PlayOn: The Basics Archives

June 30, 2006

Naming Patterns in Fantasy Races

We were interested in the names that people picked for their characters. Were there commonalities across the WoW races or did different races have their own naming conventions? So we parsed through all unique names in the January data in several ways - by first letter, by 3-letter prefix, and 3-letter suffix. Here are the top 10 lists for these different parses by race.

There were interesting findings throughout. The most common first letter of a name was "S". 10% of all names in the sample began with an "S". This was followed by "A" (7.6%) and "D" (6.7%). If anyone has access to the distribution of first letters of English names, please let us know how this matches to those.

Among the prefixes, it was interesting to see the prefix "Sha" appear in the top ten for all the races. It was also interesting to see racial differences. For example, we see references to "Moon", "Night" and "Star" among the Night Elf names, whereas we find references to "Dead/Death", "Mort" and "Malevolence" in the Undead names.

Posted by Nick & Eric

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February 17, 2006

The Level 60 Game

Anecdotally and from our own experiences, the game at level 60 is entirely different from the game pre-60. For one thing, level advancement is no longer the goal and most guilds become raid and instance oriented. We wanted to get a sense of this shift with numbers. And also, we wanted to see whether this is a gradual shift starting at level 40 or level 50, or whether this is indeed a drastic shift that occurs at level 60.

We decided to look at this via social network metrics. How different are characters in guilds at different levels? For this, we calculated the social network metrics (density, centrality, and combined connection times) for each character and found their means according to their level range.

The data suggest a sudden shift at 60 rather than a gradual change. Here are the 3 graphs showing the difference for the 3 metrics mentioned.

Server Sample: RP (High), PvE (High), PvE (High), PvP (High), PvP (High)
Sampling Period: Month of January
Sampling Resolution: ~12 minutes
Parsing Method: The sample unit is each unique character. Each character was tracked across the server logs. Total playing time, lowest observed level, highest observed level, guild affiliation, and zones seen in were parsed.
Data Filter: Only those characters who are in a guild.
Sample Size: 179,003 characters

Posted by Nick & Nic

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December 26, 2005

Restarts

Since I first began parsing the census data, I've always noticed that some people made negative progress over the sampling period. In other words, their ending level was lower than their starting level. The only way to do this is to have restarted a character using the same name. I never thought much about this, and always assumed that these were separate players who simply used the same names, and thus I always filtered these characters out (always around 0.3%).

Recently, Nic brought this issue up at our weekly meeting and we finally got around to talking about it. And as we talked about what was driving this phenomenon, it became clear that it probably wasn't the case that we were looking at two different players. Nic and Eric had also noticed this when they first started looking at the data (before I arrived this summer) and they suggested that these were players who decided to recreate a character using that name because they liked that name. And then I realized that there is no reason why someone would delete their character given that even when players quit they might want to come back at a later date. So we all started to realize that the majority of these characters with negative progress are probably made by the same player rather than two different players.

Altogether, we found 567 restarts in our sample. That came out to 0.3% of all characters we parsed. Plotting out the frequencies of characters that have been restarted is quite interesting. There were quite a few high level characters that were restarted.

Server Sample: RP (High), PvE (Medium), PvE (High), PvP (High), PvP (High)
Sampling Period: 10/14/2005 12:00 am - 10/30/2005 12:00 am
Sampling Resolution: ~12 minutes
Parsing Method: The sample unit is each unique character. Each character was tracked across the server logs. Total playing time, lowest observed level, highest observed level, guild affiliation, and zones seen in were parsed.
Data Filter: See below
Sample Size: 207,298 characters

Posted by The PlayOn Team

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November 28, 2005

Who's Farming?

We just wanted to share some farming-related data that goes well with what many on WoW servers have a gut-feeling about. First, here's the overall class distribution of characters. Given some recent articles on the habits of gold farmers, we felt an easy way of identifying them would be to filter characters by their play-time over the period of one month.

Now, we include only those characters in the top 99% percentile of play-time (n = 2413).

The trend is sharper if we only take the top 99.9% percentile of play-time (n = 245). Rogues and hunters together account for 85% of characters in that range.

Server Sample: RP (High), PvE (Medium), PvE (High), PvP (High), PvP (High)
Sampling Period: 8/01/2005 12:00 am - 8/30/2005 12:00 am
Sampling Resolution: ~12 minutes
Parsing Method: The sample unit is each unique character. Each character was tracked across the server logs. Total playing time, lowest observed level, highest observed level, guild affiliation, and zones seen in were parsed.
Data Filter: None
Sample Size: 241,378 characters

Posted by Nick & Eric

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November 04, 2005

Rate of Advancement (Overview)

We wanted to explore level advancement at a character level. In other words, a true sense of how much a character levels over a one month period. This also provides an approximation of the player's achievement motivation - how much they want to advance their character as quickly as possible. To do this, we looked at the first 10 days of the month and the last 10 days of the month and included only those characters that were observed in both periods. This was done so that we did not include new characters that started towards the end of the month - who presumably would have had less time to advance than those characters that were already there at the beginning of the month. This sampling method yielded 83,020 characters. We calculated a standardized measure of level advancement as follows.

Standardized Character Advancement Score: A character's raw advancement is simply the number of levels the character has advanced. In this case, we subtracted the starting level from the ending level (end of month - beginning of month). The problem is that over a one month period, a 10 level advancement by a level 1 character is much less significant than a 10 level advancement by a level 50 character. In other words, the advancement needs to be qualified by the starting level somehow. The method we used to standardize character advancement was to calculate the average (and standard deviation) of advancement for every starting level. In other words, compared with other characters who also started at level 10, were you above, below, or right on the curve? Mathematically, we did this by calculating the z-score of advancement for every character.

There were two large groups of characters that were excluded in this analysis. First, we excluded all characters who spent over 90% of their time in a city. We presumed that these were mules of one kind or another and they would simply introduce too much noise. 6,393 (or 7%) of the original sample were excluded this way. Then we excluded all characters who were already level 60 since by definition they couldn't advance anymore. This further excluded 14,408 (or 18.8%) of the remaining sample. Thus, we ended up with a sample of 62,035 characters. The means and standard deviations used to calculate the standardized scores were actually derived from this sample so we were making consistent comparisons.

Here is the plot of average level advancement over August by the starting level. We also have the full table of means and standard deviations below. We're using this article to set the stage for level advancement differences by server, class, and race.

Posted by Nick & Eric

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September 17, 2005

Fastest Leveling Times

Server Sample: RP (High), PvE (Medium), PvE (High), PvP (High), PvP (High)
Sampling Period: 8/07/2005 12:00 am - 8/14/2005 12:00 am
Sampling Resolution: ~12 minutes
Parsing Method: The sample unit is leveling event. We tabulate the time between a character's level and when we observe them at a new level. Only a player's online time is counted. We exclude the first leveling event from every character because it doesn't constitute the total amount of time to make that level.
Data Filter: None
Sample Size: 149,240 leveling events

To get a sense of the fastest leveling times, we calculated the top 1st percentile, 5th percentile, and 10th percentile of times it takes to get from one level to the next. We summed these times to get a lower bound on the time it takes to get to level 60. This is a lower bound because we're not tracking any actual characters from level 1 to 60 but the fastest times it took any character to get from one level to the next. Also, significantly lowered leveling times may be due to turning in quests where the work was done from the previous level.

Here is the plot for the time it took the fastest characters to reach the next level.

The graphs below show the time to level by class and top percentiles. Interestingly, several classes that overall have long leveling times had much lower leveling times in the top percentiles (i.e., Druids and Hunters).

Levels 1-20

Levels 21-40

Levels 41-60

The table below shows the estimated time to reach level 60 by class and top percentiles based on the data above. The lower bound produced by the top 1st percentile times hovered between 4 and 5 days. For the 5th percentile times, the lower bound was between 6 and 7 days. And finally, the lower bound was between 7 and 8 days for the top 10th percentile.

Finally, we chart the estimated time it takes for characters of different classes to reach level 60 by the top percentiles.

Posted by nickyee at 11:24 AM | Comments (6) | TrackBack

September 06, 2005

Distribution of Leveling Times

To get a better sense of the distribution of leveling times - whether most people level fairly quickly and the overall mean is skewed by laggers - we calculated the normalized score for every leveling event based on the character level. We then plotted all the normalized scores.

Normalized Score = Z Score = (X - Mean) / Standard Deviation

The plot shows that most people actually do beat the overall mean (a z-score of 0). While the average time it takes to get from level 1 to 60 is now 15.3 days, the median is 13.9.

Posted by Nick

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August 31, 2005

Change in Leveling Time Over Time

We reported before that on average it takes characters about 20 days to get from level 1 to 60. While analyzing newer data for other purposes, we noticed that the average leveling time had decreased. We then double-checked our numbers to make sure we weren't looking at a parsing or collation error. While our double-checking showed that the average leveling-time had indeed decreased, we uncovered an error made early on in estimating our sampling resolution.

The actual sampling resolution for the previous data was actually lower than we had estimated (every 11.82 minutes instead of 13.50 minutes - we have since switched to an algorithm that calculates exact time between samples). So the average leveling time to get to level 60 from our previous data set (early June 2005) should have been 18.0. The average leveling time to get to level 60 from our current August data set is 15.3. That's about a 15% reduction in leveling time. Our hunch is that we're seeing the activity of alt characters lowering the overall leveling time.

Posted by Nick

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August 15, 2005

Predictors of Character Abandonment

Server Sample: RP (High), PvE (Medium), PvE (High)
Sampling Period: Week 1: 6/10 - 6/17. Week 2: 07/05 - 07/12.
Sampling Resolution: ~14 minutes
Parsing Method: We tracked all unique characters in both periods. For each character, we noted their playing time, guild affiliation, group ratio, starting level, class, and race. Then we tabulated which of the characters observed in June were not observed in July (both 1 week periods). This way we generated two lists of characters - those who were observed again after a month and those that were not.
Data Filter: None
Sample Size: 75,314 characters

Once we had the list of characters along with whether they were observed again or not, we ran a logistic regression with the following variables as predictors: playing time, grouping ratio, level, guild size, and guild affiliation.

As expected, level and playing time were the best predictors of abandonment. Whether the character was guilded was the third best predictor. Interestingly, as long as a character was guilded, the size of the guild did not matter.

The model had an r-square of .23 and had a classification success rate of 75% for abandonment and 70% for retention.

Posted by Nick

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August 03, 2005

Character Abandonment

Server Sample: RP (High), PvE (Medium), PvE (High)
Sampling Period: Week 1: 6/10 - 6/17. Week 2: 07/05 - 07/12.
Sampling Resolution: ~14 minutes
Parsing Method: We tracked all unique characters in both periods. For each character, we noted their playing time, guild affiliation, group ratio, starting level, class, and race. Then we tabulated which of the characters observed in June were not observed in July (both 1 week periods). This way we generated two lists of characters – those who were observed again after a month and those that were not.
Data Filter: None
Sample Size: 75,314 characters

Of the 75,314 characters observed in the one-week period in June, 46% were not observed in a one-week period in July. The lower level the character, the less likely they were observed again in July.

Now, there are other possible reasons for not observing a character again, such as being away for vacation or cycling through another character. But another way of looking at the data seems to suggest that we are indeed looking mostly at abandonment. Below is the histogram of characters who were observed in July but not in June. In other words, we are looking at a mix of new characters (who began after the June sample) and old characters (who didn't log on during the June sample). The majority of these characters are low level characters (as suggested by the abandonment hypothesis) rather than mid or high level characters (as suggested by the cycling hypothesis).

Interestingly, the server populations grew over this period. The June sample had 75,315 characters. The July sample had 83,253 characters. What is unclear is the relationship between character abandonment and player churn. Once we get more data, we'll rerun this using one month time frames.

Posted by Nick

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July 08, 2005

Leveling Time

Server Sample: RP (High), PvE (Medium), PvE (High)
Sampling Period: 6/13/2005 9:00 am - 6/20/2005 9:00 am
Sampling Resolution: ~14 minutes
Parsing Method: The sample unit is leveling event. We tabulate the time between a character's level and when we observe them at a new level. Only a player's online time is counted. We exclude the first leveling event from every character because it doesn't constitute the total amount of time to make that level.
Data Filter: None
Sample Size: 81,887 leveling events

We calculated the amount of time for every character to make a level within the sampling period of one week. The sampling unit was a leveling event. A leveling event was defined as the time it took for a character to be observed at a new level from their previous level. The first leveling event of every character is excluded because it doesn't constitute the total time it took to make that level (since presumably we started sampling when most characters were in the middle of their current level).

Below we plot the average amount of time it took for characters to make the next level from a given level. The curve is roughly linear with a mild dip at level 39 and a large spike at level 40. In other words, it takes people slightly less time to get to level 40 (playing harder) but then much longer to get to level 41. The curve also becomes steeper after level 53. Also of interest is the mild "step" effect throughout - leveling time is shorter at odd levels (close to new skills) and longer at even levels. All of these findings make sense given the new skills granted at even levels and the mount becoming available at level 40.

The time it takes to make the next level is roughly linear. The equation is approximately:

Leveling Time (in mins) = (Current Level x 17.8) - 49

If we assume that current level 60s spent these amounts of time while reaching level 60, then the average level 60 character has an accumulated play time of 20.3 days - a total of 61 8-hour work days, or roughly two full months of work days. 10% of all characters in WoW are currently level 60 and have spent this amount of time in the game.

The 10 day accumulated play time occurs around level 43. 20% of characters in WoW are at least level 43 and have spent 30 8-hour work days, or roughly one full month of work days in the game. Please note that we are counting characters and not players. Actual play-time will be higher for players who have multiple characters. Also, we only have non-PvP servers in this sample. Leveling times on PvP servers may be significantly higher. We'll try to get this data soon.

Here is the plot of the average accumulated play time by level.

The integral of the "time to next level" equation would give us the accumulated time on average needed to get to a certain level:

Accumulated Leveling Time (in mins) = 8.9 x Current Level (Current Level - 5.5)

Below are the tables for:
1) The average time it takes for a character to reach the next level from a given level
2) The average accumulated play-time of a character at a given level

Posted by nickyee at 10:49 AM | Comments (40) | TrackBack

June 22, 2005

Level Distribution

Server Sample: RP (High), PvE (Medium), PvE (High)
Sampling Period: 6/13/2005 9:00 am - 6/20/2005 9:00 am
Sampling Resolution: ~14 minutes
Parsing Method: The sample unit is each unique character. Each character was tracked across the server logs. Total playing time, lowest observed level, highest observed level, guild affiliation, and zones seen in were parsed.
Data Filter: None
Sample Size: 76,364 characters

Because level distributions change over time, we wanted to capture the current level distribution as well as present it here on the blog. 14% of observed characters were level 1. 25% were level 5 and below. 12.4% were level 55 and above. 9.8% were level 60.

By plotting only those characters above level 5, the spiking effect at every 10 levels becomes a little more noticeable. There are more characters at every 10 even level than the level preceding it. This is most noticeable for the 39-40. There are about twice as many level 40 characters as there are level 39 characters.

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June 21, 2005

Playing Time

Server Sample: RP (High), PvE (Medium), PvE (High)
Sampling Period: 6/13/2005 9:00 am - 6/20/2005 9:00 am
Sampling Resolution: ~14 minutes
Parsing Method: The sample unit is each unique character. Each character was tracked across the server logs. Total playing time, lowest observed level, highest observed level, guild affiliation, and zones seen in were parsed.
Data Filter: None
Sample Size: 76,364 characters

What's quite striking about the plot of playing time over the 60 levels are the spikes right before every 10 levels and the sudden drop right after. This is most prominent right before and after level 40 (for the mount in addition to the new skills). The pre-40 spike has a ramp-up starting at level 37 that the other spikes don't have. Level 39 characters were played on average 17.2 hours over the sample period compared with 12.9 hours with level 40 characters. In other words, level 39 characters were played about 33% more than level 40 characters.

The gradual increase in play time over the levels might be due to several factors:
1) casual players become discouraged to continue leveling and stop playing.
2) some players play several low to mid-level characters at the same time, although it could be that high level characters are more likely to have alts than mid-level characters.
3) increasing commitment as characters grow in level.
4) a spreading effect - characters at the high end are those in habit of putting in enough time since December to reach the high levels.

The average play-time per character over the period was 10.2 hours. Given that players are known to play multiple characters on their accounts, the average number of hours played per week per player is probably substantially higher. Also, 14% of observed characters were level 1, and 38% of these were never observed to advance beyond level 1.

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