rank batsman and bowler includes the ‘date range’ and has changed for all T20 formats.
GooglyPlusPlus2021 supports all the following T20 formats
I have included some random screen shots of some of using these tabs and options in GooglyPlusPlus2021.
A) KL Rahul’s Cumulative average in IPL 2021 vs IPL 2020
a) KL Rahul in IPL 2021
b) KL Rahul in IPL 2020
B) Performance of Babar Azam in Intl. T20 (men)
a) Babar Azam’s cumulative average from 2019
b) Babar Azam’s Runs against opposition since 2019
Note: Intl. T20 (women) data available upto Mar 2020 from Cricsheet
a) A J Healy performance between 2010 – 2015
b) A J Healy performance between 2015 – 2020
D) M S Dhoni’s performance with the bat pre-2020 and post 2020
There has been a significant decline in Dhoni’s performance in the last couple of years
I) Dhoni’s performance from Jan 2010 to Dec 2019
a) Moving average at 25+(Dhoni before)
The moving average actually moves up…
b) Cumulative average at 25+(Dhoni before)
c) Cumulative Strike rate 140+ (Dhoni before)
d) Dhoni’s moving average is ~10-12 (post 2020)
e) Dhoni’s cumulative average (post 2020)
f) Dhoni’s strike rate ~80 (post 2020)
E) Bumrah’s performance in IPL
a) Bumrah’s performance in IPL 2020
b) Bumrah’s performance in IPL 2021
F) Moving average wickets for A. Shrubsole in ODI (women)
G) Chris Jordan’s cumulative economy rate
We can see that Jordan has become more expensive over the years
G) Ranking players
In this latest version the ‘Since year slider’ has been replaced with a Date Range selector. With this we can identify the player ranks in any IPL, CPL, PSL or BBL season. We can also check the performance over the last couple of years. Note: The matches played and Runs over Strike rate or Strike rate over runs can be computed. Similarly for bowlers we have Wickets over Economy rate and Economy rate over wickets options.
a) Ranking IPL batsman in IPL season 2020
b) Ranking Intl. T20 (batsmen) from Jan 2019 to Jul 2021
c) Ranking Intl. T20 bowlers (women) from Jan 2019 – Jul 2021
d) Best IPL bowlers over the last 3 seasons (Wickets over Economy rate)
e) Best IPL bowlers over the last 3 seasons (Economy rate over wickets)
You can clone/download this latest version of GooglyPlusPlus2021 from Github at gpp2021-7
The IPL 2021 extravaganza has restarted again, now in Dubai, and it was time for me to crank up good ol’ GooglyPlusPlus2021. As in my earlier post, GooglyPlus2021 with IPL 2021 as it happens, during the initial set of IPL 2021 games,, a command script will execute automatically every day, download the latest data files, unzip, sort, process and put them in appropriate directories so that GooglyPlusPlus can work its magic on the data, with my R package yorkr. You can do analysis of IPL 2021 matches, batsmen, bowlers, historical performance analysis of head-to-head clashes and performances of teams.
Note: Since the earlier instalment of IPL 2021, there are 2 key changes that have taken place in GooglyPlusPlus.
Now,
a) All charts are interactive. You can hover over charts, click, double-click to get more details. To see more details on how to use the interactive charts, see my post GooglyPlusPlus2021 is now fully interactive!
You can try out my app GooglyPlusPlus2021 by clicking GooglyPlusPlus2021
The code for my R package yorkr is available at Github at yorkr
You can clone/fork GooglyPlusPlus2021 from github at gpp2021-6
IPL 2021 is already underway.
Some key analysis and highlights of the 2 recently concluded IPL matches
CSK vs MI
KKR vs RCB
a) CSK vs MI (19 Sep 2021) – Batting Partnerships (CSK)
b) CSK vs MI (19 Sep 2021) – Bowling scorecard (MI)
c) CSK vs MI (19 Sep 2021) –Match worm chart
Even though MI had a much better start and were cruising along to a victory, they lost the plot around the 18.1 th over as seen below (hover on the chart)
d
d) KKR vs RCB ( 20 Sep 2021)– Bowling wicket match
This chart gives the wickets taken by the bowler and the total runs conceded
e) KKR vs RCB ( 20 Sep 2021)– Match worm chart
This was a no contest. RCB batting was pathetic and KKR blasted their way to victory as seen in this worm chart
Note: You can also do historical analysis of teams with GooglyPlusPlus2021
For the match to occur today PBKS vs RR (21 Sep 2021) we can perform head-to-head historical analysis. Here Kings XI Punjab has been chosen instead of Punjab Kings as that was its name.
f) Head-to-head (PBKS vs RR) today’s match 21 Sep 2021
For the Rajasthan Royals Sanjy Samson and Jos Buttler have the best performance from 2018 -2021 as seen below
For Punjab Kings KL Rahul and Chris Gayle are the leading scorers for the period 2018-2021
g) Current ranking of batsmen IPL 2021
h) Current ranking of bowlers IPL 2021
Also you analyse individual batsman and bowlers
i) Batsman analysis
To see Rituraj Gaikwad performance checkout the batsman tab
j) Bowler analysis
Performance of Varun Chakaravarty
Remember to check out GooglyPlusPlus2021 for your daily analysis of matches, teams, batsmen and bowlers. Your ride will be waiting for you!!!
You can clone/fork GooglyPlusPlus2021 from github at gpp2021-6
GooglyPlusPlus2021 has been updated with all completed 31 matches
Every time I think that I have my R packages or Shiny apps all wrapped up, I find another idea trots up and knocks at my door. Since I intend to keep GooglyPlusPlus current with the latest data, I decided to include the ranking functions in my Shiny app GooglyPlusPlus.
Fortunately, since GooglyPlusPlus is based on my R package ‘yorkr‘ (see Introducing cricket package yorkr: Beaten by sheer pace!), I could make the necessary changes to the ranking functions in the package, so that it could be incorporated into my latest Shiny app GooglyPlusPlus2021!! To know how to use GooglyPlusPlus see my post Introducing GooglyPlusPlus
Note: GooglyPlusPlus can analyze batsmen, bowlers, matches and teams.
Ranking IPL batsmen (minMatches = 80) – The following table shows the ranking of IPL players who have played 80 matches or more
B) Identifying batsmen of potential and promise
Ranking IPL batsmen (minMatches =70) – If we reduce the minimum number of matches played to 70, then we see it pushes up KL Rahul above Kohli.
Ranking IPL batsmen (minMatches =60) – When the slider is moved to 60, we see that Rishabh Pant has a better mean average and mean strike rate and is also ranked above Kohli. We can identify promising players this way. However, it is also likely that some players may be just a bright flash in the pan
C) Ranking T20 bowlers (men)
D) Ranking NTB Batsmen
GooglyPlusPlus2021 can rank all T20 formats (IPL, BBL, Intl. T20 (men), Intl. T20 (women), NTB, PSL and WBB. Do give it a try!
Also remember that GooglyPlusPlus2021 includes close to 100+ functions which enable it to perform analysis of batsmen, bowlers, T20 matches, head-to-head confrontation of T20 teams and overall performance of T20 teams . To know more about GooglyPlusPlus2021 see Introducing GooglyPlusPlus
You can download the code for this app from Github at GooglyPlusPlus2021
I have updated my GooglyPlusPlus Shiny app with data from latest IPL 2020. GooglyPlusPlus 2020 is also based on my R package yorkr. To know more about yorkr (see Revitalizing R package yorkr.) Now you should be able to analyze IPL matches, teams, players upto IPL 2020. Note: My latest GooglyPlusPlus 2020 can analyze all formats of T20 matches. yorkr uses data from Cricsheet
There are 5 tabs in each of the T20 formats
i) Analyze T20 batsmen ii) Analyze T20 bowlers. iii) Analyze T20 match iv) Analyze T20 team
vs another T20 team v) Analyze overall performance of T20 against all other teams
I plan to update GooglyPlusPlus at least twice a year to keep it abreast of all the latest data of all T20 formats
In GooglyPlusPlus 2020 you can check out IPL data upto 2020, besides other T20 formats like BBL, PSL, NTB, WBBL, Intl. T20 etc.
Important note: My earlier app GooglyPlusPlus handled all T20 formats including ODI (men and women). Due to an issue with Shiny, I could not include ODI matches in GooglyPlusPlus 2020
Here are some snapshots from GooglyPlusPlus 2020
A. Batting – Runs vs Deliveries (Shreyas Iyer)
B. Batting – Cumulative Batting Average (Shubman Gill)
C. Bowling – Mean Economy Rate (T. Natarajan)
D. Bowling -Bowler’s wickets against opposition (N A Saini)
E. Match scorecard – CSK vs DC 2020-10-17
The scorecards batting and bowling are computed on the fly for all T20 matches
F. Match – Batsmen vs Bowlers (DD vs KKR 2015-04-20)
G. Head-to-head: MI vs KXIP all matches – Batting scorecard
H. Overall team performance- Team Bowler Wicket kind: Rajasthan Royals
Do take GooglyPlusPlus 2020 for a drive! While I have highlighted only IPL T20, because I have updated with the latest data, GooglyPlusPlus 2020 can also handle other T20 formats like BBL, Natwest, PSL, Intl. T20 (men &women) and WBB
The function below ranks the IPL batsmen post IPL 2020. Note: We can specify the minimum number of matches that should have played by the batsmen for the ranking. By varying this parameter we can identify upcoming stars versus those who are more consistent.
Giga thoughts ... 