Running Towards a Healthier Lifestyle with ChatGPT: My Journey to the Half Marathon
16
October
2023
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In my earlier blog, I have talked about nutrition and using ChatGPT as a nutritional guide. However, having a healthy lifestyle isn’t just about eating habits, it’s also about staying active and fit. For me, running became a preferred choice over traditional gym workouts, aligning more with my personal preferences. My father used to be a marathon runner, and I remember cycling with him as he trained for those marathons. Those moments left a lasting impression on me, and I later came to understand and share his passion for the sport. This change in my fitness routine brought along the goal of completing a half marathon in Breda on may 19th 2024, a challenge that requires structured training. In this blog, I will share how ChatGPT is playing an essential role in setting up my training schedule, , incorporating interval training and setting intermediate training goals,
One of the first hurdles I encountered was creating a structured training plan that would prepare me for the half marathon. ChatGPT helped me develop a training routine based on my fitness level, available time, and the specific race date. It took into account factors like gradually increasing distances, rest days, and the importance of cross-training. I was able to run 5 kilometers in 27 minutes and I used this as a baseline in my prompt.
As you can see, the aim is to increase my weekly running distance by 2 km, and on the second day of the week, I would run 1 km less than I did on the first day.
In the second month of my half marathon training journey, ChatGPT recommended incorporating interval training into my schedule. This addition enabled me to further optimize my training and improve my running performance. In addition, interval training helped me prevent training plateaus, since the body tends to adapt to the same workout over time.
I’ve always been really competitive and I’ve found that one of the best ways to motivate myself is by setting ambitious intermediate goals during my training. These goals not only make running more enjoyable and challenging, but also provide a clear way to track my progress. Knowing this, I asked ChatGPT to incorporate this in my training schedule for October. I asked ChatGPT to set the first intermediate goal in week 7 and the second intermediate goal in week 10. I was convinced that I would improve measurably within three weeks.
My journey to a healthier lifestyle through healthier nutrition and running was significantly enriched by the assistance of ChatGPT. It facilitated my training schedule, incorporated interval training and helped me set intermediate goals to keep me on track. I am eager to use ChatGPT as an training assistant for the upcoming months! As I continue to train, I look forward to running the half marathon in Breda.
A new era for the Mountainbike industry
16
October
2022
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When you think about mountain biking, the first thought will probably be about being outside in vast forests mountains and whatever other terrain you dare to cross. You might not immediately think about digital ecosystems and smart parts.
Most mountainbikes designed for heavier use have front and back suspension. More high-end bikes have numerous options to fine tune the specific workings of the suspension. Example of this is the adjustment of the high and low speed compression, high and low speed rebound and the amount of air in the fork. From personal experience adjusting these setting requires a lot of experience and trial and error. Small changes such as different types of terrain or even if the weather is wet or dry require totally different setting. Imagine every time you step on the bike around 10 to 20 minutes of fine tuning.
(FOX Factory, 2022)
However recently the mountainbike industry has seen a shake-up with the introduction of smart components. The example that will be discussed during this article is the LIVEVALVE technology by (FOX Factory, 2022). LIVEVALVE is an electronically controlled suspension system that uses sensors to automatically adjust the suspension settings according to the terrain (FOX Factory, 2022).
LIVEVALVE changes the game as they automatically adapt to the different styles of terrain (FOX Factory, 2022). This saves the rider from adapting suspension settings during a ride and even allows for automatic suspension adjustments during rides.
(FOX Factory, 2022)
(FOX Factory, 2022)
Additionally the LIVEVALVE is connected to an app which allows the user to change suspension settings. This is revolutionary compared to the traditional mechanical dial tuning without any insight.
Implications and predictions
It is hard to predict how these smart components will affect the mountainbike market as a whole. These smart components are still very pricy with LIVEVALVE costing around 3.000-3250 Dollars (Phillips, 2018). Additionally they require batteries that have to be charged (traditionally mountainbikes do not have batteries) which might be an obstacle for some buyers requiring longer off-grid usage or total dependancy during long outdoor trips. One of the major advantage of this LIVEVALVE system is that is lowers the skill-minimum to fine tune the suspension. This will be really helpful for newer or less fanatic mountainbikers. Outside from LIVEVALVE by FOX factory other smart components have also been brought to market with one example being SRAMM AXS which is a smart wireless shifting system for mountainbikes (McCoy, 2019).
It will be interesting to see how many other sports gear companies will also begin to slowly incorporate more and more smart components. Traditionally these companies have competed on the hardware of the products they sell, but now software will also start to be an important factor. It will be interesting too see if these components will also start to work together and if companies will partner up to create ecosystems.
FOX Factory. (2022). LIVEVALVE: Fast-acting automated electronic suspension system. https://www.ridefox.com/content.php?c=livevalve-bike
Philips, M. (2018, September 21). Fox’s electronic live valve suspension will change your rides forever. https://www.bicycling.com/bikes-gear/a22842945/fox-live-valve-review/
McCoy, S. (2019, February 8). SRAM’s AXS system: Why it matters even though you probably can’t afford it. https://gearjunkie.com/biking/sram-xx1-xo1-eagle-axs-mountain-bike-groupset
Data Analytics in Team Sports; Top Performance as a source of revenue!
21
September
2021
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Sports industry is undoubtedly one of the biggest industries in the world. In order to put it in numbers, the sports market reached the amount of 458.8 billion in 2019 but it declined to 388.3 billion in 2020. Sports market is expected to reach a value of 599.9 billion by 2025 and 826 billion by 2030 (The Business Research Company, 2021).
As many of the other industries, the sports industry was largely affected by the COVID-19 outbreak. As mentioned also above, the sports market suffered a 15.4% decline in its value (The Business Research Company, 2021). The main reason why this happened is that the main source of revenue of almost all of the sports associations is their fans. With COVID-19 regulations, fans were not only disallowed from following their favourite teams but they were somehow distanced from the whole concept of supporting and keeping up with the team that they support. Cancellation of games, abstention from action, ban of fans in stadiums, poor athlete performance to abstention or psychological state after consecutive quarantines were some of the most outstanding issues that arose and had the result of making fans more distanced from the teams that they support.
All of the issues mentioned above, stress out the importance of having fans pleased and offer them the best quality of spectacle. Fans that are pleased with their team’s performance will tend to bring more revenue by buying sports equipment related to the team, by paying high prices for getting seats or season tickets for games, by paying to visit the stadium itself or the team’s facilities or by even buying products that are closely related to their teams. Also, most of the time, a bigger fan base will bring greater sponsorship deals to teams and associations. It is not a secret that the more consistently spectaculous a team is, the bigger fan base that it will gain throughout the years. But how can a team be always on top of their performance and attract as many fans as they can, who will eventually lead in bigger revenue levels?
The answer to the previous question is by keeping the performance of the whole team and their players as individuals to the highest levels possible. Data Analytics is a technology which has been established for many years in various industries. Sports is one of the industries that are reportedly really slow in digesting it and applying it to their processes but lately it seems there are multiple improvements at accepting it. Its adoption is in a really immature state yet but tremendous efforts of implementing and establishing it specially in the team’s sports sector are happening.
Let’s take the example of the National Basketball Association (NBA), one of the world’s most marketed sports products. Historically, in basketball there were people who were responsible for noting statistics about players in order to either scout or either improve their in-game performance through coaching. These statistics were mainly held in paper and only classical statistics such as points, attempts, assists etc could be noted by these people. The recent installment of cameras all around the court gives the opportunity for teams to keep much more detailed statistics which can be further analysed by business analytics. These analyses can later be used by machine learning models in order to design winning strategies. Strategies such as planning the most effective defensive plan for top-notch teams or players or the most efficient offensive plays according to the roster’s characteristics and capabilities are some of the examples that can provide a competitive advantage to teams who use such innovative technologies (HBS Digital Initiative, 2020).
One of the key concerns of all the teams is keeping their players well rested so that they can avoid potential injuries. Lately, teams have been selecting data from their players by offering them wearable equipment, by monitoring their sleep patterns or even collecting biological samples from them in order to track their fitness level, their rest levels and even predict their future performance. By analyzing these data, teams are trying to design the most appropriate rest strategies for each of their players. The more tired a player is, the more prone to injury he/she will be. In order to always keep them on top of their fitness so that they can contribute at most during the games, they are applying all these monitoring techniques for collecting relevant data (HBS Digital Initiative, 2020).
Last but not least, data analytics play a major role nowadays in scouting players. Back in the days, scouts would rely their decisions for players in statistics held in paper, by watching them in live action or by highlights found online. With data analytics, statistics can be analyzed in depth, thus providing a clearer and more detailed report about a player, reducing the risk of incorrect decision making. Transfers and contracts offered to players are costing a lot of money to teams and these are two of the most important expenses for a team or association, so taking right decisions in order to attract the most suitable plates for the team in order to achieve consistent performance levels is vital for them (HBS Digital Initiative, 2020).
Of course, the data models that are being analysed are far from perfect at the moment. One parameter that is really hard to take into account and that is difficult to be applied to the data models is athlete’s psychology, not only during a game but also his psychological state throughout the whole time of him/her being a member of a team. Data analysis has changed the way that teams operate but in order to take right decisions they still have to consider the human factor. What can be predicted, though, is that teams who invest and use further new technologies in order to analyse the tremendous amount of data that they can get from their athletes can be ahead of their opponents and build consistency in terms of performance so that they can always be at the top, which naturally attracts more and more fans, thus revenue, as explained in this post.
