Agree 100%.
But why coaches need good statistical analysts on their staff is lost on many people. It has to do with the quality and relevance of the data. Analytics is data driven, but which statistical measures are relevant, and which are not. For example, when used in personnel selection:
- Arm length is correlated to height, and arm length is very statistically relevant when projecting success for pass rushers and offensive tackles.
- 40 time speed is very relevant for wide receivers, and defensive backs, but almost a non-factor in evaluating quarterbacks.
- A good 3-cone time may be more important for some positions than others.
- Bench press repetitions is not very relevant to how successful a running back will be.
- No one wants to draft a 250 lb. offensive lineman, no matter how agile he may be, or how skilled he may be at using leverage.
The job of the data analyst is not just to crunch the numbers. It is to figure out which numbers are important to crunch, and what data should be left out of the equation. It is not intuitively obvious to the casual observer why a particular statistic doesn't matter, and should be excluded from consideration.
I remember back in 1998, I decided to create my own system for power ranking teams in the NFL during the season. The difficulty was in determining which statistics to measure. It took me 6 years to finally develop a system that was reasonably accurate. That only happened when I dropped all statistics from special teams, which turn out to be only marginally important, and added in penalty yardage for and against a team. Then "suddenly", I had a formula which used 12 basic statistical measures and was > 90% accurate when predicting which teams would make the playoffs. Back in the 2013 season, I was living in Denver, when the Broncos ended up playing the Seahawks in the Super Bowl. A lot of my co-workers asked me who I thought would win. Statistically, it wasn't even close. The Seahawks were far superior to the Broncos, and they proved it in the Super Bowl, much to the chagrin of my neighbors and co-workers in Denver.
I published my own Power Rankings each year on the old DC.com website from 2004 - 2017 for 14 straight years. A lot of people wanted to argue the numbers every season, but after spending 6 years from 1998 - 2003 figuring out what the right numbers to use were, my system consistently out-performed people's gut feelings. The only real glitch was I never could figure out how to incorporate special teams data. One year, the Chargers had both the #1 offense and #1 defense, and yet missed the playoffs due to atrocious special teams play - which just goes to show you that even the best system is not 100% accurate.
Bottom Line: knowing which data to use is highly important. That's why many people "don't trust the numbers." It is because they don't know how to figure out which numbers matter, and what data is irrelevant.