Hydrofoils have become a popular design addition to different kinds of vessels, particularly yachts and race boats. Predicting hydrodynamic forces acting on hydrofoils remains challenging, due to a wide operating regime and complex hydrodynamical phenomena. In this paper we investigate methods of decomposing the total drag force of a hydrofoil from high-fidelity Reynolds--Averaged Navier Stokes (RANS) and low-fidelity lifting line computational fluid dynamics simulations into its physical components. Namely, these are the wave-pattern, induced, and viscous drag components. These components were calculated using wake surveys in RANS, while a separation of downwash coefficients was used in the lifting line formulation. Reynolds numbers between $2.57\times10^5$ and $2.06\times10^6$ were simulated, which corresponded to chord Froude numbers between 0.5 and 4. We present various Froude number-dependent trends in these components which we observed from RANS. Lifting-line models were modified to account for free surface effects using a mirror image of the hydrofoil as well as free surface Green's function for the wave pattern; and benchmarked against RANS results to gauge their accuracy. A parameter study of submergence depth was also carried using the lifting line model. Strong submergence-dependence of the induced and wave drag components was observed. Higher submergences led to overall lower total drag except at Froude numbers below around 1.5. In this intermediate regime, strong wave effects acted to increase the total drag compared to even shallower submergences. The efficiency of the numerical LL model here, demonstrated through an extensive parameter study on submergence depth, can be greatly exploited for exploring a large design space to optimise candidate designs during preliminary conception. However, great care should be taken in interpreting these results as the theoretical models employed, especially for the free surface effects, can be difficult to validate and still shows significant discrepancies with CFD.