Expected Index of Coincidence usually refers to a language's expected index of coincidence (1.73 for English, or 0.067 if you're not normalising).
The formula in question is usually used to determine the length of the key ($t$) given the (measured) $IC$ of received cipher-text. $IC$ is the probability that two randomly-selected letters from the cipher text are identical.
Let $X=\{ x_1,x_2,x_3,...x_L\}$ be the cipher-text. If we think the the poly-alphabetic cipher has period $t$, then we would expect each of the following:
\begin{eqnarray}
& X_1 =\{x_1, x_{t+1},x_{2t+1},...\}\\
& X_2 =\{x_2, x_{t+2},x_{2t+2},...\}\\
& \vdots \\
&X_t =\{x_t, x_{2t},x_{3t},...\}
\end{eqnarray}
to exhibit the same index as the plaintext ($\kappa_p$). So we can reconstruct $IC(X)$ as follows. Pick two letters at random, we want the probability that they match.
The probability that they are in the same $X_i$ is:
$$
\frac{tC(\frac{L}{t},2)}{C(L,2)} = \frac{L*(\frac{L}{t}-1)}{L(L-1)}
$$
The probability they are in different $X_i$s is:
$$
\frac{C(t,2)*\frac{L}{t}*\frac{L}{t}}{C(L,2)} = \frac{t(t-1)*\frac{L}{t}*\frac{L}{t}}{L(L-1)}
$$
- If they are in the same $X_i$ then they are both enciphered using the same alphabet: so the probability is $\kappa_p$
- If they are in different $X_i$s then they are enciphered using different alphabets, so we can assume they are randomly distributed: so the probability is $\kappa_r$
So the probability of two random letters matching is approximately
\begin{eqnarray}
IC(X) & \approx \frac{L*(\frac{L}{t}-1)}{L(L-1)}\kappa_p + \frac{t(t-1)*\frac{L}{t}*\frac{L}{t}}{L(L-1)}\kappa_r\\
& = \frac{(L-t)}{t(L-1)}\kappa_p + \frac{(t-1)*L}{t(L-1)}\kappa_r
\end{eqnarray}