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tokens: differences between spots and the photosphere Δ T spot (= T phot − T spot ) are listed in Table 2 . We follow Unruh et al. ( 2008 ) and use a 1D radiative equilibrium stellar atmosphere model with a cooler effective temperature than the quiet photosphere to represent spots. Mean MURaM quiet star spectra and 1D model spectra with equivalent effective temperature agree very well, although small differences are present for all spectral types. To minimize the effect of model differences on the resulting spot intensities, ATLAS9 spectra were calculated from 1D model stellar atmospheres at effective temperatures T phot and T spot for the quiet star and spots, respectively. The ratio of intensities was multiplied with the quiet star intensities from MURaM to provide spot intensities for our models. We show Kepler band spot intensity contrasts, I ( T spot )/ I ( T phot ) − 1 in Fig. 3 (bottom panel) for all spectral types. In the Kepler band, spots always have negative contrasts several times larger than that of facular regions, regardless of limb distance. Spot contrasts become more negative with increasing stellar effective temperature (a direct consequence of the spot temperature differences chosen). 3 MODEL SETUP We performed a number of investigations using the light-curvemodelling approach described in Section 2 : obtaining typical variability levels assuming a Sun-like feature distribution and evaluating the impact of spot temperature, active region latitude, and facular-to-spot coverage fraction on variability. Here, we describe how Sun-like feature distributions are generated and the assumptions made. 3.1 Latitude and longitude distributions We aim to model brightness variability on rotational time-scales. Focusing on the Sun, spots, and facular regions are observed to occur in latitudinal bands in both the northern and southern hemispheres. The central latitudes of these ‘active bands’ are known to change throughout the solar activity cycle, beginning at higher latitudes at the start of each 11-yr cycle and moving towards the equator as the cycle progresses (Hale et al. 1919 ). To model this, we use typical solar cycle averaged latitudinal distributions. These distributions are based on Borgniet et al. ( 2015 ), in which average spot and facular latitude distributions are presented for solar cycle 23 (1996 May–2007 October), derived from USAF/NOAA sunspot group data and MDI/SOHO magnetograms (Scherrer et al. 1995 ), respectively. Transit mapping observations of the K4V star HAT-P-11 show a very similar spot distribution to the Sun (Morris et al. 2017 ). This result indicates that the solar cycle averaged distributions in our simulations can also apply to some K-type stars. We fitted the solar spot and facular region latitude data with equatorially symmetric Gaussian distributions (for spots, 〈φ〉 = ±16°, σ φ = 8°; for faculae, 〈φ〉 = ±16°, σ φ = 12°) shown in Fig. 4 (top panel). Feature longitudes are randomized. As the number of