Table 8

Great Sage's Reckoning

According to results of the table, it is seen that the monetization from this item was the lowest one among all 3 in-game items with the rarity of “Arcana”. DOTA 2 fee from trades of this item was half as much comparing to “The Magus Cypher” and even lower comparing to “Manifold Paradox”. Nevertheless, the revenue of 425 dollars was generated in the period of 1 week only from trading of this item.

On the other hand, cases within another researched free-to-play online game Counter Strike: Global Offensive are needed to be researched by the same analysis with the visual presentation of results. Thus, the first case that will be reviewed by using the same analysis is “Glove case” and the visual chart will be constructed to see the fluctuation of prices for this item.

Figure 7. The Glove case's data

The table 5 shows data about “Glove case” about the average price per day pf sold day and the overall quantity of sold items.

Table 9

The glove case's data

The difference is seen between cases in Counter Strike: Global Offensive and “Arcana” items in DOTA 2. According to the figure and to the table 5, “glove case” have low average price - about 0.148 dollars, but because of this fact cases are selling itself in much greater amounts, the quantity of sold “glove cases” used to reach 50 thousand on the May 1 and the monetization from the trade of this item was 730 dollars what is nearly double as much comparing to “The Magus Cypher” item from DOTA 2. The method that Counter Strike uses is working super effectively in the case of “glove case” at least.

The other case that will be analyzed is “Spectrum case” as it was mentioned in previous sections.

Figure 8. The spectrum case's data

As it seen from the figure, “spectrum case” has medium fluctuation with the lowest price point of 0.134 and the highest price point of 0.147. Quantity of sold items does not depend of the price of the item, probable, because of the fact that price is decently low comparing to other in-game items such as skins for in-game weapons.

Table 10

The spectrum case's data

Table 6 shows results of data collected from spectrum case on the Steam market in the period of one week. It is seen that even that the average price of this case is lower comparing to the “glove case” - about 0.139 dollars versus 0.148 dollars in the case of “glove case”, the “spectrum case” had higher monetization than “glove case” - about 4986 dollars of pure fee went to Counter Strike from trades of this item in the period of 1 week.

The final case that will be researched is the “Danger Zone case”

Figure 9. The Danger Zone case's data

The figure showed that fluctuation in price is medium, but the fluctuation in quantity of sold items is pretty high. The possible reason for the rapid decrease in amount of sold items between day 6 and day 7 in the researched week was a sharp increase in the average price of “Danger Zone case” and this is why players were reluctant to purchase this item.

Table 11

The danger zone case's data

Thus, the data from the table and the from the figure shows that the average price in the case of “Danger Zone case” is much lower comparing to other two previously described Counter Strike cases, however, amounf of sold “Danger Zone cases” is higher comparing to other two types of cases, but the monetization is half as much as it was in the analysis of “glove case” and “spectrum case”. Nevertheless, 2772 dollars of pure profit were generated during only the week of trades of this “free” item that players can randomly receive by playing the game.

The next point that will be analysed in terms of this work is the testing of third hypothesis about possible correlation of players online and number of sold items. The tools that will be used and data that is going to be collected used to be described in previous sections, therefore, only results of data will be shown here. The first item will be “Manifold Paradox” from DOTA 2 and two figures shows data for 2018 and 2019:

Figure 10. Manifold Paradox's trades and players online in 2018

Figure 11. Manifold Paradox's trades and players online in 2019

It is seen that according to the figures there is no strong correlation between these variables in the case of “Manifold Paradox”. However, in the 2019 in May there was a sharp increase in number of sold items, but the growth of players online was not that high. At the same time, in 2019 after the may amount of players online started to fall in numbers and the amount of sold items also started to drop, but in higher percentages comparing to players online. In 2018 fluctuation was not that high within number of sold items, however, in august there was a sharp increase in number of sold items and at the same time there was a growth in number of players online. Nevertheless, correlation has to be visually presented:

Figure 12. Correlation between players online and trades

Moreover, the correlation was calcuted in Excel with the help of such funstion as CORREL() and it was equal to 0.57 for the 2 years what means that the correlation is a slight positive correlation, however, the number in 0.57 does not give the opportunity to claim that there is a strong correlation between these variables. However, there is 2 more items with rarity of “Arcana” for which correlation will be calculated for the same period of time.

Therefore, the next item from DOTA 2 will be “Demon Eater” for such in-game character as Shadow Fiend. Once again figures will be constructed with the aim to visually represent collected data.

Figure 13. Demon Eater's trades and players online in 2018

Figure 14. Demon Eater's trades and players online in 2019

The figures show that the quantity of sold items is lower in average comparing to “Manifold Paradox”, but the same fluctuation is seen on the both figures. However, the highest point of players online does not match the highest point of sold items. The correlation once again has to be visually presented

Figure 15. Correlation between players online and trades

The correlation is positive once again, but it is not strong, therefore in the case of such in-game item as “Demon Eater” from DOTA 2 there is once again the slight correlation and according to the function from Excel, it equals to 0.639 what is higher comparing to “Manifold Paradox”, but still not high enough to claim that the correlation is strong betwenn such variables as players online and amount of sold items.

The final item from DOTA 2 that will be analysed is “The Great Sage's Reckoning” and for this item also the same tools of analysis will be used with the aim to find correlation.

Figure 16. The Great Sage's Reckoning's trades and players online in 2018

Figure 17. The Great Sage's Reckoning's trades and players online in 2019

Figures shows that may in both 2018 and 2019 was the month with the highest amount of sold items, however, it was not the highest month in terms of online, but online was pretty high within these months anyways. The noticeable difference in amount of sold items is also seen between 2018 and 2019. The reasons for this can be diverse: hero could become more popular in games, because of the fact that there was an in-game update that used to make this hero better or any other reason. Now the correlation itself has to be visually presented

Figure 18. Correlation between players online and trades

The figure of correlation shows that there is no correlation between such variables as players online and amount of sold items per month. Indeed, the calculation in Excel shows that the correlation equals to 0.145 what means that the number is close to the 0 and it results to the fact that in the case of “The Great Sage's Reckoning” there is no correlation and the researched variables do not depend on each other.

At the same time, with the aim to test the hypothesis the same analysis should be done for in-game items from Counter Strike: Global Offensive - for cases. Thus, the first case that will be analysed is the “Glove case” and for this item the visual figures will be constructed with the aim to visiually support to the results of collected data

Figure 19. Glove case's trades and players online in 2018

Figure 20. Glove case's trades and players online in 2019

The figures show that the fluctuation in amount of sold items was decent, but not super high. Moreover, it is seen that the the highest point of sold items and the players online used to happen in the same month for both figures what can tell about possible high positive correlation between researched variables. With the aim to test this theory, correlation is needed to be calculated and visually presented:

Figure 21. Correlation between players online and trades

According to the figure with correlation between such variables as players online and amount of sold items for “Glove case” the correlation is positive and pretty high, but with the aim to calculate the exact number it is needed to use Excel function as it was in the case of “Arcana” items from DOTA 2. Therefore, the correlation equals to 0.949 what means that the correlation eagers to the perfect correlation with number of +1. Thus, the correlation is positive and it is high for the “glove case”. Nevertheless, it is the first in-game item that has the positive and strong correlation from all researched items at this moment, other 2 items from Counter Strike: Global Offensive have to be analysed with the aim to test third hypothesis.

The other in-game item that will be analysed is the “Spectrum case”. The same analysis will be done for this in-game item from Counter Strike:

Figure 22. The spectrum case's trades and players online in 2018

Figure 23. The spectrum case's trades and players online in 2019

The figures show the minimal fluctuation in the the 2019 both in amount of sold items and number of players online and decent fluctuion in 2018 for both variables. However, the fluctuation is not so vividly represented and cannot be seen via these 2 figures, therefore, once again another figure with correlation will be construncted and the correlation will be calculated:

Figure 24. Correlation between players online and trades

It is seen that positive fluctiation is present, but it is not that high comparing to the previous “Glove case”. Indeed, the correlation in this case equals to 0.62 what means that the correlation is slight and this result is similar to the result of correlation of the “Demon Eater” from DOTA 2. At the same time it the third item from all analysed in-game items that have slight and positive correlation.

Finally, the last in-game item from Counter Strike that will be reviewed is the “Gamma 2” case. This case replaces “Danger Zone case” for the reasons that were described previously. Two figures that show changes in researched variables within a period of 2 years will be constructed first:

Figure 25. Gamma 2 case's trades and players online in 2018

Figure 26. Gamma 2 case's trades and players online in 2019

The fluctuation is not high for both variables in both 2018 and 2019. At the same time in 2019 the highest point of players online matches with the highest point of sold items what might mean that some sort of relationship exists between researched variables in the case of “Gamma 2” case. However, to be completely sure about this fact it is needed to present another figure with actual correlation between these variables and calculate the exact number of correlation:

Figure 27. Correlation between players online and trades

The correlation is positive and near to be the strong one. However, the exact number is needed to claim that there is a strong correlation between amount of players online and amount of sold items in the “Gamma 2” case. The calculations shows that correlation equals to 0.742. It means that correlation is definitely positive, nevertheless, it is not enough to be totally sure and claim that correlation is strong. Because of the fact that 0.742 < 0.8, then it is not enough to claim that in this case the strong correlation is seen. There is a correlation, but variables have medium relationship from each other and not strong one how it was in the case of “Glove case”where correlation was higher than 0.9.

Now it is needed to conduct an independent t - test analysis for both DOTA 2 and Counter Strike: Global Offensive. The researched data was mentioned in the previous sections, now it is time to conduct the analysis with the aim to test the hypothesis that there is no difference between means of two groups of variables. First of all the DOTA 2 data will be studied and tested by using independent t - test in SPSS. The results are following:

Table 12