<?xml version="1.0" encoding="UTF-8"?><ns2:project xmlns:ns1="http://gtr.rcuk.ac.uk/gtr/api" xmlns:ns2="http://gtr.rcuk.ac.uk/gtr/api/project" xmlns:ns3="http://gtr.rcuk.ac.uk/gtr/api/fund" xmlns:ns4="http://gtr.rcuk.ac.uk/gtr/api/person" xmlns:ns5="http://gtr.rcuk.ac.uk/gtr/api/project/outcome" xmlns:ns6="http://gtr.rcuk.ac.uk/gtr/api/organisation" ns1:created="2026-07-08T08:44:08Z" ns1:href="http://gtr.ukri.org/gtr/api/projects/F33A22B6-6C5A-4DA5-9EAC-8E0E7D200623" ns1:id="F33A22B6-6C5A-4DA5-9EAC-8E0E7D200623"><ns1:links><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/persons/A8EADF08-F4F2-4EA2-A332-4CA5A6C98271" ns1:rel="PM_PER"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/FA118648-8F39-4CA1-854C-A98CC059A24D" ns1:rel="LEAD_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/31404CB1-0F2C-4858-9486-66DA210F1EDB" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/FA118648-8F39-4CA1-854C-A98CC059A24D" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:end="2024-09-28T23:00:00Z" ns1:href="http://gtr.ukri.org/gtr/api/funds/27AAF356-8F4F-40F6-9A39-CFC7E9029F1B" ns1:rel="FUND" ns1:start="2022-09-28T23:00:00Z"/></ns1:links><ns2:identifiers><ns2:identifier ns2:type="RCUK">10021526</ns2:identifier></ns2:identifiers><ns2:title>University of Suffolk and Statsport Group Limited KTP 21_22 R3</ns2:title><ns2:status>Closed</ns2:status><ns2:grantCategory>Knowledge Transfer Partnership</ns2:grantCategory><ns2:leadFunder>Innovate UK</ns2:leadFunder><ns2:abstractText>To explore the application of inertial sensors for quantifying athletic performance. This will include the development of novel analysis techniques to guide the prescription of training load and the development of a bespoke software solution, using STATSports' industry leading athlete monitoring hardware.</ns2:abstractText></ns2:project>