In the city of Amsterdam, many structures, such as houses,bridges and quay walls, are founded on wooden piles. In order to gain insightinto the safety of such structures, assessment of the foundations is required.As part of an experimental framework assessing the safety of bridges and quaywalls in the city of Amsterdam, a number of piles are instrumented with fiberoptic sensors and load tested in compression. These tests aim to providedetailed information on the behavior of timber piles subjected to loading. Thisinformation can be used to determine the geotechnical bearing capacity of suchpiles. An in-depth analysis is conducted on 8 timber piles tested within thisframework.  The conducted analysis has resulted in a variation ofoutcomes. Without including the effects of residual loads, an average baseresistance of 130 kN is observed. Upon inclusion of residual loads the averagetrue base resistance increases to a value of 188 kN. The average shaftcapacities in the bearing sand layer for scenarios excluding and includingresidual effects are 48 and 60 kN respectively.  The correlation factor α_p is derived usingthree cone resistance averaging techniques. The Koppejan method hasconsistently resulted in the highest derived α_p factors withvalues of 1.09 and 1.61 for scenarios excluding and including residual loadsrespectively.  The scenario excluding residual effects has resulted in anaverage α_sof 0.009 for the bearing sand layer. Upon inclusion of residual loads, thederived α_sfactor for the first sand layer amounts to 0.012. This increase in shear forcesis also observed in the Pleistocene peat layer. Therefore, residual loadsredistribute the capacity of the piles by increasing the shaft resistance inthe bearing sand and Pleistocene peat, while simultaneously decreasing theshear stresses in the Holocene layers above.  Conclusively, timber pile characteristics such as variationin geometry and mechanical properties have significant effects on the capacityof the piles. Additionally, these variations result in fluctuations in thecalculated load distribution along the pile. Local smoothing of thesefluctuations results in higher apparent loads, most specifically at the pilebase. Therefore, smoothing algorithms are not implemented in this analysis. Thevariation in diameter along the entire length of each pile directly affects theload distribution. Despite this influence, no trend is observed for thevariation of α_p factors with respect to pile tip diameter. Anapparent relationship between the tapering of the pile in the bearing sandlayer and the derived α_s factors suggests that tapering effectivelyincreases the shear forces along the shaft in that layer.  Furthermore, the usage of fiber optic sensors on woodenpiles has proven to be effective. The variation in local behavior of wood isclearly illustrated through the conducted analysis. As a consequence of thebiological nature of wood, the local behavior of wooden piles is best capturedby sensing technologies measuring strains at high spatial frequencies.