In honor of ds106 radio and thinking ahead to our session at Northern Voice 2011, this retro mic was suggested as a prop– it is pretty much a plastic piece of junk- it does record audio, with noise, and it wont work at all streaming with Nicecast. But it does have a light on top.
Introduction
Alan Levine has had a close look at the inclusion of audio recordings in WordPress blog posts (link).
He looked at SPLOT Box (link) as the host for his audio. There is a demonstration of his work on SPLOT Box (link). He used Video.js Record (link) to record his audio.
What is interesting about Alan’s process is the opportunity for collaborative work through the audio recording.
Discussion
Alan’s post raises important issues about the role of audio in blog posts. His instructions are comprehensive.
I have looked at a variety of options for audio in WordPress. I have not had the opportunity to explore SPLOT Box (link). I do think the possibility of collaborative audio is fascinating. Alan observes in his post “with support for podcasting feeds, moderation options, and now recording, this could be a one site podcast studio. The thing you get with this… is an ability to have people contribute content”.
The availability of multiple podcasts makes this sharing particularly interesting. One could imagine compilations and aggregation of ideas that adds to the accessibility dimensions of WordPress sites. W3C has some excellent advice in this regard (link).
The Big Bash Regular Season concluded on the 27th January with the Renegades’ defeat of the Heat (link) by seven wickets with four balls remaining.
During the Regular Season, there were forty-two games in which the result was decided without a Duckworth-Lewis rate being set. In these games, the median winning score was 168 runs and thee median losing score was 148 runs. The median rate set by the team batting first was 17 runs per wicket.
A ggplot of winning and losing scores:
The two outliers in this plot are the Stars v Scorchers (a rate of 9 runs per wicket) and the Hirricanes v Strikers (a rate of 22 runs per wicket).
When to Bat?
Of the forty two games played without a Duckworth-Lewis Rate, the winning team batted first 22 times and second 22 times. The data suggest that teams won when batting second when a low rate was set:
Games were won by a team batting first that was able to set a high rate:
Teams found it difficult to chase down a high rate.
There are three games in the BBL 2019-2020 that give outliers and medians after the Sixers’ game against the Heat. All three games involve the Stars who won all three games. The Stars batted first twice (v Sixers and v Heat) and second once (v Scorchers).
I really enjoy writing blog posts on Clyde Street. I have been blogging on WordPress since 2008 and am approaching my 2000th post. I have always thought that my blog was a way for me to think out aloud and explore ideas in teaching, coaching, learning and performance. I did not anticipate an audience for my writing but I have been surprised that Clyde Street has had nearly half a million visits since 2008.
In addition to thinking out loud, one of the aims of my blog was to put teaching, coaching, learning and performance in a social media space and to explore what ubiquitous access through phones might be (link). A second aim was to explore alternative means of scholarly communication (link). This, as Alan Levine points out requires full disclosure about content attribution (link) and appreciative inquiry (link). I was really heartened when the LSE Impact blog took up these issues (link) as “a burgeoning area of knowledge exchange that seeks to assist with the dissemination of substantive research and analysis”.
Standards for Writing Accessibly
I am mindful that Stephen Downes keeps an eye on the process and form of blogging (link). This week his newsletter included a link to Michael J. Metts and Andy Welfle’s Standards for Writing Accessibly (link).
They propose we write:
Chronologically, not Spatially
Left to Right, Top to Bottom
Without the of Use Colors and Icons Alone
About the Action, not the Behavior
Michael and Andy also have some advice about screen readers. They note
The average reading time for sighted readers is two to five words per second. Screen-reader users can comprehend text being read at an average of 35 syllables per second, which is significantly faster.
People want to be able to skim long blocks of text, regardless of sight or audio, so it’s extremely important to structure your long form writing with headers, short paragraphs, and other content design best practices.
Conclusion
The About section of the LSE Impact blog observes that it is “a hub for researchers, administrative staff, librarians, students, think tanks, government, and anyone else interested in maximising the impact of academic work in the social sciences and other disciplines. We hope to encourage debate, share best practice and keep the impact community up to date with news, events and the latest research” (link).
I do think the power of blogs compared to academic books and papers is their immediacy and connection with current practice. Their digital form means that the posts can be updated and new links added. In my case, I have been able to add postscripts to enrich posts with recommendations made. As an action researcher it has also enabled me to modify my texts when there have been strong objections to content. I see blogging in this sense as an inclusive activity without abandoning critical judgement.
Postscript
The LSE Impact blog shows hoe to cite blog posts. For this article on WordPress, I have used these references:
Catherine Moore (2019). What is Appreciative Inquiry? A Brief History & Real Life Examples. Postive Psychology blog https://positivepsychology.com/appreciative-inquiry/ 19 November 2019 (Accessed 24 January 2020).
The Hurricanes have defeated the Renegades by four runs in a #BBL game played on 21 January (link). The Hurricanes batted first and set the Renegades the rate of 19 runs per wicket to win the game.
This season in the BBL, there have been seven other occasions (in non-Duckworth-Lewis games) when a team has set a rate of 19 or more runs. All these games have been won by the team setting that rate. The Renegades are the team that has come closest to winning when batting second.
My ggplot of the game data:
This season in the BBL, the median winning score is 167 runs, and the median losing score is 146 runs. The median rate set is 17 runs per partnership.
I have a record of 37 BBL games for the 2019-2020 (link) that were completed without Duckworth-Lewis calculations.
My data from these games suggest that the median winning score is 166 runs and the median losing score is 145 runs. The rate set at the end of the first innings is a median of 16 runs per wicket.
My ggplot for the 37 games (with a geom_vline and a geom_hline) is:
Using the ggrepel function (link), these data can be subdivided:
I have 142 examples of a team scoring first and losing in six European football leagues this season. The leagues are EPL, Ligue 1, Bundesliga, Serie A, Eredevisie, and the Primeira.
For teams that overcome a first goal and win, the median time to equalise is 22 minutes. The median time to win a game after going a goal behind is 46 minutes.
My ggplot of these 142 games and my geom_vline and geom_hline (in black) to indicate the medians is:
The outlier in these data is Borussia Mönchengladbach who took 81 minutes to win against Fortuna Dusseldorf in week 5 of the Bundesliga season (link).
Two recent games in the BBL have resulted in low scores. Both games involved the Brisbane Heat.
On 17 January, the Adelaide Strikers defeated the Brisbane Heat by ten wickets (link). Brisbane Heat batted first and set a rate of 10 runs per wicket for the Strikers. It is very rare that a team does not chase down a rate of 10.
My ggplot of this game:
In a second game on 19 January, the Melbourne Renegades defeated the Brisbane Heat by 44 runs (link). The Melbourne Renegades batted first and set the Heat a rate of 16 runs per wicket. 16 is not a big rate and teams have chased down this rate in the BBL. At one stage the Heat were 0-83. They were all out 37 runs later. My ggplot indicates what happened after the first wicket partnership:
I think both games have important lessons for how teams deal with the rate they have been set when they bat second.
I have had lots of time in recent months to think about pedagogical practice in sport analytics. A number of my posts in Clyde Street (link) have sought to address the changing world of sport analytics. The catalyst for my thinking has been Mine Cetinkaya-Rundel’s speaker deck, Let them eat cake (first)! (link).
I found her backward design ideas compelling and they encouraged me to think about how we prepare analysts for the world of work. Not all students will find a place in the competitive world of sport analytics, but like Sam Gregory (link), I think working in a club isn’t the only job. I do think we must stop recruiting students with promises of employment in high performance sport. We can share alternative employment options but these require our students to be highly skilled and knowledgeable. It requires us as teachers to be reflective too and demonstrate the soft (power) skills essential to practice as an analyst (link).
My thoughts, through backward design, have led me to think about how we share with students. I have Gergely Csibra and Gyorgy Gergely’s (2009) optimism about how we might share through natural pedagogy and how we might acquire new information and use it later when necessary.
In their 2009 paper (link), Gergely and Gyorgy propose “human communication is specifically adapted to allow the transmission of generic knowledge between individuals. Such a communication system, which we call ‘natural pedagogy’, enables fast and efficient social learning of cognitively opaque cultural knowledge that would be hard to acquire relying on purely observational learning mechanisms alone”.
We need conversations about how we might promote this natural pedagogy through attentional and communicative gaze and how we do with the presence of learners (link). I do think backward design facilitates this through opening up conversations and enables us to contemplate epistemic vigilence (link). (My emphases.)
Sam Gregory (link) has posted Getting into Sports Analytics 2.0 (19 January 2020) (link). Sam’s aim is to update the post he wrote in 2017, Getting into Sports Analytics (link) “the analytics world has changed since 2017: more public data sources, more job postings, and almost certainly more competition for those job postings”. I think Sam’s 2.0 article resonates strongly with some of the analytics issues raised in Clyde Street (link).
1.0
In his 2017 article, which I am calling Sport Analytics 1.0, Sam noted that he was often asked “how do I get a job in sports analytics”. He observed “I don’t really have a satisfactory answer either beyond what was told to me or an in-depth and overly specific life story. But because this is a question I get so much I thought I could give at least a few tips that I’ve picked up along the way that have either helped me or people I know in the industry”.
Sam suggested that prospective analysts:
Start doing work now and make it public
Sports Analytics isn’t a degree (and it doesn’t need to be)
Learn
Working in a club isn’t the only job
You still might not get a job and that’s okay
Sam concludes his post “so now that I’ve written all of these ideas out somewhere I hope that next time instead of messaging me to ask for advice on how to break into the industry you’ll message me with your first blog post or an example of some public work!”.
When I read Sam’s post I thought he offered some excellent advice. I was particularly interested in the sharing and learning parts of his advice. I thought sam’s career was an excellent example of the story he shared.
2.0
Sam’s 2020 article updates his 2017 post. In it he notes “the analytics world has changed since 2017: more public data sources, more job postings, and almost certainly more competition for those job postings”.
Sam looks at:
University Degrees
University Sports Analytics Clubs
Public Data Sets and Code
Sports Analytics Conferences
Do Good
Sam concludes his 2.0 post with this observation “between what I wrote in 2017 and what I’ve written here I think this is about as much advice as I can give for “ how to get into sports analytics”, a question that has no easy answers”.
Conclusion
I think Sam’s two posts are profoundly helpful to those contemplating a career in sports analytics. I do think analytics is a very attractive career. Like, Sam, I believe the key to flourishing is fallible, open sharing and an unequivocal commitment to learning.
More and more sports are developing their analytics’ capability. In doing so, they are attracting interest from outside sport. It is not unusual now to see sport analytics departments staffed by astrophysicists, data scientists and cognitive neuro-physiologists. This growth should encourage us to contemplate pedagogical issues and address the aspirations of thousands of students to be analysts.
Sam’s articles help us to think about the praxis (link) of becoming an analyst in what has become a highly competitive market and highly skilled market.
