Purpose:To quantify the activity profiles of elite wheelchair rugby (WCR) players and establish classification-specific arbitrary speed zones. In addition, indicators of fatigue during full matches were explored.Methods:Seventy-five elite WCR players from 11 national teams were monitored using a radio-frequency-based, indoor tracking system across 2 international tournaments. Players who participated in complete quarters (n = 75) and full matches (n = 25) were included and grouped by their International Wheelchair Rugby Federation functional classification: groups I (0.5), II (1.0–1.5), III (2.0–2.5), and IV (3.0–3.5).Results:During a typical quarter, significant increases in total distance (m), relative distance (m/min), and mean speed (m/s) were associated with an increase in classification group (P < .001), with the exception of groups III and IV. However, group IV players achieved significantly higher peak speeds (3.82 ± 0.31 m/s) than groups I (2.99 ± 0.28 m/s), II (3.44 ± 0.26 m/s), and III (3.67 ± 0.32 m/s). Groups I and II differed significantly in match intensity during very-low/low-speed zones and the number of high-intensity activities in comparison with groups III and IV (P < .001). Full-match analysis revealed that activity profiles did not differ significantly between quarters.Conclusions:Notable differences in the volume of activity were displayed across the functional classification groups. However, the specific on-court requirements of defensive (I and II) and offensive (III and IV) match roles appeared to influence the intensity of match activities, and consequently training prescription should be structured accordingly.

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• This is the version of the paper as accepted for publica- The aim of the current study was to establish which indicators of mobility are associated with 2 successful wheelchair rugby performance and determine whether these indicators differed 3 across classification. Data were collected from 11 international teams during 30 matches (353 4 match observations) using a radio-frequency based, indoor tracking system across two 5 tournaments. Players (n = 111) were first grouped by team rank as determined by their 6International Wheelchair Rugby Federation (IWRF) world ranking (LOW, MID, HIGH) and 7 then into one of four groups based on their IWRF classification: group I (0.5), II (1.0-1.5), III 8 (2.0-2.5), IV (3.0-3.5). The volume of activity (relative distance and mean speed), peak speed, 9and time spent within classification-specific arbitrary speed zones were calculated for each 10 individual. Although no differences were identified in the volume of activity, playing time 11 was significantly reduced in LOW (34:51 ± 8:35) compared to MID (48:54 ± 0:51) and 12 HIGH (45:38 ± 9:53), which was further supported by the greater number of substitutions 13 performed by LOW. HIGH achieved greater peak speeds (3.55 ± 0.40 m·sˉ¹) than LOW (3.27 14 ± 0.42 m·sˉ¹) and MID (3.45 ± 0.41 m·sˉ¹). Peak speed was further shown to be 15 classification-dependent (P ≤ 0.005), whereby HIGH groups III and IV players achieved 16 greater peak speeds than LOW and MID. The time spent performing high-intensity activities 17 was also greater in HIGH compared to LOW and MID, whilst further influenced by 18 classification (P ≤ 0.0005). To conclude, peak speed and the ability to perform a greater 19 number of high-intensity activities were associated with successful performance in 20 wheelchair rugby. 21

Experienced athletes seemed to display a good understanding of how modifying wheelchair configurations can affect sports performance, yet the methods offered for identifying optimal settings were extremely subjective. Therefore, future quantitative research into specific areas of configuration is imperative to identify these optimums and to inform athletes about the decisions they make when configuring a new sports wheelchair.

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