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[spoiler]I have found out that using smes for 8v8 or bigger even teams and sqrt sm otherwise is best.
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[spoiler]I have found out that using smes for 8v8 or bigger even teams and sqrt sm otherwise is best.
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2 |
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Also the 2 coms team wins exactly as often as the bigger team. Maybe the system compensates its own missweighting of 2 com players by distortions in the elo scale (my tested systems do the same so far).
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Also the 2 coms team wins exactly as often as the bigger team. Maybe the system compensates its own missweighting of 2 com players by distortions in the elo scale (my tested systems do the same so far).
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@Skasi I have thought of giving 2 coms players higher weighting when calculating averages, but not tested yet. (Comparing sums of different numbers of elos however would arbitrarily add/subtract 1500 and would no longer be invariant to shifts of the elo scale.)[/spoiler]
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@Skasi I have thought of giving 2 coms players higher weighting when calculating averages, but not tested yet. (Comparing sums of different numbers of elos however would arbitrarily add/subtract 1500 and would no longer be invariant to shifts of the elo scale.)[/spoiler]
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[quote]* Did you replicate existing system first? That means calculating elo progress over time for each player over time, using ZK's weighted elo?
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[quote]* Did you replicate existing system first? That means calculating elo progress over time for each player over time, using ZK's weighted elo?
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6 |
*
Did
you
compare
ZK's
weighted
elo
average
to
your
predictor
and
see
that
your
predictor
is
better
than
ZK's?
That
means
it
predicted
the
winner
more
reliably
than
weighted
elo?[/quote]@KingRaptor's
data
already
included
players'
elos
and
teams'
averages.
I
don't
know
whether
it
considered
weighting
and
progress
with
the
current
system,
but
I
doubt
it.
I
don't
even
know
how
the
weighted
average
is
calculated
currently
nor
how
elo
wins
and
losses
are
distributed
within
a
team
with
weightings.
If
@KingRaptor's
data
already
included
it
(
unlikely)
,
my
systems
will
probably
only
get
better
when
using
their
own
elo
progress.
If
not,
all
systems
will
probably
become
a
bit
better
and
we
don't
know
by
how
much.
In
any
case
my
systems
could
use
the
same
weightings.
|
6 |
*
Did
you
compare
ZK's
weighted
elo
average
to
your
predictor
and
see
that
your
predictor
is
better
than
ZK's?
That
means
it
predicted
the
winner
more
reliably
than
weighted
elo?[/quote]@KingRaptor's
data
already
included
players'
elos
and
teams'
averages.
I
don't
know
whether
it
considered
weighting
and
progress
with
the
current
system,
but
I
doubt
it.
I
don't
even
know
how
the
weighted
average
is
calculated
currently
nor
how
elo
wins
and
losses
are
distributed
within
a
team
with
weightings.
If
@KingRaptor's
data
already
included
it
(
unlikely)
,
my
systems
will
probably
get
even
better
when
using
their
own
elo
progress.
If
not,
all
systems
will
probably
become
a
bit
better
and
we
don't
know
by
how
much.
In
any
case
my
systems
could
use
the
same
weightings.
|
7 |
\n
|
7 |
\n
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8 |
I only know that the total elo win (loss) of a team with winning (loosing) probability p must be (1-p)*f(p), where f>0 any function with a line of symmetry at 50% (e.g. f(p)=c*(p*(1-p))^z) to guarantee the expectation value of elo change is zero. Probably z=0,f=c=30 is used currently. I still don't know how weighted average and weighted elo change is calculated, though.
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8 |
I only know that the total elo win (loss) of a team with winning (loosing) probability p must be (1-p)*f(p), where f>0 any function with a line of symmetry at 50% (e.g. f(p)=c*(p*(1-p))^z) to guarantee the expectation value of elo change is zero. Probably z=0,f=c=30 is used currently. I still don't know how weighted average and weighted elo change is calculated, though.
|
9 |
\n
|
9 |
\n
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10 |
Thanks for the data, @Anarchid. Should I assume that all players have elo 1500 in the beginning? If you can include the elos that the players had respectively at the time of those games and their weighted team average, I don't have to write an own programm for the test. Recalculating and storing all players' elos will be quite extensive. At best there would be 2 columns for the teams' weighted averages and 32 columns for the player elo slots, where the looser team always starts at the 17th of those columns like in @KingRaptor's data. If "smes" or "sqrt sm" will be better than current even when using current elo progress, they will probably be even better, when using their own. But for testing them with their own progress it might be easier to use existing zk infrastructure than coding new programms.
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10 |
Thanks for the data, @Anarchid. Should I assume that all players have elo 1500 in the beginning? If you can include the elos that the players had respectively at the time of those games and their weighted team average, I don't have to write an own programm for the test. Recalculating and storing all players' elos will be quite extensive. At best there would be 2 columns for the teams' weighted averages and 32 columns for the player elo slots, where the looser team always starts at the 17th of those columns like in @KingRaptor's data. If "smes" or "sqrt sm" will be better than current even when using current elo progress, they will probably be even better, when using their own. But for testing them with their own progress it might be easier to use existing zk infrastructure than coding new programms.
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