We speak to Michael Najdan who has a Masters in Performance Analysis and has been involved in various roles in cricket over the last decade. He’s been the Performance Analyst for Kent in the UK since 2014 and talks with us about the evolution of data & tech in cricket and how T20 has brought even more innovation to the ‘gentleman’s game’.
Tell us about your background
After completing a degree in Business I wasn’t sure what sort of career to pursue but I’d always had a strong interest in sport and particularly sports data. Around this time sports analytics was starting to grow, with companies like OPTA and Prozone emerging and professional teams starting to build their analysis departments. I completed a masters degree in Performance Analysis, which included completing a piece of research on T20 cricket for Durham CCC, that was subsequently published in the International Journal of Performance Analysis in Sport.
From there I worked for a number of sports teams in the North East of England, then onto OPTA as their cricket department was starting to grow. This included a trip to India to work as an analyst for ESPN Star Sports on their coverage of the India-England test series in 2012, providing viewers with new and advanced data insights. While working for a company like OPTA provided a varied experience of sports analytics I was keen to work in professional sport so was delighted to accept the role of Performance Analyst with Kent County Cricket Club when the opportunity arose in 2014 and I’ve worked at the club since then.
How has the sport science & analytics industry evolved over the last 8-10 years?
Certainly 10 years ago few, if any, county teams had full time analysts. Numbers have grown steadily in the years I have been involved to the point where most teams have full time analysts and a number of intern students. 10 years ago there was an emphasis more on the video side of analysis, filming, coding and producing videos of key events from a match or practice for players and coaches. Over the last few years data science, analysis and visualisation has grown in importance and become a key aspect of the work analysts complete.
You’ve worked for some well known organisations like Opta & ESPN Star Sports. Tell us about some of your most exciting stories from earlier on in your career?
Working for ESPN was an exciting new venture at the time, providing more detailed and advanced data insights than televised cricket had previously offered. Moving on from looking at basic runs and averages to areas such as false shot percentage, attack and defence percentage and match-ups against different types of bowlers. I worked closely with Simon Hughes providing the data analysis to supplement his sections at breaks, pre and post-match. One piece of analysis that stands out was when I looked at how many run outs each commentator had been involved in during their Test career and what percentage of times their partner had been dismissed.
You’ve been with Kent since 2014. Tell us about your key responsibilities there?
Home first XI matches are all coded and uploaded so the setup of cameras and the coding of those matches is the first responsibility of an analyst. On non-match days I prepare a detailed pre-match dossier on all opponents providing the statistical information to better inform decision-making and highlighting their strengths and weaknesses. We also look back at data from previous performances to identify areas to improve in future matches. During the winter there is a greater opportunity to analyse our own performance in different formats and look at how we have performed individually and collectively in key areas compared to our peers. We use tools such as Tableau and R to analyse and review our own performance and competition trends.
In one of the first T20 matches I was involved with, while preparing the pre-match dossier we noticed several of the opposition batsmen had much reduced strike rates against a certain type of bowler. We subsequently used this strategy and it proved to be successful on this occasion.
How has T20 and the introduction of modern technology changed the way things are done in cricket?
T20 has leant itself to analysis, both video and data, more than other formats of the game and we spend a greater time looking at the opposition and their data in T20 cricket attempting to gain a competitive advantage. It’s obviously important not to overload players with a large amount of data and a key part of the analyst’s role is to filter the most relevant and essential information from the all the data available. It has also changed other aspects of sports science, with a greater emphasis on fitness and strength for power hitting.
In terms of technology, we have more and more access to footage and data from players all around the UK and globally since I first started. We are able to identify the best players in franchise cricket in particular key areas from 1 or several competitions around the world or look at 2nd XI cricket to see how players are developing. Additionally, tools like Tableau have allowed a greater level of analysis than was previously possible. Our matches are also now live streamed which has allowed the club to engage with supporters that may be unable to attend matches, particularly with a large amount of cricket played during the week.
We spoke about the work you’ve been doing with Tableau & more recently some self-learning with R. How have you found the journey familiarising yourself with these tools?
Yeah I’ve been learning R on and off for the last year or so but obviously it’s quite difficult to make much progress while working full-time, particularly during a busy cricket season! The last couple of months have provided me with the opportunity to up-skill and spend some time learning more about R and how it could be used to benefit the work I complete in the future. I am making progress, however, there is a still a large amount to learn and I’m just scratching the surface of what it is capable of at the moment!
Data visualisation is the key to getting buy in. Any cool visualisations you can share for us less technical folk?
Yeah certainly! Some coaches and players prefer to be given actual data figures but visualising the data can be an effective way to present certain data and get buy in. For example, it’s insightful for players to view where they rank in a particular area of the game to their peers on a scatter diagram and can raise further questions that may not have arisen with absolute values. I’m generally uploading some of the visualisations to my RPubs page.
What has been the biggest win you’ve had with your analysis? Any particular tip you’ve passed on to a player or coach that’s worked out straight away?
In one of the first T20 matches I was involved with, while preparing the pre-match dossier we noticed several of the opposition batsmen had much reduced strike rates against a certain type of bowler. We subsequently used this strategy and it proved to be successful on this occasion. In general, the biggest win has been players and coaches asking for, and using data more and more, either tactically or from a development perspective.
You mentioned you’re personally a big cricket and football fan. What do you think are the keys to success in the sports science & performance analysis industries in a post-covid world?
It’s a good question! I don’t think anyone knows exactly how sport and sports science and analysis will look in a post-covid world. In a sport like football I would anticipate data analysis and science becoming even more important in areas such as recruitment. Teams that perhaps haven’t previously looked at the most efficient ways to recruit players may have to change their approach. Longer term modelling, AI and machine-learning will become more and more important in sports science and analysis.