Information source evaluation matrix

An information source evaluation matrix, produced by the Library at De Montfort Universit

The maturity related physical phenotypes of English, elite youth soccer players : exploring the elite player performance plan

The aims of this thesis were to examine the relationships between relative age, maturity status, and physical phenotypes on the selection, playing position allocation, and development tempo of a broad sample of elite youth soccer players’ that best represents UK development programs governed by the Elite Player Performance Plan (EPPP).The first research study (Chapter 4) aimed to establish the short-term reliability (STR) and smallest worthwhile changes (SWC) for a battery of field tests commonly used to assess elite youth soccer players’ physical and somatic phenotypes. On two occasions, the within-practitioner STR of three anthropometric measures (stature, seated height and body-mass) were assessed to estimate age at peak height velocity (APHV). In addition, within-player STR of the Multi-Stage Fitness Test (MSFT), 10 and 20 m sprints were assessed using 45 elite youth soccer players (age: 13.5 ± 1.5 years; body-mass: 49.2 ± 10.3 kg; stature: 177.7 ± 6.4 cm). In addition, within-player STR was established for T-Test and counter-movement jump (CMJ) performance using 21 senior amateur soccer players (age: 24 ± 5.3 years; body-mass: 84.3 ± 7.1 kg; stature: 177.7 ± 6.4 cm). The within-practitioner STR (coefficient of variance [CV], (95% confidence interval [CI])) and SWC were established for anthropometric measures (stature: CV = 0.4 % [CI = 0.3 to 0.5 %], SWC = 2.3 cm; seated height: CV = 1.1 % [0.9 to 1.4 %], SWC = 1.1 cm; body-mass: CV = 0.7 % [0.6 to 0.9 %], SWC = 2.3 kg) and APHV (CV = 0.8 % [0.7 to 1.0 %], SWC 0.1 year) respectively. Within-player physical fitness reliability and SWC were also established for CMJ (CV = 5.9 % [4.6 to 9.0 %], SWC = 0.6 cm), T-Test (CV = 1.7 % [1.3 to 2.4 %], SWC = 0.08 s), 10 m sprint (CV = 2.7 % [2.2 to 3.4 %], SWC = 0.03 s) and 20 m sprint (CV = 4.9 % [4.1 to 6.4 %], SWC = 0.06 s) performances. This battery of anthropometric and physical fitness field tests observed a high level STR and produced SWC values that will permit talent development (TD) practitioners to implement SWC % to assess changes in player growth, maturity and physical fitness.Research study 2 (Chapter 5) aimed to quantify the relative-age effect (RAE) and examine differences in physical phenotypes owing to the RAE of 731 (U11 to 18) elite youth soccer players sampled from 17 UK soccer development centres. Chi-squared analysis identified a clear un-even birth distribution across all age groups, demonstrating an over-representation of players born in the first quartile (Q1) (U11 to 12: 39%; U13 to 14: 46%; U15 to 16: 57%; U17 to 18: 42%) in comparison to Q4 (U11 to 12: 13%; U13 to 14: 8%; U15 to 16: 8%; U17 to 18: 14%) of the selection year that significantly differed to the distribution expected from National census data (all ≤ 0.001). Small to moderate differences in player stature and body-mass were identified for U11 to 14 players, whereby players born in Q1 were both heavier (ES = 0.48 to 0.57) and taller (ES = 0.62 to 1.06) than players born in Q4. U11 to U12 and U17 to 18 players born in Q1 were generally (ES = 0.37 to 0.70) more mature than their relatively younger (Q4) counterparts. There were no significant differences in agility (P = 0.108 to 0.643), 10 m (P = 0.122 to 0.886) and 20 m (0.090 to 0.911) sprint times between Q1 and Q4 players. However, relatively younger (Q4) U15 to U16 players showed small to moderate (ES = 0.34 to 0.49) inferiority in MSFT performance that continued for Q2 (Q2 vs. Q4: P = 0.041, ES = 0.91). The obvious birth distribution bias identified within this chapter favours the selection of players who are born earlier in the selection year, who possess enhanced maturity related anthropometric and aerobic performance characteristics.Study 3 (Chapter 6) assessed the contribution of relative age, maturity and physical phenotypes upon soccer playing position allocation (goalkeeper [GK], central-defender [CD], lateral-defender [LD], central-midfield [CM], lateral-midfielder [LM], and forward [FWD]) in 465 elite-youth soccer players (U13 to U18`s). U13 to 14 CD were identified as being relatively older than LD (ES = 0.72). CD and GK were generally taller (U13 to 14: ES = 0.49 to 1.19; U15 to 16: ES = 0.72 to 1.48; U17 to 18: ES = 0.96 to 1.58) and heavier (U13 to 14: ES = 0.64 to 1.40; U15 to 16: ES = 0.24 to 1.57; U17 to 18: ES = 0.51 to 1.32) than other players at each developmental stage and were advanced maturers at U13 to 14 (ES = 0.63 to 1.22). Position specific fitness characteristics were distinguished at U17 to 18, where LD and LM were faster than their central counterparts (10m: ES = 0.72 to 0.83; 20m: ES = 0.94 to 1.07). In summary, relative age, maturity and anthropometric characteristics appear to bias the allocation of players into key defensive roles from an early development stage, whereas position-specific physical attributes do not become apparent until the latter stages (U17 to 18) of talent development in outfield players.Study 4 (Chapter 7) assessed the development tempo of anthropometric and physical fitness characteristics according to players decimal age and maturity offset (YPHV) of 969 (U9 to U18) UK elite youth soccer players using battery of 7 field tests. Segmented regression analysis established that estimated stature increases were highest between 10.7 (CI = 10.2 to 11.2) to 15.2 (CI = 14.8 to 11.2) years, and between -3.2 (-3.5 to -2.9) to 0.8 (0.5 to 1.1) YPHV, with estimated annual growth rates of 7.5 (CI = 7.0 to 7.9) and 8.6 (CI = 8.3 to 9.0) cm·year-1 identified for decimal age and YPHV, respectively. Estimated rate of body-mass developmet was also increased (7.1 [CI = 6.6 to 7.6] kg·year-1) between 11.9 (CI = 11.5 to 12.3) to 16.1 (CI = 15.5 to 16.7) years of age, whereas when modelled against somatic maturity, body-mass increases continued at 7.5 (CI = 7.2 to 7.7) kg·year-1 from -1.6 (CI = -2.1 to -1.1) to ~4.0 YPHV, without plataeu. Estimated CMJ development tempo decreased from 2.5 (CI = 2.2 to 2.8) to 1.3 (CI = 0.7 to 1.9) cm·year-1 circa- PHV (0.6 [-0.4 to 1.6] YPHV). Estimated T-Test performance gains ceased from 15.8 (CI = 15.2 to 16.4) years of age onwards, but when modelled against somatic maturity status, improvements slowed by ~43% at 0.4 (CI = -0.1 to 0.9) YPHV. Players estimated endurance capacity increased by 169 (CI = 158 to 179) and 185 (CI = 173 to 198) m·year-1, until 16.4 (CI = 15.9 to 17.0) years and 2.1 (CI = 1.6 to 2.5) years post PHV, respectively. Estimated 10 and 20m sprint performance increased until 11.8 (CI = 11.2 to 12.5) years of age, or -1.8 (CI = -2.5 to -1.0) YPHV, before development tempo increased (31-43%) until 15.8 (CI = 15.3 to 16.3) years, or 1.2 (CI = 0.1 to 2.3) to 1.3 (CI = 0.8 to 1.8)YPHV. Findings identified that model strength for stature and body-mass was slightly higher in YPHV (r2 = 0.89) versus decimal age (r2 = 0.81). However these trends were not apparent for the development of physical fitness attributes. In addition, Chapter 7 revealed that players estimated sprint performance development markedly increased (31 to 43%) between 11.8 years and 15.8 years, or 1.2 to 1.3 YPHV. This data will provide practitioners with a guide to help forecast players’ rate of anthropometric and physical fitness characteristics development at an early stage of their development. Findings here’s suggest that TD practitioners should systematically use estimates of maturity offset to reduce the premature deselection of equally talented but slower players who may reach the same sprint capacity in adulthood, but are slightly later maturers versus there team-mates.In summary, the standardised battery of field-tests used within this thesis observed high levels of STR. There was a clear birth distribution bias that favours the selection of players’ for UK elite soccer development centres, who are born earlier in the selection year. It is likely that transient anthropometric advantages afforded to relatively older players within younger age categories act as a major contributory factor that bias the premature selection and role allocation of these players in to key defensive (GK and CD) roles, before the development of position-specific physical attributes become apparent during the latter stages (U17 to 18) of the EPPP in outfield players. Likely to be of particular importance to TD practitioners, players’ estimated sprint performance development increased across decimal ages (11.8 to 15.8 years) spanning PHV (-1.8 to 1.3 YPHV), justifying research to further examine the intricacies between training prescription and maturity on sprint speed development.Monitoring player maturity will enable a better understanding of maturity related anthropometric and performance gains, and is likely to improve sensitivity of training prescription and physical phenotype development forecasting. Emphasising the necessity for systematic and consistent monitoring of player growth and maturity that will likely inform talent identification and development processes, and reduce the biases associated with relative age and anthropometric advantages upon talent selection and positional role allocation

Design and performance of a 39cm balloon-borne telescope

A system for stabilizing a balloon-borne telescope using a star sensor device is described. Guide stars from minus four to plus four magnitude can be used and the sensor may be offset with respect to the telescope by as much as plus or minus five degrees in elevation and cross elevation to enable parts of the sky containing no suitable guide stars to be viewed. Acquisition of the guide star and setting of the offset coordinates is carried out by ground command and both may be changed in flight. The main design parameters of the equipment are summarized. Block diagrams and circuit diagrams of the star tracker are provided

Measurement properties of external training load variables during standardised games in soccer: Implications for training and monitoring strategies

The aim of this study was to assess the measurement properties of external training load measures across three formats of standardised training games. Eighty-eight players from two English professional soccer clubs participated in the study spanning three consecutive seasons. External training load data was collected from three types of standardised game format drills (11v11, 10v10, 7v7+6) using Global Positioning Systems. For each external training load metric in each game format, the following measurement properties were calculated; coefficient of variation (CV%) to determine between- and within-subject reliability, intraclass coefficient correlation (ICC) to determine test-retest reliability, and signal-to-noise ratio (SNR) to determine sensitivity. Total distance (TD) and PlayerLoad™ (PL) demonstrated good sensitivity (TD SNR = 1.6-4.6; PL SNR = 1.2-4.3) on a group level. However, a wide variety of within-subject reliability was demonstrated for these variables (TD CV% = 1.7-36.3%; PL CV% = 4.3-39.5%) and corresponding intensity measures calculated per minute. The percentage contribution of individual planes to PL showed the lowest between-subject CV% (CV% = 2-7%), although sensitivity varied across formats (SNR = 0.3-1.4). High speed running demonstrated poor reliability across all three formats of SSG (CV% = 51-103%, ICC = 0.03-0.53). Given the measurement properties of external training load measures observed in this study, specifically the within-subject variation, reliability across trials of standardised training games should be calculated on an individual level. This will allow practitioners to detect worthwhile changes across trials of standardised game format drills. Such information is important for the appropriate implementation of training and monitoring strategies in soccer

Cryogenic mechanisms for scanning and interchange of the Fabry-Perot interferometers in the ISO long wavelength spectrometer

The Infrared Space Observatory (ISO) is an ESA cornerstone mission for infrared astronomy. Schedules for launch in 1993, its four scientific instruments will provide unprecedented sensitivity and spectral resolution at wavelengths which are inaccessible using ground-based techniques. One of these, the Long Wavelength Spectrometer (LWS), will operate in the 45 to 180 micron region (Emery et. al., 1985) and features two Fabry-Perot interferometers mounted on an interchange mechanism. The entire payload module of the spacecraft, comprising the 60 cm telescope and the four focal plane instruments, is maintained at 2 to 4 K by an onboard supply of liquid helium. The mechanical design and testing of the cryogenic interferometer and interchange mechanisms are described

Individualisation of time-motion analysis : a method comparison and case report series

© Georg Thieme Verlag KG. This study compared the intensity distribution of time-motion analysis data, when speed zones were categorized by different methods. 12 U18 players undertook a routine battery of laboratory- and field-based assessments to determine their running speed corresponding to the respiratory compensation threshold (RCT), maximal aerobic speed (MAS), maximal oxygen consumption (vVO 2max ) and maximal sprint speed (MSS). Players match-demands were tracked using 5 Hz GPS units in 22 fixtures (50 eligible match observations). The percentage of total distance covered running at high-speed (%HSR), very-high speed (%VHSR) and sprinting were determined using the following speed thresholds: 1) arbitrary; 2) individualised (IND) using RCT, vVO 2max and MSS; 3) individualised via MAS per se; 4) individualised via MSS per se; and 5) individualised using MAS and MSS as measures of locomotor capacities (LOCO). Using MSS in isolation resulted in 61 % and 39 % of player's % HSR and % VHSR, respectively, being incorrectly interpreted, when compared to the IND technique. Estimating the RCT from fractional values of MAS resulted in erroneous interpretations of % HSR in 50 % of cases. The present results suggest that practitioners and researchers should avoid using singular fitness characteristics to individualise the intensity distribution of time-motion analysis data. A combination of players' anaerobic threshold, MAS, and MSS characteristics are recommended to individualise player-tracking data