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On May 22 2013 19:23 1Dhalism wrote:Show nested quote +On May 22 2013 19:19 Stol wrote:On May 22 2013 19:15 Huckle wrote:
Like most people have said, the difference in expansion behavior of masters players versus silver players is huge in this study. If a silver zerg has two bases and injects always on both bases he will have a 100% inject rate. If a masters zerg has 4 bases and injects on 3 he will have a 75% inject rate. Which one in this case is better? Obviously, the masters zerg has a higher inject skill even though his percentage is lower. If you also realize that the majority of silver games are played on two bases this data becomes exceedingly irrelevant. Hatcheries that are not getting injected or only receive one inject are not taken into account, so its actually not that simple. Still there are a few things which would require some clarification. it is that simple. More hatcheries, less accuracy and yet more larva.
Yes, that can still be debated, but the comment on having 4 hatcheries and injecting 3 resulting in 75% inject rate is incorrect. That is not how the data presented works.
I've made several comments myself pointing out weaknesses and/or flaws in the analysis, but there's a difference between coming to another conclusion and simply reading the data wrong.
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On May 22 2013 19:19 Stol wrote:Show nested quote +On May 22 2013 19:15 Huckle wrote:
Like most people have said, the difference in expansion behavior of masters players versus silver players is huge in this study. If a silver zerg has two bases and injects always on both bases he will have a 100% inject rate. If a masters zerg has 4 bases and injects on 3 he will have a 75% inject rate. Which one in this case is better? Obviously, the masters zerg has a higher inject skill even though his percentage is lower. If you also realize that the majority of silver games are played on two bases this data becomes exceedingly irrelevant. Hatcheries that are not getting injected or only receive one inject are not taken into account, so its actually not that simple. Still there are a few things which would require some clarification and/or further investigation before one can draw any real conclusions.
I'm not so sure about that. Granted my idea of inject percentage is far simpler than the OP's. He uses time based percentages. For instance in his article he states, Inject % = (total # of minutes all hatches spent with injected larva) / (total # of minutes all hatches were active. So it is sort of that simple though. Uninjected hatches still contribute to the divisor in this case.
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Hmm also not realy since some people use queens to transfer (though mostly in lategame) and if you laying creep tumors it isnt that bad to safe up energy since you can then lay multiple tumors at once (like with orbitals safing up mules for a new expansion and to scan if needed) (this for the idea of looking at queen energy)
Maybe can look at the unspend resources per hatchery in the first say 15 minutes of the game,since larva in the end does effect the amount of resources you can spend,it does have some relation with your injections.
though this also has its flaws for example when people safe up to pop 7 mutas at once.
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On May 22 2013 19:30 Huckle wrote:Show nested quote +On May 22 2013 19:19 Stol wrote:On May 22 2013 19:15 Huckle wrote:
Like most people have said, the difference in expansion behavior of masters players versus silver players is huge in this study. If a silver zerg has two bases and injects always on both bases he will have a 100% inject rate. If a masters zerg has 4 bases and injects on 3 he will have a 75% inject rate. Which one in this case is better? Obviously, the masters zerg has a higher inject skill even though his percentage is lower. If you also realize that the majority of silver games are played on two bases this data becomes exceedingly irrelevant. Hatcheries that are not getting injected or only receive one inject are not taken into account, so its actually not that simple. Still there are a few things which would require some clarification and/or further investigation before one can draw any real conclusions. I'm not so sure about that. Granted my idea of inject percentage is far simpler than the OP's. He uses time based percentages. For instance in his article he states, Inject % = (total # of minutes all hatches spent with injected larva) / (total # of minutes all hatches were active. So it is sort of that simple though. Uninjected hatches still contribute to the divisor in this case.
No, a hatchery is only considered active after it has received its first inject, furthermore there was an exclusion rule saying that if the hatchery only received one inject throughout the game, it was not taken into consideration.
Edit:
On May 22 2013 11:09 dsjoerg wrote:Show nested quote +On May 22 2013 10:54 Poffel wrote:
I hate to be that guy, but apart from theoretizations on these very unexpected results, there also seems to be something odd about the data you're using.
Thank you for checking the data! I love "that guy"  usually he's me. I ran my code in "debug mode": + Show Spoiler +
Active:09.40 Injects:06.40 Last:14.24
Hatchery [3B80001] Injects: 04.44 05.27 06.15 07.01 07.44 08.25 09.12 10.00 11.13 13.02
Active:06.27 Injects:02.40 Last:14.24
Hatchery [4680001] Injects: 07.57 08.42 10.37 11.45
Hatchery [5D80001] Injects: 09.49
Active:09.39 Injects:06.40 Last:14.24
Lair [32C0001] Injects: 04.45 05.30 06.12 07.00 07.45 08.32 09.26 10.35 11.47 13.01
The Hatchery [5D80001] you're writing about gets only one inject, at 09.49. I dug into my code and there's an extra rule that I didn't describe in the article: a base must receive more than one inject to be considered at all for the inject % measurement.So, no bug here.
Exactly how is Inject % Computed?
Inject % = (total # of minutes all hatches spent with injected larva) / (total # of minutes all hatches were active)
A hatch is considered active from the first time a Queen injects it until the last time the hatch is selected by anyone for any reason, or the game ends. If we can someday get the actual hatch death time, we will use that instead.
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On May 22 2013 19:35 Stol wrote:Show nested quote +On May 22 2013 19:30 Huckle wrote:On May 22 2013 19:19 Stol wrote:On May 22 2013 19:15 Huckle wrote:
Like most people have said, the difference in expansion behavior of masters players versus silver players is huge in this study. If a silver zerg has two bases and injects always on both bases he will have a 100% inject rate. If a masters zerg has 4 bases and injects on 3 he will have a 75% inject rate. Which one in this case is better? Obviously, the masters zerg has a higher inject skill even though his percentage is lower. If you also realize that the majority of silver games are played on two bases this data becomes exceedingly irrelevant. Hatcheries that are not getting injected or only receive one inject are not taken into account, so its actually not that simple. Still there are a few things which would require some clarification and/or further investigation before one can draw any real conclusions. I'm not so sure about that. Granted my idea of inject percentage is far simpler than the OP's. He uses time based percentages. For instance in his article he states, Inject % = (total # of minutes all hatches spent with injected larva) / (total # of minutes all hatches were active. So it is sort of that simple though. Uninjected hatches still contribute to the divisor in this case. No, a hatchery is only considered active after it has received its first inject, furthermore there was an exclusion rule saying that if the hatchery only received one inject throughout the game, it was not taken into consideration. Edit: Show nested quote +On May 22 2013 11:09 dsjoerg wrote:On May 22 2013 10:54 Poffel wrote:
I hate to be that guy, but apart from theoretizations on these very unexpected results, there also seems to be something odd about the data you're using.
Thank you for checking the data! I love "that guy" usually he's me. I ran my code in "debug mode": + Show Spoiler +
Active:09.40 Injects:06.40 Last:14.24
Hatchery [3B80001] Injects: 04.44 05.27 06.15 07.01 07.44 08.25 09.12 10.00 11.13 13.02
Active:06.27 Injects:02.40 Last:14.24
Hatchery [4680001] Injects: 07.57 08.42 10.37 11.45
Hatchery [5D80001] Injects: 09.49
Active:09.39 Injects:06.40 Last:14.24
Lair [32C0001] Injects: 04.45 05.30 06.12 07.00 07.45 08.32 09.26 10.35 11.47 13.01
The Hatchery [5D80001] you're writing about gets only one inject, at 09.49. I dug into my code and there's an extra rule that I didn't describe in the article: a base must receive more than one inject to be considered at all for the inject % measurement. So, no bug here. Show nested quote +
Exactly how is Inject % Computed?
Inject % = (total # of minutes all hatches spent with injected larva) / (total # of minutes all hatches were active)
A hatch is considered active from the first time a Queen injects it until the last time the hatch is selected by anyone for any reason, or the game ends. If we can someday get the actual hatch death time, we will use that instead.
Well then this is an argument about degree. In this case yes, if one doesn't inject at least once then it would not be included in the divisor. However, If we make the assumption that a pro player will inject on his other bases at least twice (have you ever seen a pro or masters not inject on one of their bases that they can actually keep at least twice - I don't think I ever have.) Then that hatch will be considered active yet will contribute negatively to the inject percentage. This seems far more likely than a player injecting only once or not at all on a defensible expansion. My point remains, just not as expansively as I initially said.
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On May 22 2013 11:04 DemigodcelpH wrote:Show nested quote +On May 22 2013 06:17 Eventine wrote:
I swear, every time someone provides some data point, instead of sparking interesting debate, half the responses are like your data is wrong, my intuition is perfect and therefore i reject your findings. This. I find it amusing how every Zerg (well Zerg mains because I do play Zerg) player suddenly attempted to become a statistics major. Quite convenient, eh? To quote someone else: Show nested quote +A while back, someone collected similar data for workers-produced, time-supply-blocked, and surplus-resources-banked. Their results showed vast differences between the different divisions, implying that the above metrics are a major differentiating factor between the different divisions & skill levels. The empirical approach does work. The above metrics are also subjected to the same "real active game world" scrutiny in the same exact way, and yet they scale non-marginally with skill level.
You are saying that master level players are better at spending their resources than silver level players, which depends on good larva injects, but that master level players aren't really better at injecting? There are some other explanations, but I think it's more likely to be the case that the data is more difficult to interpret than you think.
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On May 22 2013 19:45 Grumbels wrote:Show nested quote +On May 22 2013 11:04 DemigodcelpH wrote:On May 22 2013 06:17 Eventine wrote:
I swear, every time someone provides some data point, instead of sparking interesting debate, half the responses are like your data is wrong, my intuition is perfect and therefore i reject your findings. This. I find it amusing how every Zerg (well Zerg mains because I do play Zerg) player suddenly attempted to become a statistics major. Quite convenient, eh? To quote someone else: A while back, someone collected similar data for workers-produced, time-supply-blocked, and surplus-resources-banked. Their results showed vast differences between the different divisions, implying that the above metrics are a major differentiating factor between the different divisions & skill levels. The empirical approach does work. The above metrics are also subjected to the same "real active game world" scrutiny in the same exact way, and yet they scale non-marginally with skill level. You are saying that master level players are better at spending their resources than silver level players, which depend on good larva injects, but that master level players aren't really better at injecting? There are some other explanations, but I think it's more likely to be the case that the data is more difficult to interpret than you think.
To be fair, silver zergs are also worse at getting up a good and stable economy. Hence they will not have as many minerals and will therefore require less injects to spend all of their minerals while still retaining similar inject percentages under the op's criteria.
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On May 22 2013 19:44 Huckle wrote:Show nested quote +On May 22 2013 19:35 Stol wrote:On May 22 2013 19:30 Huckle wrote:On May 22 2013 19:19 Stol wrote:On May 22 2013 19:15 Huckle wrote:
Like most people have said, the difference in expansion behavior of masters players versus silver players is huge in this study. If a silver zerg has two bases and injects always on both bases he will have a 100% inject rate. If a masters zerg has 4 bases and injects on 3 he will have a 75% inject rate. Which one in this case is better? Obviously, the masters zerg has a higher inject skill even though his percentage is lower. If you also realize that the majority of silver games are played on two bases this data becomes exceedingly irrelevant. Hatcheries that are not getting injected or only receive one inject are not taken into account, so its actually not that simple. Still there are a few things which would require some clarification and/or further investigation before one can draw any real conclusions. I'm not so sure about that. Granted my idea of inject percentage is far simpler than the OP's. He uses time based percentages. For instance in his article he states, Inject % = (total # of minutes all hatches spent with injected larva) / (total # of minutes all hatches were active. So it is sort of that simple though. Uninjected hatches still contribute to the divisor in this case. No, a hatchery is only considered active after it has received its first inject, furthermore there was an exclusion rule saying that if the hatchery only received one inject throughout the game, it was not taken into consideration. Edit: On May 22 2013 11:09 dsjoerg wrote:On May 22 2013 10:54 Poffel wrote:
I hate to be that guy, but apart from theoretizations on these very unexpected results, there also seems to be something odd about the data you're using.
Thank you for checking the data! I love "that guy" usually he's me. I ran my code in "debug mode": + Show Spoiler +
Active:09.40 Injects:06.40 Last:14.24
Hatchery [3B80001] Injects: 04.44 05.27 06.15 07.01 07.44 08.25 09.12 10.00 11.13 13.02
Active:06.27 Injects:02.40 Last:14.24
Hatchery [4680001] Injects: 07.57 08.42 10.37 11.45
Hatchery [5D80001] Injects: 09.49
Active:09.39 Injects:06.40 Last:14.24
Lair [32C0001] Injects: 04.45 05.30 06.12 07.00 07.45 08.32 09.26 10.35 11.47 13.01
The Hatchery [5D80001] you're writing about gets only one inject, at 09.49. I dug into my code and there's an extra rule that I didn't describe in the article: a base must receive more than one inject to be considered at all for the inject % measurement. So, no bug here.
Exactly how is Inject % Computed?
Inject % = (total # of minutes all hatches spent with injected larva) / (total # of minutes all hatches were active)
A hatch is considered active from the first time a Queen injects it until the last time the hatch is selected by anyone for any reason, or the game ends. If we can someday get the actual hatch death time, we will use that instead.
Well then this is an argument about degree. In this case yes, if one doesn't inject at least once then it would not be included in the divisor. However, If we make the assumption that a pro player will inject on his other bases at least twice (have you ever seen a pro or masters not inject on one of their bases that they can actually keep at least twice - I don't think I ever have.) Then that hatch will be considered active yet will contribute negatively to the inject percentage. This seems far more likely than a player injecting only once or not at all on a defensible expansion. My point remains, just not as expansively as I initially said.
Yes, I never said there arent factors playing in which can be hard to measure. I've even made similar comments regarding actual larvae generation myself. Its certainly a viable conclusion but its not the definite truth and thats a pretty big difference.
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On May 22 2013 19:52 Stol wrote:Show nested quote +On May 22 2013 19:44 Huckle wrote:On May 22 2013 19:35 Stol wrote:On May 22 2013 19:30 Huckle wrote:On May 22 2013 19:19 Stol wrote:On May 22 2013 19:15 Huckle wrote:
Like most people have said, the difference in expansion behavior of masters players versus silver players is huge in this study. If a silver zerg has two bases and injects always on both bases he will have a 100% inject rate. If a masters zerg has 4 bases and injects on 3 he will have a 75% inject rate. Which one in this case is better? Obviously, the masters zerg has a higher inject skill even though his percentage is lower. If you also realize that the majority of silver games are played on two bases this data becomes exceedingly irrelevant. Hatcheries that are not getting injected or only receive one inject are not taken into account, so its actually not that simple. Still there are a few things which would require some clarification and/or further investigation before one can draw any real conclusions. I'm not so sure about that. Granted my idea of inject percentage is far simpler than the OP's. He uses time based percentages. For instance in his article he states, Inject % = (total # of minutes all hatches spent with injected larva) / (total # of minutes all hatches were active. So it is sort of that simple though. Uninjected hatches still contribute to the divisor in this case. No, a hatchery is only considered active after it has received its first inject, furthermore there was an exclusion rule saying that if the hatchery only received one inject throughout the game, it was not taken into consideration. Edit: On May 22 2013 11:09 dsjoerg wrote:On May 22 2013 10:54 Poffel wrote:
I hate to be that guy, but apart from theoretizations on these very unexpected results, there also seems to be something odd about the data you're using.
Thank you for checking the data! I love "that guy" usually he's me. I ran my code in "debug mode": + Show Spoiler +
Active:09.40 Injects:06.40 Last:14.24
Hatchery [3B80001] Injects: 04.44 05.27 06.15 07.01 07.44 08.25 09.12 10.00 11.13 13.02
Active:06.27 Injects:02.40 Last:14.24
Hatchery [4680001] Injects: 07.57 08.42 10.37 11.45
Hatchery [5D80001] Injects: 09.49
Active:09.39 Injects:06.40 Last:14.24
Lair [32C0001] Injects: 04.45 05.30 06.12 07.00 07.45 08.32 09.26 10.35 11.47 13.01
The Hatchery [5D80001] you're writing about gets only one inject, at 09.49. I dug into my code and there's an extra rule that I didn't describe in the article: a base must receive more than one inject to be considered at all for the inject % measurement. So, no bug here.
Exactly how is Inject % Computed?
Inject % = (total # of minutes all hatches spent with injected larva) / (total # of minutes all hatches were active)
A hatch is considered active from the first time a Queen injects it until the last time the hatch is selected by anyone for any reason, or the game ends. If we can someday get the actual hatch death time, we will use that instead.
Well then this is an argument about degree. In this case yes, if one doesn't inject at least once then it would not be included in the divisor. However, If we make the assumption that a pro player will inject on his other bases at least twice (have you ever seen a pro or masters not inject on one of their bases that they can actually keep at least twice - I don't think I ever have.) Then that hatch will be considered active yet will contribute negatively to the inject percentage. This seems far more likely than a player injecting only once or not at all on a defensible expansion. My point remains, just not as expansively as I initially said. Yes, I never said there arent factors playing in which can be hard to measure. I've even made similar comments regarding actual larvae generation myself. Its certainly a viable conclusion but its not the definite truth and thats a pretty big difference.
Indeed. I find the conclusion interesting but I still find a lot of difficulties in interpreting the data as "player skill does not make a substantial difference in injecting accuracy and skill. However a better conclusion would be "player skill does not make a substantial difference in injection percentage as calculated by the OP."
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Well I'm still waiting for just about anyone to actually reply to either of my two comments  .
Especially this segment in my second post:
On May 22 2013 18:08 Stol wrote:
I was also unable to determine if you rebalance the graphs to account for the fact that 90% is max. As an example, 66% out of 100 is still 66 but if you account for the fact that 90 is max, you actually end up at roughly 73.3%. 60% out 90 is on the other hand roughly 66.7. So instead of having a difference of 6 percentage units we're now sitting at a difference of 6.6 percentage units. An increase of the 10% we left out of the equation when using 100% as max instead of 90%.
Ofc when using more than one queen per hatchery it would then be possible to reach over 100% but I dont really think anyone is doing that. If you rescale the numbers putting 90% as the maximum uptime instead of 100%, the difference between the leagues increases.
Edit: I'd prefer a reply to the other stuff as well though  .
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first thing that also came to my mind was lower league players having probably 2 base at a 12 min game while a masters for sure is on at least 3 bases
i'd even say lowleague players go for almost 20 min with 2 to 3 base while master is 4+ with macrohatches
I agree with people saying this data is heavily falsified by not taking into consideration how many hatches there are and how much easier it is to inject 2 hatches than 6
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On May 22 2013 20:02 robih wrote:
first thing that also came to my mind was lower league players having probably 2 base at a 12 min game while a masters for sure is on at least 3 bases
i'd even say lowleague players go for almost 20 min with 2 to 3 base while master is 4+ with macrohatches
I agree with people saying this data is heavily falsified by not taking into consideration how many hatches there are and how much easier it is to inject 2 hatches than 6
I think its wrong to say the data is heavily falsified, it does however not paint the full picture and people are drawing conclusions from it which it doesnt support.
Edit: And that goes for people on either side of the discussion.
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-_-.... Larvae inject's importance is related to your chioce of strategy. In some strats, you will be using your queen aggresively, where injects will have no importance.
In other strats, you will be agressive with larvae expensive units(i.e. lings).
Just setting a benchmark across several games, will yield nothing of value.
I don't really follow thestaircase, so i don't know what your exact goals are, but if it includes finding ways to get better as zerg. i would reccomend simply practising the basic mechanics and understanding of zerg.
i.e. Creepspread, Overlord placement, injection, droning benchmarks, how to be efficient with all the different units in different combinations against different units and scouting. <---- This much is Basic, and should be what all zerg above noob/entry/beginner level should be able to do without thinking about it.
THEN you can move up to "Advanced" stuff, like scouting and preparing for timings, timing for overlord placements, advanced creepspread(overlord puke walking with queens/queen drop to corners of the map/hatchery cancellations), micro, baneling mines, nydusworm play, drop play, baneling carpet bombing, slow pushes with swarmhosts..
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On May 22 2013 19:57 Stol wrote:Well I'm still waiting for just about anyone to actually reply to either of my two comments . Especially this segment in my second post: Show nested quote +On May 22 2013 18:08 Stol wrote:
I was also unable to determine if you rebalance the graphs to account for the fact that 90% is max. As an example, 66% out of 100 is still 66 but if you account for the fact that 90 is max, you actually end up at roughly 73.3%. 60% out 90 is on the other hand roughly 66.7. So instead of having a difference of 6 percentage units we're now sitting at a difference of 6.6 percentage units. An increase of the 10% we left out of the equation when using 100% as max instead of 90%.
Ofc when using more than one queen per hatchery it would then be possible to reach over 100% but I dont really think anyone is doing that. If you rescale the numbers putting 90% as the maximum uptime instead of 100%, the difference between the leagues increases. Edit: I'd prefer a reply to the other stuff as well though .
For comparison sake it doesn't matter about that 10% because proportionally it will yield the same result.
The graph would basically look the same, and the percent difference although as a raw number is higher it is out of 90 and not 100 so the difference is really the same. You would simply be manipulating numbers. Hopefully that makes sense and you see what you are suggesting would not make a real difference in data analysis.
And for what it is worth I'd love if this type of analysis could be done on the percent of the map covered by creep. I think that is the data that would really show the difference in leagues. Or simply number of active tumors.
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On May 22 2013 19:57 Stol wrote:Well I'm still waiting for just about anyone to actually reply to either of my two comments . Especially this segment in my second post: Show nested quote +On May 22 2013 18:08 Stol wrote:
I was also unable to determine if you rebalance the graphs to account for the fact that 90% is max. As an example, 66% out of 100 is still 66 but if you account for the fact that 90 is max, you actually end up at roughly 73.3%. 60% out 90 is on the other hand roughly 66.7. So instead of having a difference of 6 percentage units we're now sitting at a difference of 6.6 percentage units. An increase of the 10% we left out of the equation when using 100% as max instead of 90%.
Ofc when using more than one queen per hatchery it would then be possible to reach over 100% but I dont really think anyone is doing that. If you rescale the numbers putting 90% as the maximum uptime instead of 100%, the difference between the leagues increases. Edit: I'd prefer a reply to the other stuff as well though .
This is actually quite smart. The difference increases when you realize that one can only realistically attain 90% inject rate. Hence the masters players are actually slightly farther away from their silver league counterparts. In my mind it's sort of negligible but still there simply because we are just taking the difference between both inject percentages divided by 90. Of course a difference multiplied by 1/x is always going to be greater than the difference itself if x is less than 1 and greater than 0 and the difference is nonnegative.
The fact that there is a difference itself between any of the inject percentages is interesting regardless of what we set the theoretical limit at. What this methodology does do however is make the masters leaguers seem slightly better than their lower league counterparts and in that way I'm more inclined to trust it. But really, all we are doing is messing with numbers. What matters most is the calculated inject percentage and as such I'm not really inclined to desire a change in the graph or a scaling of the inject percentage by 1/.9. To me the 100% limit is fine since it is theoretically possible to attain. And, in the end all we are doing is scaling both things by the same number. As such this will not fundamentally alter the data set.
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On May 22 2013 20:39 FLuE wrote:Show nested quote +On May 22 2013 19:57 Stol wrote:Well I'm still waiting for just about anyone to actually reply to either of my two comments . Especially this segment in my second post: On May 22 2013 18:08 Stol wrote:
I was also unable to determine if you rebalance the graphs to account for the fact that 90% is max. As an example, 66% out of 100 is still 66 but if you account for the fact that 90 is max, you actually end up at roughly 73.3%. 60% out 90 is on the other hand roughly 66.7. So instead of having a difference of 6 percentage units we're now sitting at a difference of 6.6 percentage units. An increase of the 10% we left out of the equation when using 100% as max instead of 90%.
Ofc when using more than one queen per hatchery it would then be possible to reach over 100% but I dont really think anyone is doing that. If you rescale the numbers putting 90% as the maximum uptime instead of 100%, the difference between the leagues increases. Edit: I'd prefer a reply to the other stuff as well though . For comparison sake it doesn't matter about that 10% because proportionally it will yield the same result. The graph would basically look the same, and the percent difference although as a raw number is higher it is out of 90 and not 100 so the difference is really the same. You would simply be manipulating numbers. Hopefully that makes sense and you see what you are suggesting would not make a real difference in data analysis. And for what it is worth I'd love if this type of analysis could be done on the percent of the map covered by creep. I think that is the data that would really show the difference in leagues. Or simply number of active tumors.
There is a difference in the sense that what you would be measuring is the uptime of the actual injects available instead of the injects present on the hatchery. The fact that it would also affect every other aspect of the study along with standard deviation and so forth is irrelevant.
The difference is in fact not the same as people are making their assumptions based on the difference in percentage points which in this case is smaller than the difference present when balancing the values.
A point you could be making is people waiting with their first inject gaining extra energy before the injects occur which does have an impact on the possible larvae generated, but that is an entirely different matter and until the data also take into consideration when the queens themselves were spawned, one can only speculate on how much it would interfere with the end result.
Edit: To make my point more clear lets visit a somewhat extreme value. Say that instead of 90%, only a 10% uptime was possible due to queen energy generation.
A master player sitting at 8% would not look that much more impressive than a silver player sitting at 7% when we're disregarding the fact that 10% is the possible maximum and instead use 100%. It would only be a difference of 1 percentage point.
However, seeing as 10% is the actual maximum we instead get the following result: 8/10 = 80% and 7/10 = 70%. He is in fact hitting his injects at a much more consistent rate. So while the amount of larvae generated isnt substantially higher, the better player is still a lot better at hitting his injects properly.
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On May 22 2013 11:34 Poffel wrote:
In your model, if a player distributes a queen's injects between several hatcheries, his efficiency drops by a large margin.
The article states that a queen only regenerates enough energy for an inject every ~44 seconds and it takes 40 seconds for larvae to pop out after injecting. Therefore a single queen can only keep one hatchery injected 90% of the time. Therefore ~45% maximum on two hatcheries.
Consequently distributing a queen's injects between multiple hatcheries is massively inefficient by default. I fail to see how thats a failure of the system. They're still inefficient with their injects...the fact that their inefficiency is down to not having enough Queens is wholly irrelevant to whether or not inject efficiency is a useful measurement of ability.
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Very interesting finds.
You do need to argue for why you think the differences found are not important. Because there are differences, master players are better. One could make a case for that your finds are proof that injecting is an important skill to have. You're assuming the differences are small, but they could really be big. To the Statisticsmobile, I say!
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o.O interesting numbers, just checked my last 6 ladder games, half of which went to at least 3-4 bases, had a minimum uptime of 85% and a max of 90%... is 90% really the max uptime? Granted I kinda don't spread creep at all and prioritize injects for ling heavy style lol.
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I don't think there's anything surprising in the fact that perfect injection timing is not relevant in the later stages of the game, especially at master level. Most good master zerg players will only have about 4 queens injecting while using macro hatches for everything else (because queens take up supply, hatches do not) and most good zerg players will not rely on injects to rebuild their army.
What is important is to perfect injection timing in the first minutes of the game, because it makes a massive difference in how fast you can go 3base etc.
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EPT
