Analysis of Cricket using quantitative methods

Topics: Probability theory, Probability distribution, Normal distribution Pages: 24 (3305 words) Published: November 16, 2013

Table of Contents

Cricket involves numbers, the comparison of these numbers will give us an idea regarding how well a team is faring. The comparison of these number widely depends on Statistics to give us a rational conclusion. Cricket is therefore a sport which involves a lot of statistics, Statistics are needed to determine the performance of a team in various formats such as one day, international. It is also needed to determine the performance of an individual player over a period of time. Nowadays records are also maintained for List A and Twenty20 limited over matches. These matches are normally limited over games played domestically at the national level by leading Test nations. Since one-day internationals are a form of List A limited over matches, a player's List A statistics will include his ODI match statistics – but not vice versa. The data collected can of the following types.

General Data
Matches-Number of matches played.
Catches- Number of catches taken.
Stumpings- Number of stumpings made.

Batting data
Innings (I): The number of innings in which the batsman actually batted. Not outs (NO): The number of times the batsman was not out at the conclusion of an innings they batted in.1 Runs (R): The number of runs scored.

Highest score (HS/Best): The highest score ever made by the batsman. Centuries (100): The number of innings in which the batsman scored one hundred runs or more. Half-century (50): The number of innings in which the batsman scored fifty to ninety-nine runs (centuries do not count as half-centuries as well). Balls faced (BF): The total number of balls received, including no balls but not including wides.

Bowling Data
Overs (O): The number of overs bowled.
Balls (B): The number of balls bowled. Overs is more traditional, but balls is a more useful statistic because the number of balls per over has varied historically. Maiden overs (M): The number of maiden overs (overs in which the bowler conceded zero runs) bowled. Runs (R): The number of runs conceded throughout.

Wickets (W): The number of wickets taken throughout.
No balls (Nb): The number of no balls bowled throughout.
Wides (Wd): The number of wides bowled throughout.
Best bowling (BB): The bowler's best bowling performance, defined as firstly the greatest number of wickets, secondly the fewest runs conceded for that number of wickets Five wickets in an innings (5w): The number of innings in which the bowler took at least five wickets. Four wickets in an innings (4w), the number of innings in which the bowler took exactly four wickets, is sometimes recorded alongside five wickets, especially in limited overs cricket. Ten wickets in a match (10w): The number of matches in which the bowler took at least ten wickets; recorded for Tests and first-class matches only.

Data Collection for teams

Type of match format
No of matches won
No of matches lost
No of draws
Matches of no result
W/L ratio( Win/loss ratio)

With the above data obtained one can use certain statistical techniques to generate a logical conclusion. The various concepts ranging from samples & population to normal distribution will be discussed. The ways in which all this concepts are applied in the field of cricket will be shown.

Application of descriptive statistics to cricket

With the immense data generated per match, these numbers can be represented as pie charts, bar graphs, Ogives etc. Qualitative Variable
Nominal Scale: The usage of numbers on the jerseys to represent each player is a nominal scale. There is normally no order to the way these numbers are used. For example in the Indian Cricket team, the captain’s no is 7 & a fast bowler’s no is 2. Here the numbers are used only as labels and nothing else. Ordinal Scale: The way we rate one player above the other signifies ordinal scale, the grade used is used to signify who is a better player or more senior in the team. This...
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