Modelling the progression of competitive performance of an academy's soccer teams

Progression of a team’s performance is a key issue in competitive sport, but there appears to have been no published research on team progression for periods longer than a season. In this study we report the game-score progression of three teams of a youth talent-development academy over five seasons using a novel analytic approach based on generalised mixed modelling. The teams consisted of players born in 1991, 1992 and 1993; they played totals of 115, 107 and 122 games in Asia and Europe between 2005 and 2010 against teams differing in age by up to 3 years. Game scores predicted by the mixed model were assumed to have an over-dispersed Poisson distribution. The fixed effects in the model estimated an annual linear pro-gression for Aspire and for the other teams (grouped as a single opponent) with adjustment for home-ground advantage and for a linear effect of age difference between competing teams. A random effect allowed for different mean scores for Aspire and opposition teams. All effects were estimated as factors via log-transformation and presented as percent differences in scores. Inferences were based on the span of 90% confidence intervals in relation to thresholds for small factor effects of x/÷1.10 (+10%/-9%). Most effects were clear only when data for the three teams were combined. Older teams showed a small 27% increase in goals scored per year of age difference (90% confidence interval 13 to 42%). Aspire experienced a small home-ground advantage of 16% (-5 to 41%), whereas opposition teams experienced 31% (7 to 60%) on their own ground. After adjustment for these effects, the Aspire teams scored on average 1.5 goals per match, with little change in the five years of their existence, whereas their opponents’ scores fell from 1.4 in their first year to 1.0 in their last. The difference in progression was trivial over one year (7%, -4 to 20%), small over two years (15%, -8 to 44%), but unclear over >2 years. In conclusion, the generalized mixed model has marginal utility for estimating progression of soccer scores, owing to the uncertainty arising from low game scores. The estimates are likely to be more precise and useful in sports with higher game scores

Characteristics and Outcomes of People With Gout Hospitalized Due to COVID-19: Data From the COVID-19 Global Rheumatology Alliance Physician-Reported Registry

Objective: To describe people with gout who were diagnosed with coronavirus disease 2019 (COVID-19) and hospitalized and to characterize their outcomes. Methods: Data on patients with gout hospitalized for COVID-19 between March 12, 2020, and October 25, 2021, were extracted from the COVID-19 Global Rheumatology Alliance registry. Descriptive statistics were used to describe the demographics, comorbidities, medication exposures, and COVID-19 outcomes including oxygenation or ventilation support and death. Results: One hundred sixty-three patients with gout who developed COVID-19 and were hospitalized were included. The mean age was 63 years, and 85% were male. The majority of the group lived in the Western Pacific Region (35%) and North America (18%). Nearly half (46%) had two or more comorbidities, with hypertension (56%), cardiovascular disease (28%), diabetes mellitus (26%), chronic kidney disease (25%), and obesity (23%) being the most common. Glucocorticoids and colchicine were used pre-COVID-19 in 11% and 12% of the cohort, respectively. Over two thirds (68%) of the cohort required supplemental oxygen or ventilatory support during hospitalization. COVID-19-related death was reported in 16% of the overall cohort, with 73% of deaths documented in people with two or more comorbidities. Conclusion: This cohort of people with gout and COVID-19 who were hospitalized had high frequencies of ventilatory support and death. This suggests that patients with gout who were hospitalized for COVID-19 may be at risk of poor outcomes, perhaps related to known risk factors for poor outcomes, such as age and presence of comorbidity

Using athletes' world rankings to assess countries' performance

There is a need for fair measures of country sport performance that include athletes who do not win medals.Purpose:To develop a measure of country performance based on athlete ranks in the sport of swimming.Methods:Annual top-150 ranks in Olympic pool-swimming events were downloaded for 1990 through 2011. For each athlete of a given rank, a score representing the athlete’s performance potential was estimated as the proportion of athletes of that rank who ever achieved top rank. A country’s scores were calculated by summing its athletes’ scores over all 32 events. Reliability and convergent validity were assessed via year-to-year correlations and correlations with medal counts at major competitions. The method was also applied to ranks at the 2012 Olympics to evaluate countries’ swimming performance.Results:The performance score of an athlete of a given rank was closely approximated by 1/rank. This simpler score has 1 practical interpretation: An athlete ranked 7th (for example) has a chance of 1/7 of ever achieving top rank; for purposes of evaluating country performance, 7 such athletes are equivalent to 1 athlete of the top rank. Country scores obtained by summing 1/rank of the country’s athletes had high reliability and validity. This approach produced scores for 168 countries at the Olympics, whereas only 17 countries won medals.Conclusions:The authors used the sport of swimming to develop a fair and inclusive measure representing a country’s performance potential. This measure should be suitable for assessing countries in any sports with world rankings or with athletes at major competitions.</jats:sec

The reliability and usefulness of an individualised submaximal shuttle run test in elite rugby league players

Purpose: The aim of the present study was to examine the reliability and usefulness of a proposed 4-min individualised submaximal shuttle run test (SSR) in elite rugby league players. Materials and methods: Twenty-two elite rugby league players competing in the National Rugby League competition (23.2\ua0±\ua03.4\ua0years, 186.8\ua0±\ua05.4\ua0cm, 100.2\ua0±\ua08.5\ua0kg) performed the SSR twice, seven days apart (test–retest design). The SSR was prescribed as 75% of the average speed during a 1500-m time trial. Exercise heart rate was calculated as the average heart rate (HR) over the final 30 s (HRex). Seated HR recovery (HRR) was recorded at 1- (HRR) and 2-min (HRR) post-exercise. Data were analysed with magnitude-based inferences. Results: Test–retest typical errors were moderate for HRex (1.2 percentage points; 90% confidence limits: 1.0–1.7), HRR (3.4; 2.7–4.6) and HRR (2.9; 2.3–3.9). Intraclass correlation coefficients were extremely high for HRex (0.91; 0.78–0.94) and very high for both HRR (0.80; 0.61–0.90) and HRR (0.84; 0.69–0.92). Thresholds for an individual change that would be likely small and greater than the typical error were ±1.8 (percentage points), ±4.6 and ±4.1 for HRex, HRR and HRR, respectively. Conclusions: The SSR demonstrates acceptable reliability in the assessment of HRex and HRR, thus demonstrating its potential usefulness for monitoring fitness and fatigue in elite rugby league players