I would not do that. It hides what you want to benchmark not behind one, but two subroutine calls. Which are expensive in Perl. Much better is it to use strings, as shown in the benchmark below. It shows that the foreach statement modifier is faster than the map BLOCK variant (which isn't at all surprising as the modifier doesn't need to create a scope - on addition to that, the map BLOCK variant makes an additional copy of the list), but while the double sub shows a 63% speed difference, the string version shows a 92% difference.

#!/usr/bin/perl

use strict;
use warnings;
use Benchmark qw(cmpthese);

our @foo = 1 .. 10;

sub a {
    my @list = @{shift()};
    $_ += 1 foreach @list;
    return \@list;
}

sub b {
    my @list = @{shift()};
    return [map {$_ += 1} @list];
}

cmpthese(500_000, {
    a => sub {a(\@foo)},
    b => sub {b(\@foo)},
    c => 'my @list = @foo; $_ += 1 foreach @list; \@list',
    d => 'my @list = @foo; [map {$_ += 1} @list]',
});

__END__

      Rate    b    d    a    c
b  68587/s   --  -9% -39% -52%
d  74963/s   9%   -- -33% -48%
a 111607/s  63%  49%   -- -22%
c 143678/s 109%  92%  29%   --
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Note that the fastest solution is map EXPR in void context (well, at least on my computer), as shown by the benchmark below:

#!/usr/bin/perl

use strict;
use warnings;
use Benchmark qw(cmpthese);
 
our @foo = 1 .. 10;

sub a {
    my @list = @{shift()};
    $_ += 1 foreach @list;
    return \@list;
}
    
sub b {
    my @list = @{shift()};
    return [map {$_ += 1} @list];
}

sub c {
    my @list = @{shift()};
    map {$_ += 1} @list;
    return \@list;
}

sub d {
    my @list = @{shift()};
    map $_ += 1, @list;  
    return \@list;
}
    
cmpthese(250_000, {
    a1 => sub {a(\@foo)},
    b1 => sub {b(\@foo)},
    c1 => sub {c(\@foo)},
    d1 => sub {d(\@foo)},
    a2 => 'my @list = @foo; $_ += 1 foreach @list; \@list',
    b2 => 'my @list = @foo; [map {$_ += 1} @list]',
    c2 => 'my @list = @foo; map {$_ += 1} @list; \@list',
    d2 => 'my @list = @foo; map $_ += 1, @list; \@list',
});
    
__END__

       Rate   b1   b2   c1   c2   a1   d1   a2   d2
b1  68493/s   --  -9% -11% -24% -38% -44% -51% -57%
b2  75529/s  10%   --  -2% -16% -32% -38% -46% -53%
c1  76687/s  12%   2%   -- -14% -31% -37% -45% -52%
c2  89606/s  31%  19%  17%   -- -19% -27% -36% -44%
a1 110619/s  62%  46%  44%  23%   --  -9% -21% -31%
d1 121951/s  78%  61%  59%  36%  10%   -- -13% -24%
a2 140449/s 105%  86%  83%  57%  27%  15%   -- -12%
d2 160256/s 134% 112% 109%  79%  45%  31%  14%   --
[download]