What MLB should learn from other Professional Sports
The biggest mistake all Sports Science programs make
Reverse Engineer Sports Science to win – Learn from CSI
Ironically, the most common error that most sports have made in sports science is the easiest to address and it’s something baseball can easily learn from.
When the sports science trend exploded there was a rush to invest in technology. The logic most adopted was forgivingly understandable: buy technology, invest in sports science, test and measure as much as possible. When errors or outliers were found – especially low numbers such as speed, strength – work harder to improve them.
“The forgivingly understandable error”
However, this was a completely erroneous approach based on one simple oversight – you can’t measure everything, let alone everything that truly matters. Simply increasing numbers doesn’t always make players better either – everything is related.
Teams soon realized a few fundamental challenges.
- They were measuring too much data and hadn’t planned for it
- Many teams didn’t know what data was actually important and what wasn’t
- They realized they were measuring largely physical metrics only
- Many teams had now more data collection to do but hadn’t man power to do it
- Worse still, many hadn’t the inhouse expertise to interpret the data
- Often because these developments evolved without coach involvement initially, getting their buy-in later was much more difficult and many coaches ignored sports science.
- Seeing the trend there was flood by technology companies to sell every kind of product to organizations that hadn’t the inhouse expertise to distinguish marketing from truth.
As you can see, this has led to confusion, vast sums misspent and varied results across the leagues.
I’ve seen this same mistake in every sport from NFL, NCAA, International rugby, Premier League soccer and the NBA. It all sounds fine in theory – but in the real world of the bullpen, where results matter, a pragmatic approach is needed to win.