Any statistical model approach requires a dataset that can be used to train a model. As mentioned above, kp is ideal since the IUPAC has benchmarked rate coefficients for a series of monomers. 4 kp data for these monomers can be assumed to be fairly accurate. In fact, recently an online database was established that allows to retrieve these coefficients directly. In order to benchmark a monomer, IUPAC typically requires more than one laboratory to provide data. In addition, several laboratories have provided sole PLP-SEC data that can still be regarded as fairly reliable. We collated data for close to 40 monomers that we deemed reliable (it should be noted that the IUPAC also defined reliability criteria that make such selection possible). We omitted acidic monomers, since it is known that they are governed largely by pH, and hence are outliers in the complete set of available data. Most data is available for the monomer families of acrylates and methacrylates. It is known that these monomers can be correlated within their respective families, allowing for some inference from one family to the other. All other monomers have no known quantitative correlation, even though it is common knowledge that radical stability plays a major role in predicting their reactivity. A full list of monomers and their respective values in Arrhenius form are given in the supporting information. For the sake of this work in this study, four distinct groups of monomers have been identified, these being as described above (i) acrylates, (ii) methacrylates (iii) monomers exhibiting strong H-bonding effects and (iv) 'others', such as the important monomer styrene.