class: title-slide background-image: url(https://raw.githubusercontent.com/SportStatisticsRSweet/WCSF_WorkshopInR/master/WhittenOval.jpg) background-size: cover .left[ # Sport, Data & R ## Alice Sweeting, PhD #### R-Ladies Melbourne <br> Monday 21st September, 2020 ] <img class="logoposR", src="WBLogo.png", width=3.5%> <br> <img class="logoposRB", src="VU_iHES.png", width=20%> <div> <style type="text/css">.xaringan-extra-logo { width: 200px; height: 200px; z-index: 0; background-image: url(https://raw.githubusercontent.com/SportStatisticsRSweet/SportStatisticsRSweet.github.io/master/VU_iHES.png); background-size: contain; background-repeat: no-repeat; position: absolute; top:1em;right:1em; } </style> <script>(function () { let tries = 0 function addLogo () { if (typeof slideshow === 'undefined') { tries += 1 if (tries < 10) { setTimeout(addLogo, 100) } } else { document.querySelectorAll('.remark-slide-content:not(.title-slide):not(.inverse):not(.hide_logo)') .forEach(function (slide) { const logo = document.createElement('a') logo.classList = 'xaringan-extra-logo' logo.href = 'https://www.vu.edu.au/research/institute-for-health-sport' slide.appendChild(logo) }) } } document.addEventListener('DOMContentLoaded', addLogo) })()</script> </div> --- class: inverse, centre, bottom background-image: url(https://www.yarracity.vic.gov.au/-/media/all-images/yarra-city-council-images/events/events-2020/january/_bpp9388.jpg) background-size: cover .center[ .caption[ Image source: [Yarra City Council](https://aboriginalhistoryofyarra.com.au/) ]] --- <br> .pull-left[ <img src="https://raw.githubusercontent.com/SportStatisticsRSweet/SportStatisticsRSweet.github.io/master/AliceLemonade.jpg", align="middle", width="90%"> ] -- .pull-right[ <img src="https://static01.nyt.com/images/2017/12/06/arts/05rolton-obit-2/05rolton-obit-2-jumbo.jpg?quality=90&auto=webp", align="middle", width="100%"> .caption[ Image source: [Equestrian Australia](https://www.nytimes.com/2017/12/04/obituaries/gillian-rolton-australian-who-won-gold-despite-broken-bones-dies-at-61.html)] <img src="https://www.u-vet.com.au/__data/assets/image/0021/63309/UVet-Primary_Co-Branded_RGB_WEB.jpg", align="middle", width="70%"> ] --- class: inverse, bottom, right background-image: url(https://www.vu.edu.au/sites/default/files/building-k-footscray-park-evening.jpg) background-size: cover --- <br> .pull-left[ <img src="https://static.ffx.io/images/$width_800%2C$height_450/t_crop_fill/q_86%2Cf_auto/7e5cde91e8445fa885a0dbde6b277817ee2bcab2", align="middle", width="150%">.caption[ Image source: [Sydney Morning Herald](hthttps://www.smh.com.au/sport/cuttingedge-technology-put-australian-diamonds-on-track-20130521-2jzfu.html)] <br> ### 2013 to 2016: PhD #### Victoria University <br> Netball Australia <br> Australian Institute of Sport] -- .pull-right[ <img src="https://resources.westernbulldogs.com.au/photo-resources/2019/12/01/a3e548cf-df01-4485-bd8f-b89b4da55937/utJEnQbI.jpg?width=952&height=592", align="middle", width="91%"> .caption[ Image source: [Western Bulldogs](https://www.vu.edu.au/about-vu/news-events/news/bulldogs-vu-create-afl-first-partnership)] <br> ### 2017 to present: Research Fellow #### Victoria University <br> Western Bulldogs Football Club] --- class: inverse background-image: url(https://www.vu.edu.au/sites/default/files/images/mitch-wallis-large.jpg) background-size: cover --- class: inverse, bottom, right background-image: url(https://waydev.co/wp-content/uploads/2020/01/moneyball-git-analytics.jpg) background-size: cover <br> <br> <br> .caption[ Image: [Moneyball]()] --- class: inverse, bottom, right background-image: url(https://careers.amsi.org.au/wp-content/uploads/sites/59/2019/06/3_amsi-careers_careerssearch-lp_v3_11.jpg) background-size: cover <br> <br> <br> .caption[ Image source: [AMSI](https://careers.amsi.org.au/search-careers/)] --- class: left, top # Data Sources in Australian Rules Football ### <svg style="height:0.8em;top:.04em;position:relative;fill:black;" viewBox="0 0 512 512"><path d="M504 256c0 136.997-111.043 248-248 248S8 392.997 8 256C8 119.083 119.043 8 256 8s248 111.083 248 248zM262.655 90c-54.497 0-89.255 22.957-116.549 63.758-3.536 5.286-2.353 12.415 2.715 16.258l34.699 26.31c5.205 3.947 12.621 3.008 16.665-2.122 17.864-22.658 30.113-35.797 57.303-35.797 20.429 0 45.698 13.148 45.698 32.958 0 14.976-12.363 22.667-32.534 33.976C247.128 238.528 216 254.941 216 296v4c0 6.627 5.373 12 12 12h56c6.627 0 12-5.373 12-12v-1.333c0-28.462 83.186-29.647 83.186-106.667 0-58.002-60.165-102-116.531-102zM256 338c-25.365 0-46 20.635-46 46 0 25.364 20.635 46 46 46s46-20.636 46-46c0-25.365-20.635-46-46-46z"/></svg> [Monitor how an athlete rates their perceived exertion from a training session.](https://journals.humankinetics.com/view/journals/ijspp/12/2/article-p230.xml) -- <br> ### <svg style="height:0.8em;top:.04em;position:relative;fill:black;" viewBox="0 0 640 512"><path d="M255.03 261.65c6.25 6.25 16.38 6.25 22.63 0l11.31-11.31c6.25-6.25 6.25-16.38 0-22.63L253.25 192l35.71-35.72c6.25-6.25 6.25-16.38 0-22.63l-11.31-11.31c-6.25-6.25-16.38-6.25-22.63 0l-58.34 58.34c-6.25 6.25-6.25 16.38 0 22.63l58.35 58.34zm96.01-11.3l11.31 11.31c6.25 6.25 16.38 6.25 22.63 0l58.34-58.34c6.25-6.25 6.25-16.38 0-22.63l-58.34-58.34c-6.25-6.25-16.38-6.25-22.63 0l-11.31 11.31c-6.25 6.25-6.25 16.38 0 22.63L386.75 192l-35.71 35.72c-6.25 6.25-6.25 16.38 0 22.63zM624 416H381.54c-.74 19.81-14.71 32-32.74 32H288c-18.69 0-33.02-17.47-32.77-32H16c-8.8 0-16 7.2-16 16v16c0 35.2 28.8 64 64 64h512c35.2 0 64-28.8 64-64v-16c0-8.8-7.2-16-16-16zM576 48c0-26.4-21.6-48-48-48H112C85.6 0 64 21.6 64 48v336h512V48zm-64 272H128V64h384v256z"/></svg> [Detect biomechanical characteristics, using wearable technology, during skilled actions.](http://vuir.vu.edu.au/39871/1/icSPORTS_2019_15.pdf) -- <br> ### <svg style="height:0.8em;top:.04em;position:relative;fill:black;" viewBox="0 0 416 512"><path d="M272 96c26.51 0 48-21.49 48-48S298.51 0 272 0s-48 21.49-48 48 21.49 48 48 48zM113.69 317.47l-14.8 34.52H32c-17.67 0-32 14.33-32 32s14.33 32 32 32h77.45c19.25 0 36.58-11.44 44.11-29.09l8.79-20.52-10.67-6.3c-17.32-10.23-30.06-25.37-37.99-42.61zM384 223.99h-44.03l-26.06-53.25c-12.5-25.55-35.45-44.23-61.78-50.94l-71.08-21.14c-28.3-6.8-57.77-.55-80.84 17.14l-39.67 30.41c-14.03 10.75-16.69 30.83-5.92 44.86s30.84 16.66 44.86 5.92l39.69-30.41c7.67-5.89 17.44-8 25.27-6.14l14.7 4.37-37.46 87.39c-12.62 29.48-1.31 64.01 26.3 80.31l84.98 50.17-27.47 87.73c-5.28 16.86 4.11 34.81 20.97 40.09 3.19 1 6.41 1.48 9.58 1.48 13.61 0 26.23-8.77 30.52-22.45l31.64-101.06c5.91-20.77-2.89-43.08-21.64-54.39l-61.24-36.14 31.31-78.28 20.27 41.43c8 16.34 24.92 26.89 43.11 26.89H384c17.67 0 32-14.33 32-32s-14.33-31.99-32-31.99z"/></svg> [Collect an athlete's physical output during training and matches.](https://shapeamerica.tandfonline.com/doi/abs/10.1080/02640414.2019.1577941#.X2RNLWgzaUk) -- <br> ### <svg style="height:0.8em;top:.04em;position:relative;fill:black;" viewBox="0 0 496 512"><path d="M481.5 60.3c-4.8-18.2-19.1-32.5-37.3-37.4C420.3 16.5 383 8.9 339.4 8L496 164.8c-.8-43.5-8.2-80.6-14.5-104.5zm-467 391.4c4.8 18.2 19.1 32.5 37.3 37.4 23.9 6.4 61.2 14 104.8 14.9L0 347.2c.8 43.5 8.2 80.6 14.5 104.5zM4.2 283.4L220.4 500c132.5-19.4 248.8-118.7 271.5-271.4L275.6 12C143.1 31.4 26.8 130.7 4.2 283.4zm317.3-123.6c3.1-3.1 8.2-3.1 11.3 0l11.3 11.3c3.1 3.1 3.1 8.2 0 11.3l-28.3 28.3 28.3 28.3c3.1 3.1 3.1 8.2 0 11.3l-11.3 11.3c-3.1 3.1-8.2 3.1-11.3 0l-28.3-28.3-22.6 22.7 28.3 28.3c3.1 3.1 3.1 8.2 0 11.3l-11.3 11.3c-3.1 3.1-8.2 3.1-11.3 0L248 278.6l-22.6 22.6 28.3 28.3c3.1 3.1 3.1 8.2 0 11.3l-11.3 11.3c-3.1 3.1-8.2 3.1-11.3 0l-28.3-28.3-28.3 28.3c-3.1 3.1-8.2 3.1-11.3 0l-11.3-11.3c-3.1-3.1-3.1-8.2 0-11.3l28.3-28.3-28.3-28.2c-3.1-3.1-3.1-8.2 0-11.3l11.3-11.3c3.1-3.1 8.2-3.1 11.3 0l28.3 28.3 22.6-22.6-28.3-28.3c-3.1-3.1-3.1-8.2 0-11.3l11.3-11.3c3.1-3.1 8.2-3.1 11.3 0l28.3 28.3 22.6-22.6-28.3-28.3c-3.1-3.1-3.1-8.2 0-11.3l11.3-11.3c3.1-3.1 8.2-3.1 11.3 0l28.3 28.3 28.3-28.5z"/></svg> [Record the number of skilled involvements during drills and matches.](https://www.sciencedirect.com/science/article/abs/pii/S0167945719301939) -- <br> ### <svg style="height:0.8em;top:.04em;position:relative;fill:black;" viewBox="0 0 640 512"><path d="M96 224c35.3 0 64-28.7 64-64s-28.7-64-64-64-64 28.7-64 64 28.7 64 64 64zm448 0c35.3 0 64-28.7 64-64s-28.7-64-64-64-64 28.7-64 64 28.7 64 64 64zm32 32h-64c-17.6 0-33.5 7.1-45.1 18.6 40.3 22.1 68.9 62 75.1 109.4h66c17.7 0 32-14.3 32-32v-32c0-35.3-28.7-64-64-64zm-256 0c61.9 0 112-50.1 112-112S381.9 32 320 32 208 82.1 208 144s50.1 112 112 112zm76.8 32h-8.3c-20.8 10-43.9 16-68.5 16s-47.6-6-68.5-16h-8.3C179.6 288 128 339.6 128 403.2V432c0 26.5 21.5 48 48 48h288c26.5 0 48-21.5 48-48v-28.8c0-63.6-51.6-115.2-115.2-115.2zm-223.7-13.4C161.5 263.1 145.6 256 128 256H64c-35.3 0-64 28.7-64 64v32c0 17.7 14.3 32 32 32h65.9c6.3-47.4 34.9-87.3 75.2-109.4z"/></svg> [Quantify the interactions between team-members during training and matches.](https://www.tandfonline.com/doi/abs/10.1080/02640414.2019.1586077) -- <br> ### <svg style="height:0.8em;top:.04em;position:relative;fill:black;" viewBox="0 0 512 512"><path d="M496 384H64V80c0-8.84-7.16-16-16-16H16C7.16 64 0 71.16 0 80v336c0 17.67 14.33 32 32 32h464c8.84 0 16-7.16 16-16v-32c0-8.84-7.16-16-16-16zM464 96H345.94c-21.38 0-32.09 25.85-16.97 40.97l32.4 32.4L288 242.75l-73.37-73.37c-12.5-12.5-32.76-12.5-45.25 0l-68.69 68.69c-6.25 6.25-6.25 16.38 0 22.63l22.62 22.62c6.25 6.25 16.38 6.25 22.63 0L192 237.25l73.37 73.37c12.5 12.5 32.76 12.5 45.25 0l96-96 32.4 32.4c15.12 15.12 40.97 4.41 40.97-16.97V112c.01-8.84-7.15-16-15.99-16z"/></svg> [Track the performance of potential recruits and draft selections.](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0220901) -- <br> ### <svg style="height:0.8em;top:.04em;position:relative;fill:black;" viewBox="0 0 416 512"><path d="M207.9 15.2c.8 4.7 16.1 94.5 16.1 128.8 0 52.3-27.8 89.6-68.9 104.6L168 486.7c.7 13.7-10.2 25.3-24 25.3H80c-13.7 0-24.7-11.5-24-25.3l12.9-238.1C27.7 233.6 0 196.2 0 144 0 109.6 15.3 19.9 16.1 15.2 19.3-5.1 61.4-5.4 64 16.3v141.2c1.3 3.4 15.1 3.2 16 0 1.4-25.3 7.9-139.2 8-141.8 3.3-20.8 44.7-20.8 47.9 0 .2 2.7 6.6 116.5 8 141.8.9 3.2 14.8 3.4 16 0V16.3c2.6-21.6 44.8-21.4 48-1.1zm119.2 285.7l-15 185.1c-1.2 14 9.9 26 23.9 26h56c13.3 0 24-10.7 24-24V24c0-13.2-10.7-24-24-24-82.5 0-221.4 178.5-64.9 300.9z"/></svg> [Estimate the energy expenditure of athletes during training and matches.](https://www.sciencedirect.com/science/article/abs/pii/S1440244015000390) --- class: inverse, center, top background-image: url(https://raw.githubusercontent.com/SportStatisticsRSweet/WCSF_WorkshopInR/master/Figures/W02WBMe20DT993162838.JPG) background-size: cover # VU-WB Research (Data Analytics) Projects --- class: left, top # Exploring Skilled Involvements in the AFL .center[ <img src= "https://raw.githubusercontent.com/SportStatisticsRSweet/RLadiesMelbourneTalk/master/WB_WCE_Score.png", align="middle", width="95%"> ] .right[.caption[ Image source: [afl.com.au](https://www.afl.com.au/matches/2889#team-stats)] ] --- class: left, top # Analysing Skilled Involvements .center[ <img src= "https://raw.githubusercontent.com/SportStatisticsRSweet/RLadiesMelbourneTalk/master/WB_WCE_Disposals.png", align="middle", width="95%"> ] .right[.caption[ Image source: [afl.com.au](https://www.afl.com.au/matches/2889#team-stats)] ] --- class: left, top # Analysing Skilled Involvements .center[ <img src= "https://raw.githubusercontent.com/SportStatisticsRSweet/RLadiesMelbourneTalk/master/WB_WCE_DE.png", align="middle", width="65%"> ] .right[.caption[ Image source: [afl.com.au](https://www.afl.com.au/matches/2889#team-stats)] ] --- class: left, top # Analysing Skilled Involvements .center[ <img src= "https://ars.els-cdn.com/content/image/1-s2.0-S0167945719301939-gr6.jpg", align="middle", width="80%"> ] .right[ Figure from [Browne et al., (2019) in Human Movement Science.](https://www.sciencedirect.com/science/article/pii/S0167945719301939)] --- class: center .left[ # Wearables to Detect Skilled Involvements ] <img src="https://imeasureu.com/wp-content/uploads/2019/10/Soccer-kick.jpg" width="65%"/> .right[Image: [iMeasureU](https://imeasureu.com/wp-content/uploads/2019/10/Soccer-kick.jpg)] --- class: inverse, bottom background-image: url(https://images.catapultsports.com/wp-content/uploads/2018/05/Fundamentals.jpg) background-size: cover .left[ .caption[ Image source: [Catapult Sports](https://www.catapultsports.com/) ]] --- class: center .left[ # Analysing Athlete Physical Output ] <table style="color: black; font-size: 25px; margin-left: auto; margin-right: auto;" class="table table-responsive table-bordered"> <thead> <tr> <th style="text-align:center;font-weight: bold;color: white !important;background-color: #000000 !important;border-right: 1px solid; padding: 15px"> Drill </th> <th style="text-align:center;font-weight: bold;color: white !important;background-color: #000000 !important;border-right: 1px solid; padding: 15px"> Total Duration (mins) </th> <th style="text-align:center;font-weight: bold;color: white !important;background-color: #000000 !important;border-right: 1px solid; padding: 15px"> Total Distance (m) </th> <th style="text-align:center;font-weight: bold;color: white !important;background-color: #000000 !important;border-right: 1px solid; padding: 15px"> Total HIR (m) </th> <th style="text-align:center;font-weight: bold;color: white !important;background-color: #000000 !important;border-right: 1px solid; padding: 15px"> Metres per Min (m/min) </th> </tr> </thead> <tbody> <tr> <td style="text-align:center;"> Warm Up </td> <td style="text-align:center;"> 10 </td> <td style="text-align:center;"> 1026 </td> <td style="text-align:center;"> 83 </td> <td style="text-align:center;"> 103 </td> </tr> <tr> <td style="text-align:center;"> Pair Kicks </td> <td style="text-align:center;"> 6 </td> <td style="text-align:center;"> 414 </td> <td style="text-align:center;"> 12 </td> <td style="text-align:center;"> 69 </td> </tr> <tr> <td style="text-align:center;"> 4v3 Game </td> <td style="text-align:center;"> 5 </td> <td style="text-align:center;"> 849 </td> <td style="text-align:center;"> 277 </td> <td style="text-align:center;"> 170 </td> </tr> <tr> <td style="text-align:center;color: black !important;border-bottom: 1px solid"> Stoppages </td> <td style="text-align:center;color: black !important;border-bottom: 1px solid"> 9 </td> <td style="text-align:center;color: black !important;border-bottom: 1px solid"> 921 </td> <td style="text-align:center;color: black !important;border-bottom: 1px solid"> 362 </td> <td style="text-align:center;color: black !important;border-bottom: 1px solid"> 102 </td> </tr> </tbody> </table> --- class: center .left[ # Analysing Athlete Physical Output ] <img src="https://raw.githubusercontent.com/SportStatisticsRSweet/SportStatisticsRSweet.github.io/master/SportDataR/RawTrace.png", align="middle", width="75%"> --- class: center .left[ # Analysing Athlete Physical Output ] <img src="https://raw.githubusercontent.com/SportStatisticsRSweet/SportStatisticsRSweet.github.io/master/SportDataR/RawTrace_Bands.png", align="middle", width="75%"> --- class: center .left[ # Analysing Athlete Physical Output ] <img src="https://raw.githubusercontent.com/SportStatisticsRSweet/SportStatisticsRSweet.github.io/master/SportDataR/RawTrace_TimeSeries.png", align="middle", width="75%"> --- class: center .left[ # Analysing Athlete Physical Output ] <img src="https://www.tandfonline.com/na101/home/literatum/publisher/tandf/journals/content/rjsp20/2019/rjsp20.v037.i14/02640414.2019.1577941/20190611/images/large/rjsp_a_1577941_f0001_oc.jpeg", align="middle", width="70%"> .right[ Figure from [Corbett et al., (2019) in Journal of Sport Sciences.](https://www.tandfonline.com/doi/full/10.1080/02640414.2019.1577941)] --- class: center .left[ # Analysing Collective Team-Behaviour ] <img src= "https://www.tandfonline.com/na101/home/literatum/publisher/tandf/journals/content/rjsp20/2019/rjsp20.v037.i15/02640414.2019.1586077/20190615/images/large/rjsp_a_1586077_f0001_oc.jpeg", align="middle", width="62%"> .right[ Figure from [Alexander et al., (2019) in Journal of Sport Sciences.](https://www.tandfonline.com/doi/full/10.1080/02640414.2019.1586077)] --- class: center <blockquote class="twitter-tweet"><p lang="en" dir="ltr">📢Practitioners who determine athlete training availability in high performance sport❗️<br>Please participate in my research aimed at improving methods for making these decisions🏋️⛹️🏊<br>EOI➡️<a href="https://t.co/8pyJyullZj">https://t.co/8pyJyullZj</a><a href="https://twitter.com/hashtag/VUSportAnalyticsTech?src=hash&amp;ref_src=twsrc%5Etfw">#VUSportAnalyticsTech</a> <a href="https://twitter.com/TrackVU?ref_src=twsrc%5Etfw">@TrackVU</a> <a href="https://twitter.com/iHealthSportVU?ref_src=twsrc%5Etfw">@iHealthSportVU</a> <a href="https://t.co/wLN4yQ8IVs">pic.twitter.com/wLN4yQ8IVs</a></p>&mdash; Elissa Denton (@DentonElissa) <a href="https://twitter.com/DentonElissa/status/1278828510069415936?ref_src=twsrc%5Etfw">July 2, 2020</a></blockquote> <script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script> --- class: left # Data Hurdles in Sport Science ### <svg style="height:0.8em;top:.04em;position:relative;fill:black;" viewBox="0 0 448 512"><path d="M448 73.143v45.714C448 159.143 347.667 192 224 192S0 159.143 0 118.857V73.143C0 32.857 100.333 0 224 0s224 32.857 224 73.143zM448 176v102.857C448 319.143 347.667 352 224 352S0 319.143 0 278.857V176c48.125 33.143 136.208 48.572 224 48.572S399.874 209.143 448 176zm0 160v102.857C448 479.143 347.667 512 224 512S0 479.143 0 438.857V336c48.125 33.143 136.208 48.572 224 48.572S399.874 369.143 448 336z"/></svg> Importing data from wearables/ different platforms and exports .csv/ .pdf/ .txt etc -- <br> ### <svg style="height:0.8em;top:.04em;position:relative;fill:black;" viewBox="0 0 512 512"><path d="M256 8C119 8 8 119 8 256s111 248 248 248 248-111 248-248S393 8 256 8zm57.1 350.1L224.9 294c-3.1-2.3-4.9-5.9-4.9-9.7V116c0-6.6 5.4-12 12-12h48c6.6 0 12 5.4 12 12v137.7l63.5 46.2c5.4 3.9 6.5 11.4 2.6 16.8l-28.2 38.8c-3.9 5.3-11.4 6.5-16.8 2.6z"/></svg> Synchronising data from different systems at differing sample rates -- <br> ### <svg style="height:0.8em;top:.04em;position:relative;fill:black;" viewBox="0 0 512 512"><path d="M478.21 334.093L336 256l142.21-78.093c11.795-6.477 15.961-21.384 9.232-33.037l-19.48-33.741c-6.728-11.653-21.72-15.499-33.227-8.523L296 186.718l3.475-162.204C299.763 11.061 288.937 0 275.48 0h-38.96c-13.456 0-24.283 11.061-23.994 24.514L216 186.718 77.265 102.607c-11.506-6.976-26.499-3.13-33.227 8.523l-19.48 33.741c-6.728 11.653-2.562 26.56 9.233 33.037L176 256 33.79 334.093c-11.795 6.477-15.961 21.384-9.232 33.037l19.48 33.741c6.728 11.653 21.721 15.499 33.227 8.523L216 325.282l-3.475 162.204C212.237 500.939 223.064 512 236.52 512h38.961c13.456 0 24.283-11.061 23.995-24.514L296 325.282l138.735 84.111c11.506 6.976 26.499 3.13 33.227-8.523l19.48-33.741c6.728-11.653 2.563-26.559-9.232-33.036z"/></svg> Dealing with messy, manual, incomplete data sets! -- <br> ### <svg style="height:0.8em;top:.04em;position:relative;fill:black;" viewBox="0 0 640 512"><path d="M610.5 341.3c2.6-14.1 2.6-28.5 0-42.6l25.8-14.9c3-1.7 4.3-5.2 3.3-8.5-6.7-21.6-18.2-41.2-33.2-57.4-2.3-2.5-6-3.1-9-1.4l-25.8 14.9c-10.9-9.3-23.4-16.5-36.9-21.3v-29.8c0-3.4-2.4-6.4-5.7-7.1-22.3-5-45-4.8-66.2 0-3.3.7-5.7 3.7-5.7 7.1v29.8c-13.5 4.8-26 12-36.9 21.3l-25.8-14.9c-2.9-1.7-6.7-1.1-9 1.4-15 16.2-26.5 35.8-33.2 57.4-1 3.3.4 6.8 3.3 8.5l25.8 14.9c-2.6 14.1-2.6 28.5 0 42.6l-25.8 14.9c-3 1.7-4.3 5.2-3.3 8.5 6.7 21.6 18.2 41.1 33.2 57.4 2.3 2.5 6 3.1 9 1.4l25.8-14.9c10.9 9.3 23.4 16.5 36.9 21.3v29.8c0 3.4 2.4 6.4 5.7 7.1 22.3 5 45 4.8 66.2 0 3.3-.7 5.7-3.7 5.7-7.1v-29.8c13.5-4.8 26-12 36.9-21.3l25.8 14.9c2.9 1.7 6.7 1.1 9-1.4 15-16.2 26.5-35.8 33.2-57.4 1-3.3-.4-6.8-3.3-8.5l-25.8-14.9zM496 368.5c-26.8 0-48.5-21.8-48.5-48.5s21.8-48.5 48.5-48.5 48.5 21.8 48.5 48.5-21.7 48.5-48.5 48.5zM96 224c35.3 0 64-28.7 64-64s-28.7-64-64-64-64 28.7-64 64 28.7 64 64 64zm224 32c1.9 0 3.7-.5 5.6-.6 8.3-21.7 20.5-42.1 36.3-59.2 7.4-8 17.9-12.6 28.9-12.6 6.9 0 13.7 1.8 19.6 5.3l7.9 4.6c.8-.5 1.6-.9 2.4-1.4 7-14.6 11.2-30.8 11.2-48 0-61.9-50.1-112-112-112S208 82.1 208 144c0 61.9 50.1 112 112 112zm105.2 194.5c-2.3-1.2-4.6-2.6-6.8-3.9-8.2 4.8-15.3 9.8-27.5 9.8-10.9 0-21.4-4.6-28.9-12.6-18.3-19.8-32.3-43.9-40.2-69.6-10.7-34.5 24.9-49.7 25.8-50.3-.1-2.6-.1-5.2 0-7.8l-7.9-4.6c-3.8-2.2-7-5-9.8-8.1-3.3.2-6.5.6-9.8.6-24.6 0-47.6-6-68.5-16h-8.3C179.6 288 128 339.6 128 403.2V432c0 26.5 21.5 48 48 48h255.4c-3.7-6-6.2-12.8-6.2-20.3v-9.2zM173.1 274.6C161.5 263.1 145.6 256 128 256H64c-35.3 0-64 28.7-64 64v32c0 17.7 14.3 32 32 32h65.9c6.3-47.4 34.9-87.3 75.2-109.4z"/></svg> Dealing with breadth and depth (strength & conditioning, medical, coaching, recruiting etc) .bg-washed-green.b--dark-green.ba.bw2.br3.shadow-5.ph4.mt5[ The challenge we all face is how to maintain the benefits of breadth, diverse experience, interdisciplinary thinking, and delayed concentration in a world that increasingly incentivizes, even demands, hyperspecialization .tr[ — David Epstein, Range: How Generalists Triumph in a Specialized World ]] --- class: left # How we use R in Sport Science at VU-WB <img src="https://raw.githubusercontent.com/rstudio/hex-stickers/master/PNG/readr.png" width="9%"/> <img src="https://raw.githubusercontent.com/rstudio/hex-stickers/master/PNG/readxl.png" width="9%"/> -- <img src="https://raw.githubusercontent.com/rstudio/hex-stickers/master/PNG/tidyr.png" width="9%"/> <img src="https://raw.githubusercontent.com/rstudio/hex-stickers/master/PNG/lubridate.png" width="9%"/> <img src="https://raw.githubusercontent.com/rstudio/hex-stickers/master/PNG/hms.png" width="9%"/> -- <img src="https://raw.githubusercontent.com/rstudio/hex-stickers/master/PNG/ggplot2.png" width="9%"/> -- <img src="https://raw.githubusercontent.com/rstudio/hex-stickers/master/PNG/flexdashboard.png" width="9%"/> <img src="https://raw.githubusercontent.com/rstudio/hex-stickers/master/PNG/rmarkdown.png" width="9%"/> <img src="https://raw.githubusercontent.com/rstudio/hex-stickers/master/PNG/shiny.png" width="9%"/> <img src="https://raw.githubusercontent.com/rstudio/hex-stickers/master/PNG/xaringan.png" width="9%"/> -- <br> ### <svg style="height:0.8em;top:.04em;position:relative;fill:black;" viewBox="0 0 512 512"><path d="M448 64h-25.98C438.44 92.28 448 125.01 448 160c0 105.87-86.13 192-192 192S64 265.87 64 160c0-34.99 9.56-67.72 25.98-96H64C28.71 64 0 92.71 0 128v320c0 35.29 28.71 64 64 64h384c35.29 0 64-28.71 64-64V128c0-35.29-28.71-64-64-64zM256 320c88.37 0 160-71.63 160-160S344.37 0 256 0 96 71.63 96 160s71.63 160 160 160zm-.3-151.94l33.58-78.36c3.5-8.17 12.94-11.92 21.03-8.41 8.12 3.48 11.88 12.89 8.41 21l-33.67 78.55C291.73 188 296 197.45 296 208c0 22.09-17.91 40-40 40s-40-17.91-40-40c0-21.98 17.76-39.77 39.7-39.94z"/></svg> Creating an interactive report for Club dietitian to see change in body mass -- <br> ### <svg style="height:0.8em;top:.04em;position:relative;fill:black;" viewBox="0 0 512 512"><path d="M332.8 320h38.4c6.4 0 12.8-6.4 12.8-12.8V172.8c0-6.4-6.4-12.8-12.8-12.8h-38.4c-6.4 0-12.8 6.4-12.8 12.8v134.4c0 6.4 6.4 12.8 12.8 12.8zm96 0h38.4c6.4 0 12.8-6.4 12.8-12.8V76.8c0-6.4-6.4-12.8-12.8-12.8h-38.4c-6.4 0-12.8 6.4-12.8 12.8v230.4c0 6.4 6.4 12.8 12.8 12.8zm-288 0h38.4c6.4 0 12.8-6.4 12.8-12.8v-70.4c0-6.4-6.4-12.8-12.8-12.8h-38.4c-6.4 0-12.8 6.4-12.8 12.8v70.4c0 6.4 6.4 12.8 12.8 12.8zm96 0h38.4c6.4 0 12.8-6.4 12.8-12.8V108.8c0-6.4-6.4-12.8-12.8-12.8h-38.4c-6.4 0-12.8 6.4-12.8 12.8v198.4c0 6.4 6.4 12.8 12.8 12.8zM496 384H64V80c0-8.84-7.16-16-16-16H16C7.16 64 0 71.16 0 80v336c0 17.67 14.33 32 32 32h464c8.84 0 16-7.16 16-16v-32c0-8.84-7.16-16-16-16z"/></svg> Visualising team performance indicators (live) during matches for coaching staff -- <br> ### <svg style="height:0.8em;top:.04em;position:relative;fill:black;" viewBox="0 0 384 512"><path d="M377 105L279.1 7c-4.5-4.5-10.6-7-17-7H256v128h128v-6.1c0-6.3-2.5-12.4-7-16.9zm-153 31V0H24C10.7 0 0 10.7 0 24v464c0 13.3 10.7 24 24 24h336c13.3 0 24-10.7 24-24V160H248c-13.2 0-24-10.8-24-24zm64 160v48c0 4.4-3.6 8-8 8h-56v56c0 4.4-3.6 8-8 8h-48c-4.4 0-8-3.6-8-8v-56h-56c-4.4 0-8-3.6-8-8v-48c0-4.4 3.6-8 8-8h56v-56c0-4.4 3.6-8 8-8h48c4.4 0 8 3.6 8 8v56h56c4.4 0 8 3.6 8 8z"/></svg> Communicating return to play data on an athlete during a physiological/ lab based test -- <br> ### <svg style="height:0.8em;top:.04em;position:relative;fill:black;" viewBox="0 0 640 512"><path d="M208 352c-2.39 0-4.78.35-7.06 1.09C187.98 357.3 174.35 360 160 360c-14.35 0-27.98-2.7-40.95-6.91-2.28-.74-4.66-1.09-7.05-1.09C49.94 352-.33 402.48 0 464.62.14 490.88 21.73 512 48 512h224c26.27 0 47.86-21.12 48-47.38.33-62.14-49.94-112.62-112-112.62zm-48-32c53.02 0 96-42.98 96-96s-42.98-96-96-96-96 42.98-96 96 42.98 96 96 96zM592 0H208c-26.47 0-48 22.25-48 49.59V96c23.42 0 45.1 6.78 64 17.8V64h352v288h-64v-64H384v64h-76.24c19.1 16.69 33.12 38.73 39.69 64H592c26.47 0 48-22.25 48-49.59V49.59C640 22.25 618.47 0 592 0z"/></svg> Presenting physical output (GPS, LPS etc) data during post-season reviews -- <br> ### <svg style="height:0.8em;top:.04em;position:relative;fill:black;" viewBox="0 0 640 512"><path d="M622.34 153.2L343.4 67.5c-15.2-4.67-31.6-4.67-46.79 0L17.66 153.2c-23.54 7.23-23.54 38.36 0 45.59l48.63 14.94c-10.67 13.19-17.23 29.28-17.88 46.9C38.78 266.15 32 276.11 32 288c0 10.78 5.68 19.85 13.86 25.65L20.33 428.53C18.11 438.52 25.71 448 35.94 448h56.11c10.24 0 17.84-9.48 15.62-19.47L82.14 313.65C90.32 307.85 96 298.78 96 288c0-11.57-6.47-21.25-15.66-26.87.76-15.02 8.44-28.3 20.69-36.72L296.6 284.5c9.06 2.78 26.44 6.25 46.79 0l278.95-85.7c23.55-7.24 23.55-38.36 0-45.6zM352.79 315.09c-28.53 8.76-52.84 3.92-65.59 0l-145.02-44.55L128 384c0 35.35 85.96 64 192 64s192-28.65 192-64l-14.18-113.47-145.03 44.56z"/></svg> Analysing and preparing data for academic publication/ presentations/ reports --- class: bottom, hide_logo background-image: url(https://pbs.twimg.com/media/EiPx8D4VgAEA2Z1.jpg) background-size: cover .right[ .caption[ Image source: [Suncorp Super Netball](https://twitter.com/SuperNetball/status/1307154470539636737) <br> Ball Artwork © Simone Thomson <br> Yorta-Yorta/Wurundjeri ]] --- class: left # Getting Started with Suncorp Super Netball Data Ensure the packages below are installed or up-to-date: ```r # Create a list of the packages required NetballRPackages <- c( 'tidyverse', 'ggdark', 'devtools') # Install listed packages install.packages(NetballRPackages) ``` -- Now we will install the super neat [`SuperNetballR`](https://stevelane.github.io/superNetballR/) package, with big thanks to Steve Lane. ```r devtools::install_github("stevelane/superNetballR") ``` .center[ <img src="https://media.giphy.com/media/8BlC551jb85FYrWYSV/giphy.gif" align="middle" width="30%"/> ] --- class: left # Analysing Suncorp Super Netball (Team) Data .panelset[ .panel[.panel-name[R Code - Data Import] ```r # Load required packages library(superNetballR) library(tidyverse) library(ggdark) # 2020 season ID SeasonID = "11108" # Download the Firebirds versus Vixens Rd13 match FirebirdsVixens_Rd13 <- downloadMatch(SeasonID, 13, 4) # Tidy the match FirebirdsVixens <- tidyMatch(FirebirdsVixens_Rd13) # Inspect the first few rows head(FirebirdsVixens, 12) ``` ] .panel[.panel-name[R Output - Data Import] ``` ## # A tibble: 12 x 9 ## period squadId squadName squadNickname squadCode stat value round game ## <int> <int> <chr> <chr> <chr> <chr> <dbl> <int> <int> ## 1 1 804 Melbourne V~ Vixens MVX reboun~ 0 13 4 ## 2 2 804 Melbourne V~ Vixens MVX reboun~ 1 13 4 ## 3 3 804 Melbourne V~ Vixens MVX reboun~ 0 13 4 ## 4 4 804 Melbourne V~ Vixens MVX reboun~ 0 13 4 ## 5 1 807 Queensland ~ Firebirds QFB reboun~ 2 13 4 ## 6 2 807 Queensland ~ Firebirds QFB reboun~ 2 13 4 ## 7 3 807 Queensland ~ Firebirds QFB reboun~ 4 13 4 ## 8 4 807 Queensland ~ Firebirds QFB reboun~ 2 13 4 ## 9 1 804 Melbourne V~ Vixens MVX goalsF~ 8 13 4 ## 10 2 804 Melbourne V~ Vixens MVX goalsF~ 9 13 4 ## 11 3 804 Melbourne V~ Vixens MVX goalsF~ 8 13 4 ## 12 4 804 Melbourne V~ Vixens MVX goalsF~ 7 13 4 ``` ] .panel[.panel-name[R Code - Unique Stats] ```r # Inspect the first 30 stats head(unique(FirebirdsVixens$stat), 30) ``` ] .panel[.panel-name[R Output - Unique Stats] ``` ## [1] "rebounds" "goalsFromCentrePass" ## [3] "netPoints" "penalties" ## [5] "generalPlayTurnovers" "deflectionWithNoGain" ## [7] "goal_from_zone2" "goal_from_zone1" ## [9] "timeInPossession" "points" ## [11] "possessions" "goalMisses" ## [13] "goalAssists" "disposals" ## [15] "attempt_from_zone2" "centrePassReceives" ## [17] "obstructionPenalties" "attempt_from_zone1" ## [19] "goals" "offsides" ## [21] "goal2" "goal1" ## [23] "deflectionPossessionGain" "contactPenalties" ## [25] "gainToGoalPerc" "goalsFromTurnovers" ## [27] "centrePassToGoalPerc" "turnoverToGoalPerc" ## [29] "interceptPassThrown" "gain" ``` ] ] --- class: left # Visualising Suncorp Super Netball (Team) Data .panelset[ .panel[.panel-name[R Code - Plot #1] ```r # List of Super Netball colours that are CVD friendly SquadName_Colours <- c("#FDE725FF", "#73D055FF", "#27AD81FF", "#7E4E90FF", "#CC6A70FF", "#2D708EFF", "#C0C0C0", "#F68F46FF") names(SquadName_Colours) <- c("Sunshine Coast Lightning", "West Coast Fever", "Melbourne Vixens", "Queensland Firebirds", "Adelaide Thunderbirds", "NSW Swifts", "Collingwood Magpies", "GIANTS Netball") # Plot - lets look at one stat to start with FirebirdsVixens %>% filter(stat=="generalPlayTurnovers") %>% ggplot(aes(x = period, y = value, colour = squadName)) + geom_point() ``` ] .panel[.panel-name[Plot #1] <img src="Slides_files/figure-html/unnamed-chunk-3-1.png" width="1080" /> ] .panel[.panel-name[R Code - Plot #2] ```r # Make it even happier! FirebirdsVixens %>% filter(stat=="generalPlayTurnovers") %>% ggplot(aes(x = period, y = value, colour = squadName)) + geom_line(linetype = "dashed") + geom_point(size = 8) + geom_text(aes(label = value), size = 4, colour = "black", check_overlap = TRUE) + scale_colour_manual(values = SquadName_Colours) + scale_fill_manual(values = SquadName_Colours) + scale_x_continuous(limits = c(1,4), breaks = c(1:4), labels = function(x) paste0("Quarter ", x)) + scale_y_continuous(expand = c(0,0), limits = c(0, 10), breaks = seq(0,10, by = 2)) + labs(x = NULL, y = "Number of General Play Turnovers \n", title = "\n Rd13 - Firebirds v Vixens \n General Play Turnovers \n") + dark_theme_gray() + theme(plot.title = element_text(size = 14, face = "bold", hjust = 0.5), plot.background = element_rect(fill = "grey10"), panel.background = element_blank(), panel.grid.major = element_blank(), panel.grid.minor = element_blank(), legend.background = element_blank(), axis.title.y = element_text(size = 12, face = "bold"), axis.ticks.x = element_line(color = "grey30", size = 0.1), axis.line.x = element_line(color = "grey30", size = 0.1), axis.text.x = element_text(size = 12, face = "bold"), axis.ticks.y = element_line(color = "grey30", size = 0.1), axis.line.y = element_line(color = "grey30", size = 0.1), axis.text.y = element_text(size = 10, face = "bold"), legend.title = element_blank(), legend.position = "bottom") ``` ] .panel[.panel-name[Plot #2] <img src="Slides_files/figure-html/unnamed-chunk-4-1.png" width="1080" /> ] ] --- class: left # Analysing Suncorp Super Netball (Athlete) Data .panelset[ .panel[.panel-name[R Code - Data Import] ```r # Tidy individual player data PlayerData <- tidyPlayers(FirebirdsVixens_Rd13) # Inspect first 12 rows head(PlayerData, 12) ``` ] .panel[.panel-name[R Output - Data Import] ``` ## # A tibble: 12 x 11 ## period squadId playerId shortDisplayName firstname surname squadName stat ## <int> <int> <int> <chr> <chr> <chr> <chr> <chr> ## 1 1 804 80577 Weston, J Jo Weston Melbourn~ rebo~ ## 2 2 804 80577 Weston, J Jo Weston Melbourn~ rebo~ ## 3 3 804 80577 Weston, J Jo Weston Melbourn~ rebo~ ## 4 4 804 80577 Weston, J Jo Weston Melbourn~ rebo~ ## 5 1 804 1014127 Smith, A Allie Smith Melbourn~ rebo~ ## 6 2 804 1014127 Smith, A Allie Smith Melbourn~ rebo~ ## 7 3 804 1014127 Smith, A Allie Smith Melbourn~ rebo~ ## 8 4 804 1014127 Smith, A Allie Smith Melbourn~ rebo~ ## 9 1 804 80293 Philip, T Tegan Philip Melbourn~ rebo~ ## 10 2 804 80293 Philip, T Tegan Philip Melbourn~ rebo~ ## 11 3 804 80293 Philip, T Tegan Philip Melbourn~ rebo~ ## 12 4 804 80293 Philip, T Tegan Philip Melbourn~ rebo~ ## # ... with 3 more variables: value <chr>, round <int>, game <int> ``` ] .panel[.panel-name[R Code - Data Tidy] ```r # Call out the stats that are giving us issues PlayerData %>% filter((stat %in% c("startingPositionCode", "currentPositionCode"))) %>% head(12) ``` ] .panel[.panel-name[R Output - Data Tidy] ``` ## # A tibble: 12 x 11 ## period squadId playerId shortDisplayName firstname surname squadName stat ## <int> <int> <int> <chr> <chr> <chr> <chr> <chr> ## 1 1 804 80577 Weston, J Jo Weston Melbourn~ star~ ## 2 2 804 80577 Weston, J Jo Weston Melbourn~ star~ ## 3 3 804 80577 Weston, J Jo Weston Melbourn~ star~ ## 4 4 804 80577 Weston, J Jo Weston Melbourn~ star~ ## 5 1 804 1014127 Smith, A Allie Smith Melbourn~ star~ ## 6 2 804 1014127 Smith, A Allie Smith Melbourn~ star~ ## 7 3 804 1014127 Smith, A Allie Smith Melbourn~ star~ ## 8 4 804 1014127 Smith, A Allie Smith Melbourn~ star~ ## 9 1 804 80293 Philip, T Tegan Philip Melbourn~ star~ ## 10 2 804 80293 Philip, T Tegan Philip Melbourn~ star~ ## 11 3 804 80293 Philip, T Tegan Philip Melbourn~ star~ ## 12 4 804 80293 Philip, T Tegan Philip Melbourn~ star~ ## # ... with 3 more variables: value <chr>, round <int>, game <int> ``` ] ] --- class: left # Analysing Suncorp Super Netball (League - Team) Data .panelset[ .panel[.panel-name[R Code - Import All Teams] ```r # First, create an empty data.frame SSN_Rd13 <- FirebirdsVixens[0,] # Call out the round we are after, can change this to whatever round you are interested in! getRound = 13 # Run a loop to grab data for Rd13 for (mm in 1:4) { # Download match matchData <- downloadMatch(SeasonID,getRound,mm) # Tidy data tidy_match <- tidyMatch(matchData) # Append SSN_Rd13 <- rbind(tidy_match,SSN_Rd13) } # Inspect tail(SSN_Rd13, 12) ``` ] .panel[.panel-name[R Ouput - Import All Teams] ``` ## # A tibble: 12 x 9 ## period squadId squadName squadNickname squadCode stat value round game ## <int> <int> <chr> <chr> <chr> <chr> <dbl> <int> <int> ## 1 1 8119 Collingwood ~ Magpies MNC inter~ 3 13 1 ## 2 2 8119 Collingwood ~ Magpies MNC inter~ 2 13 1 ## 3 3 8119 Collingwood ~ Magpies MNC inter~ 4 13 1 ## 4 4 8119 Collingwood ~ Magpies MNC inter~ 1 13 1 ## 5 1 8117 Sunshine Coa~ Lightning SCL homeT~ 0 13 1 ## 6 2 8117 Sunshine Coa~ Lightning SCL homeT~ 0 13 1 ## 7 3 8117 Sunshine Coa~ Lightning SCL homeT~ 0 13 1 ## 8 4 8117 Sunshine Coa~ Lightning SCL homeT~ 0 13 1 ## 9 1 8119 Collingwood ~ Magpies MNC homeT~ 1 13 1 ## 10 2 8119 Collingwood ~ Magpies MNC homeT~ 1 13 1 ## 11 3 8119 Collingwood ~ Magpies MNC homeT~ 1 13 1 ## 12 4 8119 Collingwood ~ Magpies MNC homeT~ 1 13 1 ``` ] .panel[.panel-name[R Code - Plot #3] ```r # Now plot GPT for each team SSN_Rd13 %>% filter(stat=="generalPlayTurnovers") %>% group_by(squadName) %>% summarise(Total = sum(value)) %>% arrange(desc(Total)) %>% ggplot(aes(x = reorder(squadName, -Total), y = Total, colour = squadName)) + geom_point(size = 10) + geom_segment(aes(x = squadName, y = 0, xend = squadName, yend = Total, colour = squadName), linetype = "dashed") + geom_text(aes(label = Total), size = 4, colour = "black", check_overlap = TRUE) + scale_colour_manual(values = SquadName_Colours) + scale_fill_manual(values = SquadName_Colours) + scale_y_continuous(expand = c(0,0), limits = c(0, 40), breaks = seq(0,40, by = 10)) + labs(x = NULL, y = "Number of General Play Turnovers \n", title = "\n Suncorp Super Netball 2020 \n Rd13 - General Play Turnovers \n") + dark_theme_gray() + theme(plot.title = element_text(size = 14, face = "bold", hjust = 0.5), plot.background = element_rect(fill = "grey10"), panel.background = element_blank(), panel.grid.major = element_blank(), panel.grid.minor = element_blank(), legend.background = element_blank(), axis.title.y = element_text(size = 12, face = "bold"), axis.ticks.x = element_line(color = "grey30", size = 0.1), axis.line.x = element_line(color = "grey30", size = 0.1), axis.text.x = element_text(size = 12, face = "bold", angle = 45, vjust = 1, hjust = 1), axis.ticks.y = element_line(color = "grey30", size = 0.1), axis.line.y = element_line(color = "grey30", size = 0.1), axis.text.y = element_text(size = 10, face = "bold"),legend.title = element_blank(), legend.position = "none") ``` ] .panel[.panel-name[Plot #3 - Team Data] <img src="Slides_files/figure-html/unnamed-chunk-8-1.png" width="1080" /> ] ] --- class: left # Analysing Suncorp Super Netball (League - Athlete) Data .panelset[ .panel[.panel-name[R Code - Import All Athletes] ```r # First, create an empty data.frame SSN_Rd13_Players <- PlayerData[0,] # Call out the round we are after, can change this to whatever round you are interested in! getRound = 13 # Run a loop to grab data for Rd13 for (mm in 1:4) { # Download match matchData <- downloadMatch(SeasonID,getRound,mm) # Tidy data tidy_player <- tidyPlayers(matchData) # Append SSN_Rd13_Players <- rbind(tidy_player,SSN_Rd13_Players) } # Inspect tail(SSN_Rd13_Players, 12) ``` ] .panel[.panel-name[R Ouput - All Athletes] ``` ## # A tibble: 12 x 11 ## period squadId playerId shortDisplayName firstname surname squadName stat ## <int> <int> <int> <chr> <chr> <chr> <chr> <chr> ## 1 1 8119 1010545 Nelson, S Shimona Nelson Collingw~ inte~ ## 2 2 8119 1010545 Nelson, S Shimona Nelson Collingw~ inte~ ## 3 3 8119 1010545 Nelson, S Shimona Nelson Collingw~ inte~ ## 4 4 8119 1010545 Nelson, S Shimona Nelson Collingw~ inte~ ## 5 1 8119 1021073 Black, K Kaitlyn Black Collingw~ inte~ ## 6 2 8119 1021073 Black, K Kaitlyn Black Collingw~ inte~ ## 7 3 8119 1021073 Black, K Kaitlyn Black Collingw~ inte~ ## 8 4 8119 1021073 Black, K Kaitlyn Black Collingw~ inte~ ## 9 1 8117 1014128 Proscovia, P Peace Prosco~ Sunshine~ inte~ ## 10 2 8117 1014128 Proscovia, P Peace Prosco~ Sunshine~ inte~ ## 11 3 8117 1014128 Proscovia, P Peace Prosco~ Sunshine~ inte~ ## 12 4 8117 1014128 Proscovia, P Peace Prosco~ Sunshine~ inte~ ## # ... with 3 more variables: value <chr>, round <int>, game <int> ``` ] .panel[.panel-name[R Code - Plot #4] ```r # Plot the top 10 athletes for stat = feedWithAttempt SSN_Rd13_Players %>% filter(!(stat %in% c("startingPositionCode", "currentPositionCode"))) %>% mutate_at("value", as.numeric) %>% filter(stat=="feedWithAttempt") %>% group_by(shortDisplayName, squadName) %>% summarise(Total = sum(value)) %>% arrange(desc(Total)) %>% head(10) %>% ggplot(aes(x = reorder(shortDisplayName, -Total), y = Total, colour = squadName)) + geom_point(size = 10) + geom_segment(aes(x = shortDisplayName, y = 0, xend = shortDisplayName, yend = Total, colour = squadName), linetype = "dashed") + geom_text(aes(label = Total), size = 4, colour = "black", check_overlap = TRUE) + scale_colour_manual(values = SquadName_Colours) + scale_fill_manual(values = SquadName_Colours) + scale_y_continuous(expand = c(0,0), limits = c(0, 40), breaks = seq(0,40, by = 10)) + labs(x = NULL, y = "Number of Feeds with Attempt \n", title = "\n Suncorp Super Netball 2020 \n Rd13 - Feeds with Attempt (Individual Players) \n") + dark_theme_gray() + theme(plot.title = element_text(size = 14, face = "bold", hjust = 0.5), plot.background = element_rect(fill = "grey10"), panel.background = element_blank(), panel.grid.major = element_blank(), panel.grid.minor = element_blank(), legend.background = element_blank(), axis.title.y = element_text(size = 12, face = "bold"), axis.ticks.x = element_line(color = "grey30", size = 0.1), axis.line.x = element_line(color = "grey30", size = 0.1), axis.text.x = element_text(size = 12, face = "bold", angle = 45, vjust = 1, hjust = 1), axis.ticks.y = element_line(color = "grey30", size = 0.1), axis.line.y = element_line(color = "grey30", size = 0.1), axis.text.y = element_text(size = 10, face = "bold"),legend.title = element_blank(), legend.position = "none") ``` ] .panel[.panel-name[Plot #4] <img src="Slides_files/figure-html/unnamed-chunk-10-1.png" width="1080" /> ] ] --- class: left # Interesting Things in Suncorp Super Netball... ### <svg style="height:0.8em;top:.04em;position:relative;fill:black;" viewBox="0 0 384 512"><path d="M202.021 0C122.202 0 70.503 32.703 29.914 91.026c-7.363 10.58-5.093 25.086 5.178 32.874l43.138 32.709c10.373 7.865 25.132 6.026 33.253-4.148 25.049-31.381 43.63-49.449 82.757-49.449 30.764 0 68.816 19.799 68.816 49.631 0 22.552-18.617 34.134-48.993 51.164-35.423 19.86-82.299 44.576-82.299 106.405V320c0 13.255 10.745 24 24 24h72.471c13.255 0 24-10.745 24-24v-5.773c0-42.86 125.268-44.645 125.268-160.627C377.504 66.256 286.902 0 202.021 0zM192 373.459c-38.196 0-69.271 31.075-69.271 69.271 0 38.195 31.075 69.27 69.271 69.27s69.271-31.075 69.271-69.271-31.075-69.27-69.271-69.27z"/></svg> How does the new Suncorp Super Shot impact how a team can "claw" back into a match? -- <br> ### <svg style="height:0.8em;top:.04em;position:relative;fill:black;" viewBox="0 0 512 512"><path d="M0 168v-16c0-13.255 10.745-24 24-24h360V80c0-21.367 25.899-32.042 40.971-16.971l80 80c9.372 9.373 9.372 24.569 0 33.941l-80 80C409.956 271.982 384 261.456 384 240v-48H24c-13.255 0-24-10.745-24-24zm488 152H128v-48c0-21.314-25.862-32.08-40.971-16.971l-80 80c-9.372 9.373-9.372 24.569 0 33.941l80 80C102.057 463.997 128 453.437 128 432v-48h360c13.255 0 24-10.745 24-24v-16c0-13.255-10.745-24-24-24z"/></svg> How does the new rolling substitute rule impact margin? -- <br> ### <svg style="height:0.8em;top:.04em;position:relative;fill:black;" viewBox="0 0 640 512"><path d="M496 224c-79.6 0-144 64.4-144 144s64.4 144 144 144 144-64.4 144-144-64.4-144-144-144zm64 150.3c0 5.3-4.4 9.7-9.7 9.7h-60.6c-5.3 0-9.7-4.4-9.7-9.7v-76.6c0-5.3 4.4-9.7 9.7-9.7h12.6c5.3 0 9.7 4.4 9.7 9.7V352h38.3c5.3 0 9.7 4.4 9.7 9.7v12.6zM320 368c0-27.8 6.7-54.1 18.2-77.5-8-1.5-16.2-2.5-24.6-2.5h-16.7c-22.2 10.2-46.9 16-72.9 16s-50.6-5.8-72.9-16h-16.7C60.2 288 0 348.2 0 422.4V464c0 26.5 21.5 48 48 48h347.1c-45.3-31.9-75.1-84.5-75.1-144zm-96-112c70.7 0 128-57.3 128-128S294.7 0 224 0 96 57.3 96 128s57.3 128 128 128z"/></svg> Does calling a timeout help or hinder momentum? Including the opposition? -- <br> ### <svg style="height:0.8em;top:.04em;position:relative;fill:black;" viewBox="0 0 640 512"><path d="M128 96c26.5 0 48-21.5 48-48S154.5 0 128 0 80 21.5 80 48s21.5 48 48 48zm384 0c26.5 0 48-21.5 48-48S538.5 0 512 0s-48 21.5-48 48 21.5 48 48 48zm125.7 372.1l-44-110-41.1 46.4-2 18.2 27.7 69.2c5 12.5 17 20.1 29.7 20.1 4 0 8-.7 11.9-2.3 16.4-6.6 24.4-25.2 17.8-41.6zm-34.2-209.8L585 178.1c-4.6-20-18.6-36.8-37.5-44.9-18.5-8-39-6.7-56.1 3.3-22.7 13.4-39.7 34.5-48.1 59.4L432 229.8 416 240v-96c0-8.8-7.2-16-16-16H240c-8.8 0-16 7.2-16 16v96l-16.1-10.2-11.3-33.9c-8.3-25-25.4-46-48.1-59.4-17.2-10-37.6-11.3-56.1-3.3-18.9 8.1-32.9 24.9-37.5 44.9l-18.4 80.2c-4.6 20 .7 41.2 14.4 56.7l67.2 75.9 10.1 92.6C130 499.8 143.8 512 160 512c1.2 0 2.3-.1 3.5-.2 17.6-1.9 30.2-17.7 28.3-35.3l-10.1-92.8c-1.5-13-6.9-25.1-15.6-35l-43.3-49 17.6-70.3 6.8 20.4c4.1 12.5 11.9 23.4 24.5 32.6l51.1 32.5c4.6 2.9 12.1 4.6 17.2 5h160c5.1-.4 12.6-2.1 17.2-5l51.1-32.5c12.6-9.2 20.4-20 24.5-32.6l6.8-20.4 17.6 70.3-43.3 49c-8.7 9.9-14.1 22-15.6 35l-10.1 92.8c-1.9 17.6 10.8 33.4 28.3 35.3 1.2.1 2.3.2 3.5.2 16.1 0 30-12.1 31.8-28.5l10.1-92.6 67.2-75.9c13.6-15.5 19-36.7 14.4-56.7zM46.3 358.1l-44 110c-6.6 16.4 1.4 35 17.8 41.6 16.8 6.6 35.1-1.7 41.6-17.8l27.7-69.2-2-18.2-41.1-46.4z"/></svg> Does using depth from the bench impact margin/ momentum? Consistent seven? -- <br> ### <svg style="height:0.8em;top:.04em;position:relative;fill:black;" viewBox="0 0 512 512"><path d="M504 256c0 136.997-111.043 248-248 248S8 392.997 8 256C8 119.083 119.043 8 256 8s248 111.083 248 248zm-248 50c-25.405 0-46 20.595-46 46s20.595 46 46 46 46-20.595 46-46-20.595-46-46-46zm-43.673-165.346l7.418 136c.347 6.364 5.609 11.346 11.982 11.346h48.546c6.373 0 11.635-4.982 11.982-11.346l7.418-136c.375-6.874-5.098-12.654-11.982-12.654h-63.383c-6.884 0-12.356 5.78-11.981 12.654z"/></svg> What statistics/ performance indicators are important in (2020) Super Netball? --- class: left # Interested in R Packages for Sports Data? <img src="https://raw.githubusercontent.com/jimmyday12/fitzRoy/master/man/figures/fitz_hex.png" width="15%"/> -- <img src="https://camo.githubusercontent.com/286e689828c5f9efe22041bf33ed1b61aafafc0c/68747470733a2f2f617362636c6c632e636f6d2f6c6f676f732f6e626173746174522e706e67" width="15%"/> -- <img src="https://mrcaseb.github.io/nflfastR/reference/figures/logo.png" width="15%"/> -- <br> [BaseballR](http://billpetti.github.io/baseballr/) -- <br> [collegeballR](https://github.com/meysubb/collegeballR) -- <br> [cricketR](https://github.com/tvganesh/cricketr) -- .pull-right[ <img src="https://media.giphy.com/media/3oz8xAIWSf6s8aFkdO/giphy.gif" align="middle" width="65%"/> ] --- .pull-left[ <img src="https://raw.githubusercontent.com/allisonhorst/stats-illustrations/master/rstats-artwork/r_first_then.png"/> ] -- .pull-right[ <img src="https://github.com/allisonhorst/stats-illustrations/raw/master/rstats-artwork/welcome_to_rstats_twitter.png"/> ] .right[All (beautiful!) artwork here is by the very talented [@allison_horst](https://github.com/allisonhorst/stats-illustrations)] --- class: left, top # Any Questions? .pull-left[ <img src="https://raw.githubusercontent.com/SportStatisticsRSweet/RLadiesMelbourneTalk/master/Dudley.jpg" width="70%"/> ] <span style = 'font-size: 50%;'> .pull-right[ <br> ## <svg style="height:0.8em;top:.04em;position:relative;fill:black;" viewBox="0 0 512 512"><path d="M502.3 190.8c3.9-3.1 9.7-.2 9.7 4.7V400c0 26.5-21.5 48-48 48H48c-26.5 0-48-21.5-48-48V195.6c0-5 5.7-7.8 9.7-4.7 22.4 17.4 52.1 39.5 154.1 113.6 21.1 15.4 56.7 47.8 92.2 47.6 35.7.3 72-32.8 92.3-47.6 102-74.1 131.6-96.3 154-113.7zM256 320c23.2.4 56.6-29.2 73.4-41.4 132.7-96.3 142.8-104.7 173.4-128.7 5.8-4.5 9.2-11.5 9.2-18.9v-19c0-26.5-21.5-48-48-48H48C21.5 64 0 85.5 0 112v19c0 7.4 3.4 14.3 9.2 18.9 30.6 23.9 40.7 32.4 173.4 128.7 16.8 12.2 50.2 41.8 73.4 41.4z"/></svg> [Alice.Sweeting@vu.edu.au](mailto:Alice.Sweeting@vu.edu.au)<br> ## <svg style="height:0.8em;top:.04em;position:relative;fill:black;" viewBox="0 0 512 512"><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg> [alicesweeting](https://twitter.com/alicesweeting)<br> ## <svg style="height:0.8em;top:.04em;position:relative;fill:black;" viewBox="0 0 496 512"><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg> [SportStatisticsRSweet](https://github.com/SportStatisticsRSweet)<br> ## <svg style="height:0.8em;top:.04em;position:relative;fill:black;" viewBox="0 0 512 512"><path d="M326.612 185.391c59.747 59.809 58.927 155.698.36 214.59-.11.12-.24.25-.36.37l-67.2 67.2c-59.27 59.27-155.699 59.262-214.96 0-59.27-59.26-59.27-155.7 0-214.96l37.106-37.106c9.84-9.84 26.786-3.3 27.294 10.606.648 17.722 3.826 35.527 9.69 52.721 1.986 5.822.567 12.262-3.783 16.612l-13.087 13.087c-28.026 28.026-28.905 73.66-1.155 101.96 28.024 28.579 74.086 28.749 102.325.51l67.2-67.19c28.191-28.191 28.073-73.757 0-101.83-3.701-3.694-7.429-6.564-10.341-8.569a16.037 16.037 0 0 1-6.947-12.606c-.396-10.567 3.348-21.456 11.698-29.806l21.054-21.055c5.521-5.521 14.182-6.199 20.584-1.731a152.482 152.482 0 0 1 20.522 17.197zM467.547 44.449c-59.261-59.262-155.69-59.27-214.96 0l-67.2 67.2c-.12.12-.25.25-.36.37-58.566 58.892-59.387 154.781.36 214.59a152.454 152.454 0 0 0 20.521 17.196c6.402 4.468 15.064 3.789 20.584-1.731l21.054-21.055c8.35-8.35 12.094-19.239 11.698-29.806a16.037 16.037 0 0 0-6.947-12.606c-2.912-2.005-6.64-4.875-10.341-8.569-28.073-28.073-28.191-73.639 0-101.83l67.2-67.19c28.239-28.239 74.3-28.069 102.325.51 27.75 28.3 26.872 73.934-1.155 101.96l-13.087 13.087c-4.35 4.35-5.769 10.79-3.783 16.612 5.864 17.194 9.042 34.999 9.69 52.721.509 13.906 17.454 20.446 27.294 10.606l37.106-37.106c59.271-59.259 59.271-155.699.001-214.959z"/></svg> [SportStatisticsRSweet.rbind.io](http://sportstatisticsrsweet.rbind.io/)<br> ]