Usually crop models are run as point-based at field level. However, various soil properties may cause crop growth and yield to vary significantly at a smaller spatial scale than the field. Thus, the objective of this study was to determine whether within-field variation in yield can be simulated when appropriate input data are available. A study was performed on a 64-ha maize field located in Vojvodina region (northern Serbia). The soil was characterized as Chernozem. The field was managed by the farmer at a sub-field level in 2017. Apparent electrical conductivity zones were used for targeted soil sampling and final yield was recorded by yield monitors installed on the two harvesters used to harvest the field. According to the results, field slope, water flow direction and accumulation were important yield driving factors. Spatially variable soil properties were introduced into the WOFOST crop model by estimating available water within the field, based on calculated water flow accumulation. Points were selected within management zones. Yield predicted by the model was correlated with the yield measured by the yield monitors.