In a country there is a voting system where all parties get represented in parliament if they meet a bar of $n$ percent.
Suppose that the parties are grouped into two groups of red $R_1, \dots R_k $ and blue parties $B_1, , B_l$ and they poll percentages $r_1, \dots r_k, b_1 \dots b_l$ with standard errors $sr_1 , \dots sr_k, sb_1, \dots sb_l$ (e.g. $R_1 \sim \mathcal{N}(r_1, sr_1)$ etc. ). There are two presidential candidates a red and a blue. The presidential candidate with the largest coalition in parliament, e.g. the largest sum $\sum_{i=1}^k R_k 1_{R_k > n}$ or $\sum_{i=1}^l B_l 1_{B_l > n}$ wins the election.
Now, suppose that a voter only cares about which presidential candidate wins. I.e. a voter preferring a red candidate would vote for one of the parties $R_1, \dots R_k$ (with abuse of notation).
It is clear that if $r_j$ and $sr_j$ are both much much smaller than $n$ then the vote of the voter effectively does not matter. Whereas if $r_j$ and $sr_j$ are both much much larger than $n$ then the vote effectively count as one. But what happens when $r_j$ is very close to $n$. How do I define and compute how much a vote on $r_j$ counts compared to in the limit where $r_j$ is large?
You can say that the total amount of votes is fixed $N$ a very large number.
I guess one way to define this efficiency is the probability that the vote tips the election and of course there is a brute force way to simulate this looking at how often the single vote tips the election. But that seems computationally infeasible to me. Is there a nice way to go about this problem?