Applied Sports Science newsletter – August 19, 2016

As statisticians with experience teaching at the high school and college level, we recognize a familiar problem: A test that overshadows the ultimate outcomes it is intended to measure turns into an invalid test.

Back in the old Soviet Union, factories would produce masses of unusable products as a result of competition to meet unrealistic production quotas. Analogously, many charter schools, under pressure to deliver unrealistic gains in test scores, are contorting themselves to get the numbers they’ve promised. They’re being rewarded for doing so. But that monomaniacal focus on test scores undermines the correlation between test scores and academic accomplishment that originally existed.

This study aimed to translate movement patterns, technical skills and tactical actions associated with high-intensity efforts into metrics that could potentially be used to construct position-specific conditioning drills. A total of 20 individual English Premier League players’ high-intensity running profiles were observed multiple times (n = 100) using a computerised tracking system. Data were analysed using a novel high-intensity movement programme across five positions (centre back [CB], full-back [FB], central midfielder [CM], wide midfielder [WM] and centre forward [CF]). High-intensity efforts in contact with the ball and the average speed of efforts were greater in WMs than CBs, CMs and CFs (effect sizes [ES]: 0.9–2.1, P < 0.05). WMs produced more repeated efforts than CBs and CMs (ES: 0.6–1.3, P < 0.05). In possession, WMs executed more tricks post effort than CBs and CMs (ES: 1.2–1.3, P < 0.01). FBs and WMs performed more crosses post effort than other positions (ES: 1.1–2.0, P < 0.01). Out of possession, CFs completed more efforts closing down the opposition (ES: 1.4–5.0, P < 0.01) but less tracking opposition runners than other positions (ES: 1.5–1.8, P < 0.01). CFs performed more arc runs before efforts compared to CBs, FBs and WMs (ES: 0.9–1.4, P < 0.05), however, CBs completed more 0–90° turns compared to FBs, CMs and WMs (ES: 0.9–1.1, P < 0.01). The data demonstrate unique high-intensity trends in and out of possession that could assist practitioners when devising position-specific drills.

Athletes participating in elite sports are exposed to high training loads and increasingly saturated competition calendars. Emerging evidence indicates that poor load management is a major risk factor for injury. The International Olympic Committee convened an expert group to review the scientific evidence for the relationship of load (defined broadly to include rapid changes in training and competition load, competition calendar congestion, psychological load and travel) and health outcomes in sport. We summarise the results linking load to risk of injury in athletes, and provide athletes, coaches and support staff with practical guidelines to manage load in sport. This consensus statement includes guidelines for (1) prescription of training and competition load, as well as for (2) monitoring of training, competition and psychological load, athlete well-being and injury. In the process, we identified research priorities. [full text]

To say that Team GB have dominated the Olympic cycling would be the biggest understatement of the games. British track cyclists seem to have made peaking in line with the Olympic cycle their speciality. They won seven of the ten gold medals on offer at both London 2012 and Beijing 2008, but this year in Rio, they have really surpassed themselves. Every member of the 15-strong squad has come away with a medal, taking the final tally to six golds, four silvers and one bronze.

This remarkable success has baffled their rivals. Michael Gané – the French sprint coach – must have echoed the thoughts of many teams when he remarked; “they don’t exist for four years, then at the Olympics they outclass the whole world”. So, how have Team GB managed, yet again, to peak at the optimum time?

There are still many disagreements about how to improve the education system so that children graduate with the skills and dispositions they will need to succeed in life. Education reform discussions often center on how to tweak existing mechanisms, but what if the system itself is creating the problems educators and policymakers are trying to solve? That’s the theory favored by author and TED-talk sensation Sir Ken Robinson.

“If you design a system to do something, don’t be surprised if it does it,” Robinson said at the annual Big Picture Learning conference called Big Bang. He went on to describe the two pillars of the current system — conformity and compliance — which undermine the sincere efforts of educators and parents to equip children with the confidence to enter the world on their own terms.

When Pete Carroll was first a head coach in the NFL, he had to use the eye test to determine the energy level of his group at training camp.

Now he has data.

“The level of energy on the practice field, which we measure, we actually measure it, is way up,” Carroll said during an appearance on 710 ESPN Seattle’s Brock and Salk show. “We track it through the GPS systems that we have — how much energy they’re expending and the speed that they practice at.”

Carroll added that the energy has been the “best ever” since he started in Seattle.

… we caught up with the man in charge of recovery for Team USA: Ralph Reiff, executive director of St. Vincent Sport Performance and the head of the Athlete Recovery Center in Rio de Janeiro. Since he’s the go-to guy for taking care of recovery for the best athletes in the country, we knew he’d have some tips for acing our workout recovery as well.

“I’m a big believer in creating and following a plan,” says Reiff. “In this plan, you’re thinking about moving fluids and waste products out of the muscles—that’s what creates soreness and stiffness, and sort of bogs the muscles down the following days.”

Here are his athlete-tested tips that even mere mortals can use to flush out their muscles and amp up the recovery process after a tough workout (no fancy equipment required).

Technical debt is “a concept in programming that reflects the extra development work that arises when code that is easy to implement in the short run is used instead of applying the best overall solution.”

Although most often spoken of as a problem in software engineering for industry, academia has a severe technical debt problem. The problem is that even in the rare case that you can obtain the code and data used to generate the analysis contained in a paper, often the code is broken (I am presuming that it was at some past point not broken).

This in turn requires debugging of a foreign codebase which may or may not (probably the latter) have been written in a manner intended to be understandable to people other than the original author. Often this means that the code isn’t ever fixed.

Wearables are becoming commonplace in practice games and training, but have received a lukewarm response from athletes, unhappy with the lack of advice or instructions.

Athletes see the advantages of using wearables, according to a report from Lux Research, but want to see wearable providers take more of an active role on the advice side.

That would include analysis on training performance, how to avoid injuries, and how to be healthier. Fitbit, the largest wearable vendor, currently provides limited analytics, outside of a weekly rundown of your efforts alongside heart-rate level and calories burnt during a workout.

“Most wearables today do a great job of reporting factual information but fail to educate consumers on how to modify their behavior to achieve their health and performance goals,” said Noa Ghersin, a Lux Research associate that penned the report.

Background: Arthroscopically assisted anterior cruciate ligament (ACL) reconstruction is a common orthopaedic procedure. Graft failure after reconstruction remains a devastating complication, often requiring revision surgery and less aggressive or modified rehabilitation. Worse functional and patient-reported outcomes are reported compared with primary reconstruction. Moreover, both rates and risk factors for revision are variable and inconsistent within the literature.

Purpose: To determine the rate of revision surgery after ACL reconstruction in a large cohort of patients, to assess the influence of patient characteristics on the odds of revision, and to compare revision rates between active-duty military members and non–active-duty beneficiaries.

Study Design: Descriptive epidemiology study.

Methods: Using administrative data from the Military Health System, a retrospective study was designed to characterize the rate of ACL revision surgery among patients treated within a military facility. All patients ?18 years at the time of ACL reconstruction were identified using the American Medical Association Current Procedural Terminology (CPT) for ACL reconstruction (CPT code 29888) over 7 years (2005-2011). Revision ACL reconstructions were identified as having ?2 ACL reconstruction procedure codes on the ipsilateral knee at least 90 days apart. Univariate analysis was performed to calculate odds ratios (ORs) for demographic, perioperative medication use, and concomitant procedure–related risk factors. A multivariate logistic regression model determined risk covariates in the active-duty cohort.

Results: The study population consisted of 17,164 ACL reconstructions performed among 16,336 patients, of whom 83.3% were male with a mean ± SD age of 28.9 ± 7.6 years for the nonrevision group, and was predominantly active duty (89.2%). Patients undergoing ACL reconstruction on both knees only contributed their index knee for analyses. There were 587 patients who underwent revision surgery, corresponding to an overall revision rate of 3.6%. The median time from the index surgery to revision surgery was 500 days (interquartile range, 102-2406 days). Revision rates were higher in the active-duty cohort as compared with non–active-duty beneficiaries (3.8% vs 1.8%, respectively; OR, 2.14; 95% CI, 1.49-3.07). Based on multivariate logistic regression in the active-duty cohort, age ?35 years (OR, 0.44; 95% CI, 0.33-0.58) and concomitant meniscal repair (OR, 0.69; 95% CI, 0.53-0.91) were found to be protective with regard to the odds of revision surgery. Perioperative medication use of nonsteroidal anti-inflammatory drugs (NSAIDs) (OR, 1.33; 95% CI, 1.12-1.58; number needed to harm [NNH], 100) and COX-2 inhibitors (OR, 1.31; 95% CI, 1.04-1.66; NNH, 333) was associated with increased odds of revision surgery. No significant findings were detected among sex, race, nicotine use, body mass index, or other concomitant procedures of interest.

Conclusion: In this large cohort study, the rate of revision ACL reconstruction was 3.6%, which is consistent with the existing literature. Increased odds of revision surgery among active-duty personnel were associated with the perioperative use of NSAIDs and COX-2 inhibitors. Age ?35 years and concomitant meniscal repair were found to be protective against ACL revision.

Background: Few studies have reported the return-to-sport rate at 1-year follow-up after primary and revision anterior cruciate ligament (ACL) reconstruction.

Purpose: To compare the return-to-sport rate 1 year after primary and revision ACL reconstruction in the same cohort according to 2 modalities: any kind of sport and the patient’s usual sport at the same level as before the injury.

Study Design: Cohort study; Level of evidence, 3.

Methods: A single-center, prospective cohort study of patients undergoing ACL reconstruction (French prospective Acl STudy [FAST]) was begun in 2012. A comparative study was performed based on a retrospective analysis of data collected prospectively. Included were all athletes aged 18 to 50 years who underwent primary or revision isolated ACL reconstruction between 2012 and 2014. Two groups were formed: primary reconstruction and revision reconstruction. The main criterion was return to sport at 1-year follow-up (yes/no); secondary criteria were return to the usual sport at 1-year follow-up, knee function (International Knee Documentation Committee [IKDC] and Knee injury and Osteoarthritis Outcome Score [KOOS] scores), and psychological readiness (ACL–Return to Sports after Injury [ACL-RSI] score) at 6 months and 1 year.

Results: A total of 552 patients (primary reconstruction group: n = 497, revision reconstruction group: n = 55) were included in the study. There were 373 men and 179 women (mean [±SD] age, 30.2 ± 8.4 years). No significant difference in the return-to-sport rate was found between the 2 groups at 1-year follow-up (primary reconstruction group: 90.9%, revision reconstruction group: 87.3%; P = .38), but patients in the primary reconstruction group resumed their usual sport significantly more often (primary reconstruction group: 63.6%, revision reconstruction group: 49.1%; P = .04). Eight (1.4%) retears occurred during a new sport-related injury within a mean 8.9 ± 2.9 months: 7 (1.4%) in the primary reconstruction group and 1 (1.8%) in the revision reconstruction group (P = .8). At 1-year follow-up, functional scores were significantly better in the primary reconstruction group for subjective IKDC (82.6 ± 13.3 vs 78.4 ± 16.6; P = .04); KOOS Symptoms/Stiffness (73.3 ± 15.2 vs 67.7 ± 19.6; P = .02), Activities of Daily Living (96.3 ± 6.4 vs 94.3 ± 9.1; P = .04), Sport (79.7 ± 19.1 vs 69.1 ± 24.8; P = .0004), and Quality of Life (69.6 ± 22.7 vs 54.7 ± 24.8; P < .00001) subscales; and ACL-RSI (65 ± 23 vs 49.5 ± 24.8; P < .00001). On multivariate analysis, patients who were more likely to resume their usual sport at 1 year were high-level players (odds ratio [OR], 2.2) who underwent primary reconstruction (OR, 2.0) and had better KOOS Quality of Life (OR, 1.7) and subjective IKDC (OR, 2.1) scores at 6-month follow-up without complications or retears during the first postoperative year (OR, 2.6).

Conclusion: At 1-year follow-up, there was no significant difference in the return-to-sport rate between primary and revision ACL reconstruction. Patients who underwent primary reconstruction returned to their usual sport significantly more often.

There are three types of teams: the ones that have an expensive quarterback, the ones that have a cheap rookie quarterback, and the ones who don’t have either

Executive Summary

Statistical models of the football transfer market show a very high level of systematic variation in transfer fees.

Transfer-fee inflation tends to be closely associated with revenue growth, particularly the growth of TV media revenues.

Transfer valuations of individual players depend on five main value-drivers: player quality, selling club, buying club, current contract expiry date, and market conditions.

Player quality can be captured using five quality indicators: age, career experience, current appearance rates, current and career scoring rates, and international caps

[Page 3] … the team continued to gather information on players, a process that helped thrust Lodeiro to the top of the list.

“Early in the process, (Data Analyst) Ravi (Ramineni) ran a whole series of regressions and analytics,” Lagerwey explained. Given the data Seattle had scraped from its various sources, how would each target improve the team? Goals, expected goals. Passes, assists, chances created. Ramineni processed the data, analyzed it using the team’s assumptions, and gave Lagerwey something objective to complement his scouting.

“You can find some common denominators if you look hard enough,” according to Lagerwey. And the common denominators Ramineni found “all pointed to Lodeiro.”

The numbers only reinforced the eye test.

Neil McGuinness is one of football’s top talent scouts. Currently employed by a national team in the Middle East to recruit players for their World Cup bid, he has previously worked at Celtic and as an independent scout for numerous clubs.

We asked Neil to reveal how a player gets signed in the modern game. He outlines the process from the perspective of a scout, in this seven-step guide.