Upgrade to Pro
— share decks privately, control downloads, hide ads and more …
Speaker Deck
Features
Speaker Deck
PRO
Sign in
Sign up for free
Search
Search
False Start Detection in Elite Athletics
Search
Sponsored
·
Your Podcast. Everywhere. Effortlessly.
Share. Educate. Inspire. Entertain. You do you. We'll handle the rest.
→
Kevin Brosnan
October 18, 2016
Research
0
140
False Start Detection in Elite Athletics
Short Informal Mathematics (SIM) Talk given within the department at the University of Limerick
Kevin Brosnan
October 18, 2016
Tweet
Share
More Decks by Kevin Brosnan
See All by Kevin Brosnan
Automated Gating for Flow Cytometry
significantstats
0
200
False Starts in Athletics: Are they truly fair?
significantstats
0
110
False Starts in Athletics: Are they truly fair?
significantstats
0
100
A Markov Random Fields Approach to the Gating of Flow Cytometry Data
significantstats
0
150
A Markov Random Fields Approach to the Gating of Flow Cytometry Data
significantstats
0
140
Challenges for tertiary level mathematics tutors
significantstats
0
93
Elite Athletics: Is the false start disqualification rule appropriate?
significantstats
0
130
Quantile Regression
significantstats
0
160
Forward Modelling of UK Gas Prices
significantstats
0
61
Other Decks in Research
See All in Research
The mathematics of transformers
gpeyre
0
120
大規模言語モデルにおけるData-Centric AIと合成データの活用 / Data-Centric AI and Synthetic Data in Large Language Models
tsurubee
1
520
第66回コンピュータビジョン勉強会@関東 Epona: Autoregressive Diffusion World Model for Autonomous Driving
kentosasaki
0
470
ドメイン知識がない領域での自然言語処理の始め方
hargon24
1
260
2026年3月1日(日)福島「除染土」の公共利用をかんがえる
atsukomasano2026
0
440
社内データ分析AIエージェントを できるだけ使いやすくする工夫
fufufukakaka
1
960
明日から使える!研究効率化ツール入門
matsui_528
7
1.8k
学習型データ構造:機械学習を内包する新しいデータ構造の設計と解析
matsui_528
6
3.8k
Upgrading Multi-Agent Pathfinding for the Real World
kei18
0
430
SkySense V2: A Unified Foundation Model for Multi-modal Remote Sensing
satai
3
620
LiDARセキュリティ最前線(2025年)
kentaroy47
0
250
離散凸解析に基づく予測付き離散最適化手法 (IBIS '25)
taihei_oki
1
720
Featured
See All Featured
Reflections from 52 weeks, 52 projects
jeffersonlam
356
21k
The B2B funnel & how to create a winning content strategy
katarinadahlin
PRO
1
300
Visualizing Your Data: Incorporating Mongo into Loggly Infrastructure
mongodb
49
9.9k
Designing Dashboards & Data Visualisations in Web Apps
destraynor
231
54k
How To Speak Unicorn (iThemes Webinar)
marktimemedia
1
410
30 Presentation Tips
portentint
PRO
1
250
RailsConf 2023
tenderlove
30
1.4k
So, you think you're a good person
axbom
PRO
2
2k
[RailsConf 2023 Opening Keynote] The Magic of Rails
eileencodes
31
10k
Fight the Zombie Pattern Library - RWD Summit 2016
marcelosomers
234
17k
We Are The Robots
honzajavorek
0
190
New Earth Scene 8
popppiees
1
1.7k
Transcript
Fa l s e - St a r t D
e t e c t i o n i n E l i t e At h l e t i c s K e v i n B r o s n a n , U n i v e r s i t y O f L i m e r i c k S I M T a l k , 1 8 t h O c t o b e r 2 0 1 6
O u t l i n e … • Background
• Rule Changes • Exploratory Analysis • Modelling • Results • Outputs
B a ck g r o u n d …
R u l e C h a n ge s
… 1998 2004 2010 2016 Individual Warning
R u l e C h a n ge s
… 1998 2004 2010 2016 Individual Warning
R u l e C h a n ge s
… 1998 2004 2010 2016 Individual Warning
R u l e C h a n ge s
… 1998 2004 2010 2016 Individual Warning
R u l e C h a n ge s
… 1998 2004 2010 2016 Individual Warning Group Warning
R u l e C h a n ge s
… 1998 2004 2010 2016 Individual Warning Group Warning
R u l e C h a n ge s
… 1998 2004 2010 2016 Individual Warning Group Warning
R u l e C h a n ge s
… 1998 2004 2010 2016 Individual Warning Automatic Disqualification Group Warning
R u l e C h a n ge s
… 1998 2004 2010 2016 Individual Warning Automatic Disqualification Group Warning
E x p l o r a t o r
y … 2,310 1,007 1,303
E x p l o r a t o r
y … 2,310 1,007 1,303
M o d e l l i n g …
f ( RT|µ, , ⌧ ) = 1 ⌧ exp nµ ⌧ + 2 2⌧2 RT ⌧ o ✓RT µ 2 ⌧ ◆
M o d e l l i n g …
f ( RT|µ, , ⌧ ) = 1 ⌧ exp nµ ⌧ + 2 2⌧2 RT ⌧ o ✓RT µ 2 ⌧ ◆ µ = 400, = 100, ⌧ = 0
M o d e l l i n g …
f ( RT|µ, , ⌧ ) = 1 ⌧ exp nµ ⌧ + 2 2⌧2 RT ⌧ o ✓RT µ 2 ⌧ ◆ µ = 400, = 100, ⌧ = 0 µ = 400, = 100, ⌧ = 0 µ = 0, = 0, ⌧ = 150
M o d e l l i n g …
f ( RT|µ, , ⌧ ) = 1 ⌧ exp nµ ⌧ + 2 2⌧2 RT ⌧ o ✓RT µ 2 ⌧ ◆ µ = 400, = 100, ⌧ = 0 µ = 400, = 100, ⌧ = 0 µ = 0, = 0, ⌧ = 150 µ = 400, = 100, ⌧ = 0 µ = 0, = 0, ⌧ = 150 µ = 400, = 100, ⌧ = 50
M o d e l l i n g …
f ( RT|µ, , ⌧ ) = 1 ⌧ exp nµ ⌧ + 2 2⌧2 RT ⌧ o ✓RT µ 2 ⌧ ◆ µ = 400, = 100, ⌧ = 0 µ = 400, = 100, ⌧ = 0 µ = 0, = 0, ⌧ = 150 µ = 400, = 100, ⌧ = 0 µ = 0, = 0, ⌧ = 150 µ = 400, = 100, ⌧ = 50 µ = 400, = 100, ⌧ = 0 µ = 0, = 0, ⌧ = 150 µ = 400, = 100, ⌧ = 50 µ = 400, = 100, ⌧ = 150
R e s u l t s …
R e s u l t s …
R e s u l t s …
R e s u l t s …
O u t p u t s …
Thanks for Listening! Any Questions?