Back in the days when Test Matches were the be-all and end-all of Cricket, data analysis simply meant runs scored and wickets taken. Then came ODIs, and the sports world woke up to strike rates, economy rates, chase precision and began to crunch video data to analyze player movements. Enter T20s, and we are now comparing ball-by-ball data streams with the existing legacy data to generate unprecedented real-time insights.
How is analytics revolutionizing Cricket experience on TV, laptops, mobiles and even live audience in the stadium today? How can teams, coaches, players, management, crickets analysts and even popular media like Hotstar benefit from it? To answer some of these questions, data scientists from FORMCEPT present to you a unique player rank-discovery algorithm translated into an intuitive, visually engaging platform. It goes beyond questions like ‘How many runs did you score?’ or ‘How many wickets did you take?’, and asks questions that truly matter:
like, ‘How valuable are you to your team?’
With IPL at hand, this question has become of paramount importance. With the right tools at the disposal of teams, it can be just a matter of extracting player insights in a few minutes to compare the player’s value to one’s own team, his value to another team, his key strengths, and his key weaknesses. These can then be fed into a comprehensive mix of player mapping and ranking mechanism to churn out the best strategy for the team in terms of player selection and even other crucial match choices.
But first, let us begin with the single index that is at the heart of all this – the MVPI, or the Most Valuable Player Index.
MVPI Analysis – What it Means
MVPI stands for Most Valuable Player Index which is used to identify the best players performing in a tournament for a particular team. In reality, it is a wishful proposition to quantify the form of players and / or the importance of their wickets, especially in the light of the fact that we do not have the data for pitch and weather conditions readily available in public.
But, that didn’t stop us at FORMCEPT from crunching numbers that are available, such as the number of runs scored and strike rates of the batsmen, economy rates of bowlers, wickets taken by them, and so on, to devise a single super-index that can rank players scientifically and aid in player selection for teams with evidential data.
Dataset from CricSheet Data
The dataset that we have used for our analysis is the publicly available Cricsheet Data which a reservoir of datasets for all the cricket matches i.e both domestic and international. The analysis focuses on T20 matches in particular, and accordingly, we have calculated and weighted the metrics for batsman and bowlers in context of the shorter version of the game.
- Batting Metrics – What Makes a Batsman Indispensable to a Team?
With a view to calculating and visualizing 360° batting ability in T20, five different metrics are considered for the batsman, as discussed in the subsequent sections below. In this article, we have taken the example of Chris Gayle to illustrate the different batting metrics.
- Hard Hitting Ability = (4*Fours + 6*Sixes) / Balls Played by Batsman
Hard Hitting Ability is a crucial factor in chasing a target in T20. Our analysis indicates that Chris Gayle has an excellent Hard Hitting Ability, given his phenomenal track record of scoring fours and sixes in matches by facing the minimum number of balls. He has scored a commendable 1.102 in this parameter.
- Finisher = Not Out innings / Total Innings played
Whether a batsman can race to the bottom or not, has pivotal impact on the chances of the team in winning the match. Finishing Ability of batsmen is particularly important in the second innings. Our analysis reflects that Chris Gayle doesn’t have a good Finishing Ability, as he gets out well before match closure most of the times – he scores a modest 0.146 in this parameter.
- Fast Scoring Ability = Total Runs / Balls Played by Batsman
A Fast Scorer batsman achieves a maximum score by facing the minimum number of balls. Why is this trait important? Simply because in the T20 format, wasting a ball can severely bring down the likelihood of a team winning a match.Chris Gayle is outstanding in this metric as he is able to rake in maximum runs while facing the minimum number of balls – he scores a whopping of 149.25 in this parameter.
- Consistency = Total Runs/Number of Times Out
A consistent player with a good run average is always an invaluable asset to his team. Virat Kohli, for example, has been the bedrock of India’s T20 wins in the recent years. In our analysis, Chris Gayle has scored above average in this parameter with score at 43.51.
- Running Between Wickets = (Total Runs – (4*Fours + 6*Sixes))/(Total Balls Played – Boundary Balls)
While boundaries get the jackpot, runs scored by Running Between Wickets brings the edge to the T20 chase. It is a must-have trait in batsmen to keep the scoreboard ticking even when the boundaries are not coming. Our analysis shows that Chris Gayle scores poorly in this parameter as he deals mostly in boundaries – singles and doubles are not his forte. His score is 0.502 in this parameter.
- Hard Hitting Ability = (4*Fours + 6*Sixes) / Balls Played by Batsman
- Bowling Metrics
Similar to the batsmen metrics, there are 5 different metrics that we have taken for the bowlers as well. We have taken the example of Amit Mishra to illustrate the bowling metrics.
- Economy = Runs Scored / (Number of balls bowled by bowler/6)
Economy is perhaps one of the important bowler traits in a T20 match. Why? Because chasing targets in T20 can get troublesome very quickly. For a team to ensure that the opposition team doesn’t score much, and to give the other bowlers a chance to put pressure on the batting team, good Economy bowlers are the ones to bet on. Our analysis shows that Amit Mishra has an economy of 7.02 which is highly commendable in T20 cricket.
- Wicket Taking Ability = Number of balls bowled / Wickets Taken
Wicket Taking ability is equally vital for a bowler for two key reasons – firstly, it puts pressure on the upcoming batsman, and secondly, it slows down the run rate briefly. Amit Mishra has scored 18.2 in terms of Wicket Taking Ability, because he takes relatively more wickets than an average bowler in a given number of overs.
- Consistency = Runs Conceded / Wickets Taken
This is a no-brainer – just because a bowler is taking wickets, doesn’t mean that he can be generous with runs – especially in T20. Consistent bowlers help a team to to get the maximum wickets while keeping runs at bay. Amit Mishra demonstrates high Wicket Taking Ability with an outstanding 21.12 score in this parameter.
- Crucial Wicket Taking Ability = Number of times Four or Five Wickets Taken / Number of Innings Played
Crucial Wicket Taking bowler is the anchor in the team whose one man performance can change the entire course of a match. Such bowlers help win a team due to their splendid performance as individuals. Amit Mishra scores 0.026 in this attribute for having taken more 4 and 5 wicket hauls than the average bowler.
- Short Performance Index = (Wickets Taken – 4* Number of Times Four Wickets Taken – 5* Number of Times Five Wickets Taken) / (Innings Played – Number of Times Four Wickets or Five Wickets Taken)
This parameter factors in good bowling periods demonstrated by a bowler throughout the tournament. Amit Mishra, who has turned around games many times for his team, scores 1.082 in this parameter.
Approach – Methodology and Analysis
Now that we understand what MVPI is and how it can identify a player’s potential value to a team, let us see how it works in a step-by-step manner:
- First, we used the 10 metrics (5-batting and 5 bowling) explained above to calculate the effectiveness of a player in the T20 format of cricket. We have benchmarked these scores against pre-defined ranges for different metrics and then normalized the scores to remove any metric bias, using the formula:
Score for a Feature = (Players Count – Rank in that Feature / Players Count)
- In the next step, we have carried out feature selection and have calculated the respective weights for each of the selected metrics. This is done using the Recursive Feature Elimination technique, which retains features by recursively narrowing down to smaller and smaller sets of attributes.
- The model is first trained by feeding an initial set of attributes followed by computation of relative importance of each attribute. Then, the least important attributes are eliminated from the present set of attributes. This approach is then repeated on the reduced set each time, until the desired number of attributes to be selected is eventually reached.
- The last step involves multiplying the importance (weight) of each feature with its value and then aggregating the weighted value set. This way, we get the final points corresponding to each player which are then sorted in decreasing order to get the Most Valuable Players in a particular.
Platform Screenshots – Take a Peek into Our Engaging T20 Analysis Platform
The above screenshot shows the library of player analysis across diverse metrics that one can access from our platform.
For each player, the depth of analysis and insight coverage is reflected in the screenshot above. At FORMCEPT, we are committed to bring insights at the most granular level to ensure an enriched experience for everyone.
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*Disclaimer: Please note that the opinions expressed in this article are purely based on analysis of data available with FORMCEPT at the time of such analysis, and are not intended to promote / defame any player or any other entity.