For ease of formatting and explanation, I'll be doing everything for the $5 \times 5$ example. However, the same trick works for any $n \times n$ antisymmetric matrix (though slightly differently for even $n$).
Suppose
$$
A =
\begin{pmatrix}0&0&0&0&a_{15}\\0&0&0&a_{24}&0\\0&0&a_{33}&0&0\\0&a_{42}&0&0&0\\a_{51}&0&0&0&0 \end{pmatrix}
$$
Here's a neat trick: we note that
$$
A^2 = \pmatrix{
a_{15}a_{51}&&&&\\
&a_{24}a_{42}&&&\\
&&(a_{33})^2&&\\
&&&a_{24}a_{42}&\\
&&&&a_{15}a_{51}\\
}
$$
So, the eigenvalues of $A^2$ are precisely $\{a_{15}a_{51}, a_{24}a_{42}, (a_{33})^2\}$.
Now, note that if $\lambda$ is an eigenvalue of $A$, then $\lambda^2$ must be an eigenvalue of $A^2$. This gives you six candidates for the eigenvalues of $A$.
In fact, with more thorough analysis, we can guarantee that the eigenvalues will be precisely $\lambda = \pm \sqrt{a_{i,(n+1-i)}a_{(n+1-i),i}}$ for $i = 1,\dots,\lfloor n/2\rfloor$ and, for odd $n$, $\lambda = a_{(n+1)/2,(n+1)/2}$.
Proof that this is the case: Let $e_1,\dots,e_n$ denote the standard basis vectors. Let $S_{ij}$ denote the span of the vectors $e_i$ and $e_j$.
Note that $A$ is invariant over $S_{i(n-i)}$ for $i = 1,\dots,\lfloor n/2\rfloor$. We may then consider the restriction $A_{i(n-i)}: S_{i(n-i)} \to S_{i(n-i)}$, which can be represented by the matrix
$$
\pmatrix{0 & a_{i(n-i)}\\a_{(n-i)i} & 0}
$$
It suffices to find the eigenvalues of this transformation.
For the case of an odd $n$, it is sufficient to note that $a_{(n+1)/2,(n+1)/2}$ lies on the diagonal with zeros in its row and column.
Another explanation: denote the matrix
$S = \pmatrix{e_1 & e_{n} & e_2 & e_{n-1} & \cdots}$
Noting that $S$ is orthogonal (i.e. $S^{-1} = S^{T}$), we find that
$$
SAS^{-1} =
\pmatrix{
0&a_{1,n}\\
a_{n,1}&0\\
&&0&a_{2,n-1}\\
&&a_{n-1,2}&0\\
&&&&\ddots
}
$$
This matrix is similar, and therefore has the same eigenvalues. However, it is also block diagonal.
Best Answer
Yes. Transposing with respect to the antidiagonal is equivalent to transposing in the normal way, then reversing the order of rows and reversing the order of columns. Reversing the order of rows or columns either leaves the determinant the same or multiplies it by $-1$, depending on whether the number of rows/columns is even or odd. Reversing both rows and columns thus leaves the determinant the same.