The biggest indicator of a player's skill is their kills/minute. Not kills/death. A very slow-reaction player with poor hand-eye coordination can hide in spawn and get a kill every 4 minutes. This does not take any skill. The reason why kills/minute is the best indicator of skill is because in order to achieve it a number of important factors need to be satisfied. First, game-sense. A player must know where to be, at the right time, and when to anticipate the enemy. If somebody is getting many K/M then it indicates they have game-sense, otherwise, they be stuck in places on the map without much enemy action. Second, reaction-time. If one frequently gets into fire-fights and wins most of them, then it generally means that player has a superior reaction time. Since the faster player shoots first, shoot first, kill first, generally speaking of course. Lastly, superior hand-eye coordination, i.e. basically aim. It is conceivable that one has superior reaction time, but very poor aim, and that can lead the player to dying more often. Thus, when somebody has a high K/M rate, then it means their game-sense, reaction-time, and hand-eye coordination are working better than expected.
Some might object to the use of K/M as a measurement of skill. But then one has to supply a better indicator. For example, suppose the alternative, "caps per minute", C/M, is proposed. The problem with this measured is that one can have poor game-sense, poor hand-eye coordination, and poor reaction time, and still, despite all of that, get many caps/minute simply because they keep on retaking open flags. A relatively new player can achieve a high C/M rate by learning the routes and making it their sole purpose to cap as much as possible. Therefore, C/M is not a good measurement of skill. And so, if one objects to K/M, then one should a better alternative statistic to use.
Now we get to the interesting part.
I took the data of the top 101 players from the server. I took the top 101 for the sole purpose because those are some of the most frequent players on the servers. Below is a histogram plot of those top 101 players.
View attachment 18102
Notice how the data is not normally distributed. The four players who are in the over 2.11 K/M range break the normality. The four players who are in that range happen to all be former competitive DOD players. When these four players are removed from the data set look how shockingly normal it looks. There is a center at 22 height, and the other bars, on each side, are almost perfectly symmetrical.
In a way it makes sense why these four players create statistical anomalies. The rest of the data set consist of casual gamers. It is irresponsible to analyze this data by including four outcasts in the data set. Therefore, I have removed these four players and reduced the data set down to 97 players.
With this adjusted I ran four statistical tests to check for normality.
Anderson-Darling Test: 92% probability of normal distribution.
Jarque?Bera Test: 98% probability of normal distribution.
d'Agostino-Pearson Test: 96% probability of normal distribution.
Shapiro-Wilks Test: 97% probability of normal distribution.
Cramer-von Mises Test: 90% probability of normal distribution.
These observations support the hypothesis that K/M is an appropriate measure of skill since the skill level is normally distributed.
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The mean K/M score (in the adjusted data set) is 1.2
The standard deviation is 0.35
Therefore, if your personal K/M score is one standard deviation above the average, i.e. 1.55 K/M or above, you are in the top 16% of the skill among players. If your personal K/M score is two standard deviations above the average, i.e. 1.9 K/M or above, you are in the top 2% of the skill among players.
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However, kills/death, K/D, as many would say, is not a good measure of skill. Here is the plot of the top 101 players and their K/D scores.
View attachment 18103
At first glance this picture looks normal. It has a spike in the center and symmetry on both sides. However, the right has, one extra column spike, which suggests this data is not normal. Let us see what various normality tests indicate.
Anderson-Darling Test: 25% probability of normal distribution.
d'Agostino-Pearson Test: 37% probability of normal distribution.
Shapiro-Wilks Test: 51% probability of normal distribution.
Cramer-von Mises Test: 21% probability of normal distribution.
The picture and these tests strongly suggest that K/D is not even log-normal.
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One may also wonder between the relationship between K/M and K/D.
Here is the scatter plot of K/M vs K/D for each player. In this graph the two data sets were not adjusted.
View attachment 18104
Here the x-axis are K/M scores and y-axis are K/D scores.
The Pearson correlation coefficient is equal to .13
Therefore, there is probably no relationship between a gamers K/D and skill level. Some players with low K/D scores may be higher skilled and some players with high K/D scores may be lower skilled. Everyone already agrees with this sentiment, namely, K/D does not equate to skill. However, it is nice when the data actually supports that hypothesis.
Some might object to the use of K/M as a measurement of skill. But then one has to supply a better indicator. For example, suppose the alternative, "caps per minute", C/M, is proposed. The problem with this measured is that one can have poor game-sense, poor hand-eye coordination, and poor reaction time, and still, despite all of that, get many caps/minute simply because they keep on retaking open flags. A relatively new player can achieve a high C/M rate by learning the routes and making it their sole purpose to cap as much as possible. Therefore, C/M is not a good measurement of skill. And so, if one objects to K/M, then one should a better alternative statistic to use.
Now we get to the interesting part.
I took the data of the top 101 players from the server. I took the top 101 for the sole purpose because those are some of the most frequent players on the servers. Below is a histogram plot of those top 101 players.
View attachment 18102
Notice how the data is not normally distributed. The four players who are in the over 2.11 K/M range break the normality. The four players who are in that range happen to all be former competitive DOD players. When these four players are removed from the data set look how shockingly normal it looks. There is a center at 22 height, and the other bars, on each side, are almost perfectly symmetrical.
In a way it makes sense why these four players create statistical anomalies. The rest of the data set consist of casual gamers. It is irresponsible to analyze this data by including four outcasts in the data set. Therefore, I have removed these four players and reduced the data set down to 97 players.
With this adjusted I ran four statistical tests to check for normality.
Anderson-Darling Test: 92% probability of normal distribution.
Jarque?Bera Test: 98% probability of normal distribution.
d'Agostino-Pearson Test: 96% probability of normal distribution.
Shapiro-Wilks Test: 97% probability of normal distribution.
Cramer-von Mises Test: 90% probability of normal distribution.
These observations support the hypothesis that K/M is an appropriate measure of skill since the skill level is normally distributed.
---------
The mean K/M score (in the adjusted data set) is 1.2
The standard deviation is 0.35
Therefore, if your personal K/M score is one standard deviation above the average, i.e. 1.55 K/M or above, you are in the top 16% of the skill among players. If your personal K/M score is two standard deviations above the average, i.e. 1.9 K/M or above, you are in the top 2% of the skill among players.
---------
However, kills/death, K/D, as many would say, is not a good measure of skill. Here is the plot of the top 101 players and their K/D scores.
View attachment 18103
At first glance this picture looks normal. It has a spike in the center and symmetry on both sides. However, the right has, one extra column spike, which suggests this data is not normal. Let us see what various normality tests indicate.
Anderson-Darling Test: 25% probability of normal distribution.
d'Agostino-Pearson Test: 37% probability of normal distribution.
Shapiro-Wilks Test: 51% probability of normal distribution.
Cramer-von Mises Test: 21% probability of normal distribution.
The picture and these tests strongly suggest that K/D is not even log-normal.
----------
One may also wonder between the relationship between K/M and K/D.
Here is the scatter plot of K/M vs K/D for each player. In this graph the two data sets were not adjusted.
View attachment 18104
Here the x-axis are K/M scores and y-axis are K/D scores.
The Pearson correlation coefficient is equal to .13
Therefore, there is probably no relationship between a gamers K/D and skill level. Some players with low K/D scores may be higher skilled and some players with high K/D scores may be lower skilled. Everyone already agrees with this sentiment, namely, K/D does not equate to skill. However, it is nice when the data actually supports that hypothesis.


















