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[quote][quote]for most active players skill is not moving a lot outside of fluctuation[/quote]I call bullshit. We're talking about a multi-year time frame[/quote]
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1 |
[quote][quote]for most active players skill is not moving a lot outside of fluctuation[/quote]I call bullshit. We're talking about a multi-year time frame[/quote]
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| 2 |
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2 |
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| 3 |
i think we are not. Freund suggested that we are talking about very small time frames of a few games, and the impact a split data set has here on the quality of predictions.
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3 |
i think we are not. Freund suggested that we are talking about very small time frames of a few games, and the impact a split data set has here on the quality of predictions.
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| 4 |
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4 |
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| 5 |
my argument was that in these small time frames, elo movements are largely due to natural fluctuation and not so much skill improvement.
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5 |
my argument was that in these small time frames, elo movements are largely due to natural fluctuation and not so much skill improvement.
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| 6 |
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| 7 |
[quote]That example was cited in the other thread, too, and while it's clearly disfavoring the combined elo, apparently this situation is a lot less common than people having played too few games in either mode to make the respective predictions accurate.[/quote]
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7 |
[quote]That example was cited in the other thread, too, and while it's clearly disfavoring the combined elo, apparently this situation is a lot less common than people having played too few games in either mode to make the respective predictions accurate.[/quote]
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| 8 |
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8 |
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| 9 |
maybe
this
is
because
the
"all
games
in
history"
data
set
contains
just
too
much
garbage
(
ie.
newbies
playing
5
games
and
then
quitting,
smurfs,
etc)
.
i
suggested
that
after
someone
reaches
a
base
level
of
competency,
the
example
case
is
more
likely
to
happen
than
lack
of
data.
(
a
test
case
could
be
constructed
with
data
only
from
players
lvl
>
20/50/100)
|
9 |
maybe
this
is
because
the
"all
games
in
history"
data
set
contains
just
too
much
garbage
(
ie.
newbies
playing
5
games
and
then
quitting,
smurfs,
etc)
.
i
suggested
that
after
someone
reaches
a
base
level
of
experience,
the
example
case
is
more
likely
to
happen
than
lack
of
data.
(
a
test
case
could
be
constructed
with
data
only
from
players
lvl
>
20/50/100)
|
| 10 |
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|
10 |
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| 11 |
so i agree with your conclusion. similar to the newbie malus the different ratings would at first develop together and then eventually diverge. you could go further and weigh the number of games in either mode.
|
11 |
so i agree with your conclusion. similar to the newbie malus the different ratings would at first develop together and then eventually diverge. you could go further and weigh the number of games in either mode.
|
| 12 |
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12 |
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| 13 |
so for example if you never play 1v1s, your team rating would just carry over. if you play exactly the same amount in either type, there would be no carry-over at all, and interpolation would happen in between these extremes.
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13 |
so for example if you never play 1v1s, your team rating would just carry over. if you play exactly the same amount in either type, there would be no carry-over at all, and interpolation would happen in between these extremes.
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| 14 |
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14 |
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| 15 |
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15 |
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Predictiveness of the new ELO Split in 1v1-4v4