title: Rugby placekicking mechanics to inform coaching strategies and enhance performance

authors: Hébert-Losier, Kim

abstract: Introduction
The ability to score from placekicks is a trait discriminating winning and losing in elite Rugby Union1. Placekicks account for 45% of points in international Rugby Union, with match outcomes reliant on placekicking success2. Clearly, improving placekicking success can alter match outcomes and should be a key focus in rugby skills coaching. Currently, coaching placekicking techniques mainly relies upon practical experience or findings from other sports or non-elite Rugby Union players tested in laboratory environments. These studies provide limited real-world guidance for placekickers and coaches. Our aim was to determine biomechanical variables that discriminate good and bad placekicking attempts in an ecologically valid environment.

Methods
Three competitive male placekickers performed 10 kicks outdoors, 35-meters from the goalposts. Placekicker and ball 3D biomechanics were collected at 300-Hz using a Qualysis 3D motion capture system. Coach and player perceptions and placekick outcomes were recorded to define the three best and three worst kicks for each placekicker. Differences between the best and worst kicks were examined using standardised effect sizes (ES).

Results
Seven variables meaningfully and consistently differentiated the best from worst placekicks in all three players (‘core variables’, Figure 1). In the best kicks, resultant and forward speed of centre of mass were slower at ball contact, but maintained better through contact; the kicking leg reached greater knee flexion during swing and was more flexed at the hip and knee at ball contact; and the trunk was less rotated outwards relative to the kicking direction. Twenty-seven variables were consistently associated with better kicking performance in all players, with a large ES in at least one player (‘meaningful variables’, Figure 1). These variables indicated that the best kicks demonstrated less sideways ball spin, speed, and direction; greater change in vertical and sideways foot speed during ball contact; a more “C” than “J” shape footpath; larger shoulder-to-hip separation; and less ankle motion during swing.

text: Rugby placekicking mechanics to inform coaching strategies and enhance performance Introduction
The ability to score from placekicks is a trait discriminating winning and losing in elite Rugby Union1. Placekicks account for 45% of points in international Rugby Union, with match outcomes reliant on placekicking success2. Clearly, improving placekicking success can alter match outcomes and should be a key focus in rugby skills coaching. Currently, coaching placekicking techniques mainly relies upon practical experience or findings from other sports or non-elite Rugby Union players tested in laboratory environments. These studies provide limited real-world guidance for placekickers and coaches. Our aim was to determine biomechanical variables that discriminate good and bad placekicking attempts in an ecologically valid environment.

Methods
Three competitive male placekickers performed 10 kicks outdoors, 35-meters from the goalposts. Placekicker and ball 3D biomechanics were collected at 300-Hz using a Qualysis 3D motion capture system. Coach and player perceptions and placekick outcomes were recorded to define the three best and three worst kicks for each placekicker. Differences between the best and worst kicks were examined using standardised effect sizes (ES).

Results
Seven variables meaningfully and consistently differentiated the best from worst placekicks in all three players (‘core variables’, Figure 1). In the best kicks, resultant and forward speed of centre of mass were slower at ball contact, but maintained better through contact; the kicking leg reached greater knee flexion during swing and was more flexed at the hip and knee at ball contact; and the trunk was less rotated outwards relative to the kicking direction. Twenty-seven variables were consistently associated with better kicking performance in all players, with a large ES in at least one player (‘meaningful variables’, Figure 1). These variables indicated that the best kicks demonstrated less sideways ball spin, speed, and direction; greater change in vertical and sideways foot speed during ball contact; a more “C” than “J” shape footpath; larger shoulder-to-hip separation; and less ankle motion during swing.

year: 2018

title: How the dragons work: searching in a web

authors: Witten, Ian H.

subjects: computer science

abstract: Search engines -- "web dragons" -- are the portals through which we access society's treasure trove of information. They do not publish the algorithms they use to sort and filter information, yet how they work is one of the most important questions of our time. Google's PageRank is a way of measuring the prestige of each web page in terms of who links to it: it reflects the experience of a surfer condemned to click randomly around the web forever. The HITS technique distinguishes "hubs" that point to reputable sources from "authorities," the sources themselves. This helps differentiate communities on the web, which in turn can tease out alternative interpretations of ambiguous query terms. RankNet uses machine learning techniques to rank documents by predicting relevance judgments based on training data. This article explains in non-technical terms how the dragons work.

text: How the dragons work: searching in a web Search engines -- "web dragons" -- are the portals through which we access society's treasure trove of information. They do not publish the algorithms they use to sort and filter information, yet how they work is one of the most important questions of our time. Google's PageRank is a way of measuring the prestige of each web page in terms of who links to it: it reflects the experience of a surfer condemned to click randomly around the web forever. The HITS technique distinguishes "hubs" that point to reputable sources from "authorities," the sources themselves. This helps differentiate communities on the web, which in turn can tease out alternative interpretations of ambiguous query terms. RankNet uses machine learning techniques to rank documents by predicting relevance judgments based on training data. This article explains in non-technical terms how the dragons work.

year: 2006

title: Ethics in Maori research: Working paper

authors: Cram, Fiona

subjects: Maori

abstract: When we think about what we are doing as researchers, one of our main tasks is to acquire knowledge. For some researchers their task begins and ends there. Knowledge is viewed as cumulative, that by adding to some knowledge pool we will one day be able to put the component parts together and discover universal laws. Many researchers also assume that the knowledge they have collected is objective, value-free and apolitical. This is part of psychologists’ ‘physics envy’. A Maori view of knowledge is very different from this. For Maori the purpose of knowledge is to uphold the interests and the mana of the group; it serves the community. Researchers are not building up their own status; they are fighting for the betterment of their iwi and for Maori people in general.

text: Ethics in Maori research: Working paper When we think about what we are doing as researchers, one of our main tasks is to acquire knowledge. For some researchers their task begins and ends there. Knowledge is viewed as cumulative, that by adding to some knowledge pool we will one day be able to put the component parts together and discover universal laws. Many researchers also assume that the knowledge they have collected is objective, value-free and apolitical. This is part of psychologists’ ‘physics envy’. A Maori view of knowledge is very different from this. For Maori the purpose of knowledge is to uphold the interests and the mana of the group; it serves the community. Researchers are not building up their own status; they are fighting for the betterment of their iwi and for Maori people in general.

year: 1993