If you just want to have a quick overview, look at the infographic. There is more content below the infographic for the people that want to read a bit about the topic. The drop-down content is mainly technical for people who either have a lot of time, commitment to the subject, or students.

**Click on the picture to see a bigger version.**

### **Note that PUBG have very good values overall, probably because it is/was a new game.

# Let’s get to know our audience.

### Methodology

The survey is based on existing academic research (namely “Why do you play? The development of the motives for online gaming questionnaire” by Demetrovics et al 2011, and is inspired by ESA’s annual report. The ESA reports have some flaws, and one of the main reasons people are criticizing them, is the fact that they say 97% of households in USA have a computer, which is 13% off other statistics (the American Community Survey), which means they are not showing a representative of the “real” audience. The reasons I write this is, even though we are inspired by them, we will not have this problem since we target gamers, specifically. Meaning that all our respondents already own computers.

Respondents

Our audience (N =3664) is mainly Danish (75%), the rest (25%) is obtained by forums such as Reddit, Steam, and Facebook. Note that not all of 3664 answered all questions: the lowest amount of answers on a question is 3269. If we assume that 500 million people play computer worldwide, this survey will have a confidence interval of 99% and a margin of error around 2,2%. This is higher than academic standards.

## Demografic

70% of the respondents are between 15-29, and 13,4% is under 15. This is a bit lower than my other surveys conducted on Reddit, this time we also gathered responses elsewhere.

Question: What is your age? |
|||||

Frequency | Percent | Valid Percent | Cumulative Percent | ||

Valid | Under 15 years old | 492 | 13,4 | 13,4 | 13,4 |

15-19 years old | 1155 | 31,5 | 31,5 | 45,0 | |

20-24 years old | 886 | 24,2 | 24,2 | 69,2 | |

25-29 years old | 517 | 14,1 | 14,1 | 83,3 | |

30-34 years old | 216 | 5,9 | 5,9 | 89,2 | |

35-39 years old | 154 | 4,2 | 4,2 | 93,4 | |

40 years old or older | 243 | 6,6 | 6,6 | 100,0 | |

Total | 3663 | 100,0 | 100,0 | ||

Missing | System | 1 | ,0 | ||

Total | 3664 | 100,0 |

We see that 95,3% of our respondents are male, so we can’t really make any analysis of the difference between male and female players. Another interesting fact is that the youngest players play CS (by far), and the oldest players play WoW.

It seems that gamers need their daily fix: 70,2% of the respondents play games daily, and 98% play a couple of times a week. – But there is a big difference in how much they play.

## Play time for an average player?

Frequency | Percent | Valid Percent | Cumulative Percent | ||

Valid | 1-5 hours/week | 381 | 10,4 | 10,5 | 10,5 |

6-10 hours/week | 653 | 17,8 | 18,0 | 28,5 | |

11-15 hours/week | 560 | 15,3 | 15,4 | 43,9 | |

16-20 hours/week | 532 | 14,5 | 14,7 | 58,6 | |

21-25 hours/week | 396 | 10,8 | 10,9 | 69,5 | |

26-30 hours/week | 360 | 9,8 | 9,9 | 79,4 | |

31-35 hours/week | 216 | 5,9 | 6,0 | 85,4 | |

36-40 hours/week | 151 | 4,1 | 4,2 | 89,5 | |

More than 40 hours/week | 380 | 10,4 | 10,5 | 100,0 | |

Total | 3629 | 99,0 | 100,0 | ||

Missing | System | 35 | 1,0 | ||

Total | 3664 | 100,0 |

As we see the most common is 6-10 hours a week. 1-30 hours a week have around 10% each, the interesting thing here is that it dips down, from 31-40 hours, but then it goes up to 10% again at more than 40 hours. That raises a couple of questions. First one is: Does age have a correlation?

The short answer is yes, and it significant. However, it doesn’t seem to be the defining factor in how much time is spent playing computer.

Explaining the effect (R2 squared .020) The question is a text question, so in theory you make correlations based on hidden values. To give you an idea about what people answered, the formula is Y= 5,006 -0,215x.

Every cell in a survey is given a hidden value, imagine this:

- Under 15
- 15-19 years
- 20-24 years

Everyone starts at value 5,006 in the “how much do you game each week” question. This is 21-25 hours weekly. So if you are between 20-24 years old, you will put 3 as “x”, and you will lose -0,645. It doesn’t seem as much but 1 point is the 5hours difference in average.

Coefficients^{a} |
||||||

Model | Unstandardized Coefficients | Standardized Coefficients | t | Sig. | ||

B | Std. Error | Beta | ||||

1 | (Constant) | 5,006 | ,086 | 58,225 | ,000 | |

What is your age? | -,215 | ,025 | -,143 | -8,679 | ,000 | |

a. Dependent Variable: How many hours do you play computer in an average week? |

Note: That this is only for guidance, it doesn’t take into consideration that +40 hours may be more than 40-44 hours. Each group is equally big.

## Is there a correlation between playing with friends and playing computer?

As above there is a significant correlation between how much you play with friends, and how much you play computer. However, this isn’t the main drive either. We see that 84,9% of respondents play with friends more often than rarely (occasionally, frequently and always).

## Other factors

2 other factors worth investigating are:

- If playing different games influence playtime in general, this will be covered in
**this**post about how the different game types have an effect on: gaming time, motivations, reputation, and much more. - The other one is if the motivation to play has an effect of play time, we will go into that after presenting the different motivations to play.

eSports survey results

- 78,3 % see eSport as a real sport.
- 22,9% don’t watch eSports, 48% watch a bit of eSports and 29 follow eSports.
- Where do people watch eSports? Twitch is far ahead with 73,8%, Youtube got 20,4% and 5,8% answered “others”.

Let’s dig deeper into the data, because there is something interesting in there.

Do you see eSport as a “”real”” sport? * Which sentence fits you best? Crosstabulation |
||||||

Which sentence fits you best? | Total | |||||

I dont watch esport | I watch esport | I watch abit of esport | ||||

Do you see eSport as a “”real”” sport? | Yes | Count | 376 | 990 | 1474 | 2840 |

% within Do you see eSport as a “”real”” sport? | 13,2% | 34,9% | 51,9% | 100,0% | ||

% within Which sentence fits you best? | 45,2% | 93,9% | 84,6% | 78,3% | ||

No | Count | 456 | 64 | 269 | 789 | |

% within Do you see eSport as a “”real”” sport? | 57,8% | 8,1% | 34,1% | 100,0% | ||

% within Which sentence fits you best? | 54,8% | 6,1% | 15,4% | 21,7% | ||

Total | Count | 832 | 1054 | 1743 | 3629 | |

% within Do you see eSport as a “”real”” sport? | 22,9% | 29,0% | 48,0% | 100,0% | ||

% within Which sentence fits you best? | 100,0% | 100,0% | 100,0% | 100,0% |

54,8% of the people that “don’t usually watch eSports”, don’t see eSport as a real sport, this category is pulling the number down to 78%. To the people saying they “watch eSport”, this number is 6,1%. So if we only asked people that watched eSports regularly, 93,9% would say eSport is a real sport. I think we see this in all categories, take for example golf: if you play it you want to defend it.

Another interesting factor is, if you play CS, League and PUBG you are more likely to see eSport as a real sport, around 86% of the players do. If you play Battlefield and GTA 5 it is only around 60% who see eSport as a real sport..

# Motivation

I was trying to measure 7 items: Coping, Skill development, Fantasy, Recreation, competition, Escape, and Social. So to do this I asked 24 questions. For example:

Competition got measured by the following (I play online games…): “because I enjoy competing with others”, “because I like to win”, “because it is good to feel that I am better than others” and “for the pleasure of defeating others”. The reason to ask these 4 questions is that if I only asked: “because I like to win?” it doesn’t really reflect completion alone.

### Technical stuff

Long explanation: So, in a factor analysis we take these 4 questions and see if they correlate, the idea is, that if it is important for a respondent to win, the 3 other questions will most likely be pretty important. A factor analysis can confirm this.

I had to remove 1 item from the list “because it helps me get into a better mood.” it simply fit into everything I was trying to measure, and that is not a good sign in factor analysis.

KMO and Bartlett’s Test |
||

Kaiser-Meyer-Olkin Measure of Sampling Adequacy. | ,888 | |

Bartlett’s Test of Sphericity | Approx. Chi-Square | 32975,415 |

df | 276 | |

Sig. | ,000 |

The stats looks awesome! And let’s take a quick look at the reliability. You can see a table with questions, factor loadings and Cronbach’s alpha.

Item |
Factor loadings |
Cronbachs alpha |

Because gaming helps me escape reality | 0,842 | .849 |

Because it makes me forget real life | 0,840 | |

To forget about unpleasant thing or offenses | 0,751 | |

Because gaming helps me to forget about daily hassles | 0,746 | |

For the pleasure of defeating others | 0,839 | .825 |

Because I like to win | 0,820 | |

Because it is good to feel that I am better than others | 0,803 | |

Because I enjoy competing with others | 0,685 | |

Because gaming sharpens my sense | 0,804 | .827 |

Because it improves my concentration | 0,801 | |

Because it improves my coordination skills | 0,760 | |

Because it improves my skills | 0,581 | |

Because I can get to know new people | 0,864 | .812 |

Because I can meet many different people | 0,853 | |

Because it is a good social experience | 0,670 | |

For recreation | 0,864 | .650 |

Because it helps me get rid of stress | 0,853 | |

Because it reduce tension | 0,670 | |

Because I can do things that I am unable to do or I am not allowed to do in real life | 0,804 | .749 |

To feel as if I was somebody else | 0,631 | |

Because I can be in another world | 0,613 | |

Because I enjoy gaming | 0,853 | .744 |

Because it is entertaining | 0,853 |

## The respondents choices

When the respondents were asked the 24 questions, they could choose between these 5 answers:

1 ‘Strongly disagree’

2 ‘Disagree’

3 ‘Neither agree nor disagree’

4 ‘Agree’

5 ‘Strongly Agree’

To illustrate it in a simple way.

And here are the numbers:

Social | Escape | Competition | Recreation | Skill_improvement | Fantasy | Entertaining | |

Mean | 3,41 | 3,00 | 3,56 | 3,91 | 3,52 | 3,12 | 4,66 |

As you see “escape” and “fantasy”, which scored the lowest, scored just over 3 “Neither agree nor disagree”. “Entertaining” is by far the most important factor.

### Correlations between factors.

Correlations |
||||||||

Social | Escape | Competition | Recreation | SkillDevelopment | Fantasy | Fun | ||

Social | Pearson Correlation | 1 | ,250^{**} |
,262^{**} |
,264^{**} |
,516^{**} |
,344^{**} |
,204^{**} |

Sig. (2-tailed) | ,000 | ,000 | ,000 | ,000 | ,000 | ,000 | ||

N | 3265 | 3263 | 3264 | 3264 | 3265 | 3262 | 3264 | |

Escape | Pearson Correlation | ,250^{**} |
1 | ,117^{**} |
,336^{**} |
,257^{**} |
,622^{**} |
,074^{**} |

Sig. (2-tailed) | ,000 | ,000 | ,000 | ,000 | ,000 | ,000 | ||

N | 3263 | 3266 | 3266 | 3265 | 3266 | 3265 | 3266 | |

Competition | Pearson Correlation | ,262^{**} |
,117^{**} |
1 | ,115^{**} |
,438^{**} |
,134^{**} |
,209^{**} |

Sig. (2-tailed) | ,000 | ,000 | ,000 | ,000 | ,000 | ,000 | ||

N | 3264 | 3266 | 3268 | 3267 | 3267 | 3265 | 3267 | |

Recreation | Pearson Correlation | ,264^{**} |
,336^{**} |
,115^{**} |
1 | ,334^{**} |
,280^{**} |
,340^{**} |

Sig. (2-tailed) | ,000 | ,000 | ,000 | ,000 | ,000 | ,000 | ||

N | 3264 | 3265 | 3267 | 3268 | 3267 | 3264 | 3267 | |

SkillDevelopment | Pearson Correlation | ,516^{**} |
,257^{**} |
,438^{**} |
,334^{**} |
1 | ,343^{**} |
,230^{**} |

Sig. (2-tailed) | ,000 | ,000 | ,000 | ,000 | ,000 | ,000 | ||

N | 3265 | 3266 | 3267 | 3267 | 3269 | 3265 | 3268 | |

Fantasy | Pearson Correlation | ,344^{**} |
,622^{**} |
,134^{**} |
,280^{**} |
,343^{**} |
1 | ,109^{**} |

Sig. (2-tailed) | ,000 | ,000 | ,000 | ,000 | ,000 | ,000 | ||

N | 3262 | 3265 | 3265 | 3264 | 3265 | 3265 | 3265 | |

Fun | Pearson Correlation | ,204^{**} |
,074^{**} |
,209^{**} |
,340^{**} |
,230^{**} |
,109^{**} |
1 |

Sig. (2-tailed) | ,000 | ,000 | ,000 | ,000 | ,000 | ,000 | ||

N | 3264 | 3266 | 3267 | 3267 | 3268 | 3265 | 3270 | |

**. Correlation is significant at the 0.01 level (2-tailed). |

Intern Correlations:

“Escape” and “Fantasy” are very strongly correlated (38% variance)

“Competition” and “Skill development” are strongly correlated (19% variance)

“Skill Development” and “Social” are strongly correlated (26,6% variance)

### Correlations with playtime.

Coefficients^{a} |
||||||

Model | Unstandardized Coefficients | Standardized Coefficients | t | Sig. | ||

B | Std. Error | Beta | ||||

1 | (Constant) | 1,990 | ,378 | 5,268 | ,000 | |

Social | ,335 | ,053 | ,130 | 6,353 | ,000 | |

Escape | ,254 | ,050 | ,113 | 5,044 | ,000 | |

Competition | -,015 | ,053 | -,006 | -,290 | ,772 | |

Recreation | -,270 | ,062 | -,086 | -4,324 | ,000 | |

SkillDevelopment | ,147 | ,065 | ,051 | 2,285 | ,022 | |

Fantasy | ,095 | ,054 | ,040 | 1,747 | ,081 | |

Fun | ,164 | ,080 | ,038 | 2,045 | ,041 | |

a. Dependent Variable: How many hours do you play computer in an average week? |

What we can see here is, if one of your main motivations to play is either to be social (meet new people) or to escape (from reality), you will most likely be playing more. However, if you play for recreation, you will be playing less. – The other items are not significant, and therefore not important to mention.

## Similarities from a study 6 years ago:

What we can read from this, is that our respondents had a higher mean value in general, when we know this, we can see the following:

Skill development and competition have highly increased since then – This is most likely due to eSport growth. It is backed by the fact that the only motivation factor that has lost value is recreation (relaxing). You might also notice that fun/enjoyment is missing. – The reason for this is the way the factor analysis was conducted: we could only measure with 2 items out of 3, so it not fair to compare them.

Young people are the most competitive, and the older you get, the more you play for recreation.

**Let’s have a quick discussion about this section because, while this measures which motivational factors gamers feel important when they play certain games, there are some pitfalls.**

**I asked what games you play the most, if a respondent play 80% League of legends and 20% Hearthstone, then it is not really precise.****Imagine that young people are competitive, and a lot of younger people play CS:GO. Which statement is right: that young people are more competitive, or that CS:GO players are more competitive? Both are true, but if I only tell you one of the facts, then you won’t get the full picture.**