Statistical analysis of boxing

Statement of Task3



Math Processes5

Simple math processes:5

Pearson’s Correlation Coefficient r:7




Plants Cited11

Statement of Undertaking

Boxing is a really good known athletics around the universe, where two disciplined jocks face off in a ring, trading blows until one of them submits or until Judgess decide a victor. The athletics revolves around throwing blows with their fists, and to form said jocks, their features are measured, and their achievements are recorded. Before a battle is held, a fighter’s profile is summarized, adverting the person’s tallness, weight, range, and their win/loss record. All of what is mentioned is said to play a large portion in the flow of the lucifer. The intent of this probe is to find if there is a relationship between a boxer’s range and his winning rate. The information that will be taken will be professional boxers’ measured range and their counts of wins and losingss for winning rate. The measuring of a boxer’s range is used to find how far he can widen his clout. The step of boxers’ ranges and their records of wins and losingss will be used to find if range is one of the larger factors that affect an athlete’s opportunities in a lucifer. Plan

The probe will include informations gathered from professional drawerss, which are their range and their counts of wins and losingss. The information that will be collected can be collected from official sites online, which have brief profiles of athletes’ measurings. I will be utilizing official sites since they tend to be up to day of the month and have accurate and legit information. The sum of informations collected will dwell of 30 jocks, half of whom are male and half are female. The information will be collected from official packaging sites such as, which contains the profiles of legion official drawerss and their measurings, which includes their range and wins and losingss. The information for one jock will dwell of his range and his win/loss record. I will try to avoid any professional jocks that are comparatively new to the professional phase, so I will be looking at drawerss with about at least five old ages of experience. Once the information has been acquired, the informations will be analyzed utilizing different mathematical procedures. A spread secret plan will be used to plot out said informations. The correlativity coefficient R will be calculated. The trial of independency will be used to find if there is a dependence between a boxer’s gender and winning rate. Datas

| Males| |

Boxer| Reach ( centimeter ) | Win Rate ( % ) |

1| 170| 90.00|

2| 173| 96.77|

3| 183| 96.88|

4| 194| 88.57|

5| 183| 87.88|

6| 207| 92.31|

7| 177| 94.29|

8| 183| 72.34|

9| 201| 100.00|

10| 198| 95.24|

11| 198| 80.77|

12| 179| 86.21|

13| 179| 89.29|

14| 183| 87.88|

15| 180| 89.66|

| Females| |

Boxer| Reach ( centimeter ) | Win Rate ( % ) |

1| 165| 89.47|

2| 161| 86.67|

3| 167| 66.04|

4| 166| 75.00|

5| 162| 81.25|

6| 168| 93.33|

7| 163| 76.47|

8| 162| 75.00|

9| 159| 88.46|

10| 167| 86.21|

11| 176| 80.95|

12| 171| 83.87|

13| 168| 82.61|

14| 166| 78.95|

15| 169| 90.48|

From the spread secret plan utilizing both male and female sets of informations, we can foretell that the deliberate correlativity would be weak and that a boxer’s win rate decrepit correlatives with his/her range. This can be seen as the information points are dispersed and plotted rather far from the line of best tantrum.

Mathematics Procedures

Simple math procedures:

Average: Males

* Reach in centimetres:

170+173+183+194+183+207+177+183+201+198+198+179+179+183+180=2788 2788/15= 185.8666667 centimeter

* Win rate in per centum:

90.00+96.77+96.88+88.57+87.88+92.31+94.29+72.34+100+95.24+80.77+86.21+89.29+87.88+89.66= 1348.09

1348.09/15= 89.87 %

Average: Females

* Reach in centimetres:

165+161+167+166+162+168+163+162+159+167+176+171+168+166+169= 2490 2490/15= 166 centimeter

* Win rate in per centum:

89.47+86.67+66.04+75+81.25+93.33+76.47+75+88.46+86.21+80.95+83.87+82.61+78.95+90.48=1234.76 1234.76/15=82.32

Average: both genders

* Reach in centimetres:


5278/30=175.93 centimeter

* Win rate in per centum:

1348.09+1234.76= 2582.85

2582.85/30= 86.095 %

We can see a little difference in win rate between the genders, with male drawerss holding a higher win rate by about 7 % . We can see a bigger difference between the range of the two genders but this would most probably be because work forces tend to turn and develop their organic structures of course larger than adult females.

Standard Deviation: Range:


Sx=170-185.872+173-185.872+183-185.872+194-185.872…180-185.87215 Sx=10.626


Sx=165-1662+161-1662+167-1662+166-1662+162-1662…169-166215 Sx=4.163

Both Genders:



We are able to see that the standard divergence is greater for the male drawerss female drawerss. We can presume that the pieces of informations from the work forces are spread farther from the mean as compared to the information from the adult females. This means that in respects to the informations collected, female drawerss seem to be closer in their mensural range as compared to the males. The standard divergence for both groups surpasses the deliberate criterion divergence for the separate male and female groups, intending that as a whole scope of informations, the ranges recorded wholly are even more dispersed out from the norm every bit compared to the genders individually.

Standard Deviation: Win rate:







Both Genders:


Sy = 7.8087

We can see from the deliberate criterion divergences that the standard divergence for the win rate of males and females are close to each other, intending that both have pieces of informations that are likewise far from the deliberate mean.

In respects to all informations recorded regardless of gender, the standard divergence is found to be somewhat higher, intending that the pieces of informations for both genders are somewhat further from the mean as compared to the separate gender groups of informations.

Subject| Reach| Win Rate| xy|

1| 170| 90| 15300|

2| 173| 96.77| 16741.21|

3| 183| 96.88| 17729.04|

4| 194| 88.57| 17182.58|

5| 183| 87.88| 16082.04|

6| 207| 92.31| 19108.17|

7| 177| 94.29| 16689.33|

8| 183| 72.34| 13238.22|

9| 201| 100| 20100|

10| 198| 95.24| 18857.52|

11| 198| 80.77| 15992.46|

12| 179| 86.21| 15431.59|

13| 179| 89.29| 15982.91|

14| 183| 87.88| 16082.04|

15| 180| 89.66| 16138.8|

16| 165| 89.47| 14762.55|

17| 161| 86.67| 13953.87|

18| 167| 66.04| 11028.68|

19| 166| 75| 12450|

20| 162| 81.25| 13162.5|

21| 168| 93.33| 15679.44|

22| 163| 76.47| 12464.61|

23| 162| 75| 12150|

24| 159| 88.46| 14065.14|

25| 167| 86.21| 14397.07|

26| 176| 80.95| 14247.2|

27| 171| 83.87| 14341.77|

28| 168| 82.61| 13878.48|

29| 166| 78.95| 13105.7|

30| 169| 90.48| 15291.12|

sum| 5278| 2582.85| 455634|

average| 175.9333| 86.1| 15187.8|

Pearson’s Correlation Coefficient R:


x-x ( y-y ) N or xyn-x Y











41.1078912.798 ( 7.8087 ) =.411344119



Correlation coefficient R is calculated to be really weak, intending that range and win rate demo really small correlativity and that a boxer’s range is non a large factor of his or her opportunities of triumph.

With low correlativity between a boxer’s range and win rate, I will now see if gender is a factor of an athlete’s win rate by ciphering qi squared.


Observed Valuess

| Numerical| Numerical| Total|

Category| A| B| A+B|

Category| C| D| C+D|

Total| A+C| B+D| N|

Calculating Expected Valuess

| Numerical| Numerical| Total|

Category| ( A+B ) ( A+C ) /30| ( A+B ) ( B+D ) /30| A+B|

Category| ( C+D ) ( A+C ) /30| ( C+D ) ( B+D ) /30| C+D|

Total| A+C| B+D| N|

Time intervals have been decided by norm of the winning rates of the two genders. ( 82.32+89.87 ) /2=86.095

Observed Datas Valuess

| Win rate & A ; gt ; 86 % | Win rate ? 86 % | Total|

Male| 2| 13| 15|

Female| 9| 6| 15|

Total| 11| 19| 30|

Calculated Expected Data Values

| Win rate & A ; gt ; 86 % | Win rate ? 86 % | Total|

Male| 5.5| 9.5| 15|

Female| 5.5| 9.5| 15|

Total| 11| 19| 30|

Degrees of Freedom

Df= ( Rows-1 ) ( Columns-1 )

( 2-1 ) ( 2-1 ) = 1


field-grade officer = Observed Frequency

iron = Expected Frequency


Chi Square Value Table

fo| fe| fo-fe| ( fe-fe ) ^2| ( fo-fe ) ^2/fe|

2| 5.5| 3.5| 12.25| 2.227272727|

13| 9.5| -3.5| 12.25| 1.289473684|

9| 5.5| -3.5| 12.25| 2.227272727|

6| 9.5| 3.5| 12.25| 1.289473684|

| | | amount: | 7.033492823|

?2= 7.033

Degrees of freedom= 1

Significance level= 5 %

5 % significance is used because it is the most common degree of significance used.

HO= Gender and win rate are independent of each other

H1= Gender and win rate are dependant of each other

The ?2 critical value at 5 % significance with 1 grades freedom is found to be 3.841. The ?2 value is greater than the critical value: 7.033 & A ; gt ; 3.841, the void hypothesis is rejected and it can hence be assumed that a boxer’s win rate is dependent of his or her gender.


The probe carried out to detect the correlativity of Win rate and range and win rate and gender has a few restrictions that have affected the result of the consequences.

One restriction is that although it is taken into history the range of each pugilist, their size and weight topographic points them in different categories for professional battles. This means that combatants would usually be contending people that have similar size, and theoretically, similar range. With similar range between two contending drawerss, the result of an athlete’s history of battles truly could hold been affected by other factors such as tactics and strength. Another restriction would be the fact that all of the gathered pieces of informations are all of high win rates. In pugilism records and conferences, if there is a pugilist who has won 90 % of his lucifers, there should besides be a pugilist who has lost that many of his lucifers every bit good.

The collected information covers 30 pieces. This is done to provide a big sum of informations, plenty to give moderately accurate consequences. Half of the informations gathered covered male drawerss and the other half covered female for the intent of look intoing the dependence of win rate on gender with qi squared.

One restriction in respects to the genders, is that there is no coeducational pugilism, intending that females and males do non vie with each other and are separated into two genders for packaging lucifers.

Although there is no specified threshold for winning rates in pugilism, the intervals decided in the qi squared tabular arraies can be justified as the below and above norms for the mean win rates of the two genders.


The found ?2 value of 7.033 culls the void hypothesis, that Win rate for drawerss is independent of their gender and accepts the alternate hypothesis, that a boxer’s win rate is dependent of a boxer’s gender. The extent of this computation is affected by the nature of the informations collected. The information that was collected for males and females consisted of high win rate per centums, and in pugilism, when there is an person who has won 70 % of his lucifers, there is certain to be an jock who has lost 70 % of his lucifers every bit good. The probe shows that there is a really low correlativity between ranges and win rate for drawerss irrespective of their gender. This result could hold been affected because of one of the mentioned restrictions above, where drawerss of similar size and weight are placed in the same category and battle, so reach becomes less of a factor for triumph as compared to strength, velocity, and tactics.

Plants Cited

Boxrec Boxing Records Ratings. 4 November 2012 & A ; lt ; hypertext transfer protocol: // & A ; gt ; . Boxrec. Boxrec Boxing Records.

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