On all levels of rowing, a general rule is that you have to row together. Rowing together has no clear-cut definition. However, it is known that each rower has his or her own style, which can be registered in movement patterns and force curves. The big question is how to combine these individual styles such that the crew works together in the best way. The Dutch Rowing Federation showed interest in this topic, wanting to know how to adjust the rigging dimensions of the boat to allow the best racing performance. The goal of this thesis is to provide advice on what features of the rowing stroke should be synchronized and whether and how this could be promoted by individualized rigging.

The theoretical foundation for this study was a literature study about the current knowledge on the rowing stroke and differences within and between individuals and crews. Current used measures on performance and synchronization of rowers were described, and finally a proposal was done for which methods to use in the ongoing of the study.

Data was obtained from five female athletes of elite level, doing trials in a quadruple sculls of approximately 30 seconds at 30 SPM and 32 SPM in four different combinations. The strokes were identified and analyzed, based on performance and synchronization measures. Performance measured as Average Speed, Work per Stroke, Blade Losses, Velocity Fluctuation Losses and their respective and combined efficiencies. Synchronization measures were defined as Mean Standard Deviation of the Phase, Standard Deviation of the Time to Half Impulse and Standard Deviation of the Time to Half Work.

The chosen synchronization measures were not completely independent. Standard deviations of time to half impulse and half work were found to be highly similar (r = 0.970). An opposite effect was found between kinematic synchronization and the other two, Mean Standard deviation of the Phase was not in line with the empirical rule that better synchronization leads to better performance. The kinetic and energetic measures did show this effect: Lower standard deviations of time to half impulse and time to half work meant higher average speed (r = −0.193) and higher Work per Stroke (r = −0.574).

The best performing synchronization measure was time to half impulse synchrony. A drawback on this measure was that the sampling period was long, compared to the interpolated time differences. Athletes were found to achieve their half impulse moments in a consistent order.

To find out whether it is possible to promote synchronization and thus performance by individualizing rigging, the oar angles at the time to half impulse were analyzed. This new measure correlated moderately (r = 0.624), meaning it quantifies more or less the same effect. The kinetic similarity actually worked better (r = −0.292 with Average Speed and r = −0.748 with Work per Stroke) than the synchronization measure.

Similarity of half impulse angles enables the coach to adjust the rigging such that the timing should improve too. However, this should be tested in a follow-up study.