Math is more reliable than intuition
Sam considers himself an exception to the rule because of all developers he is the only one that lacks a math or a sciences background. A lesson that he learned very early on is that mathematics is reliable and numbers don't lie. They record data and that data is a goldmine. They can see through the data which cards are more liked, which are more disliked, what colors are more played, what colors are least played and all sorts of statistics to help shape the game. More often than not, the numbers contradict the intuition. He uses the phrase that describes to be standing on the shoulders of giants.
I'd like to comment that statistics is not properly taught at school at all. The sole exception depends on really exceptional teachers at school that know statistics very well. One thing about science in all fields is that it requires data and the data has to be reliable. There is a whole field that is to make sure that the data is reliable because one of the greatest pitfalls of science itself is when the data is unreliable or biased. I can't discuss bias here because it's a broad topic with many books covering it. The point that Sam makes is that intuition is often biased and by relying on statistics we can eliminate the bias. I agree with that.
I'd add that mathematics and statistics are prone to mistakes too. I'm not trying to disprove Sam. Mark Rosewater talks a lot about the emotional aspect of designing cards and emotions are not math. Emotions are the opposite of numbers and rational thinking. I'm trying to say that bias is dangerous and numbers can bring in bias too. For example: there is something called the survival bias, which happens when we make assumptions based on who or what survives something, ignoring the population that didn't survive. One of the dangers of blindly believing in numbers is when the numbers themselves are biased. For example: Suppose that a company is hired to play test a game but that company lies or miscommunicates, running playtests that have only women or players of a certain age group. If you look at the data and think that it represents your target audience when it doesn't, we have a problem. I'm not saying that numbers can lie. What I'm saying is that, sometimes, people can lie and use false or biased data to misguide others. Politics is a great example of this and there are numerous examples regarding companies and governments that lie about diseases, catastrophes and so on.
Be careful with blindly following numbers because they aren't immune to mistakes or lies. To give a quick example: suppose that you are measuring the wind speed at the ground level with a sensor. If you have data from a whole month and some days show winds with speeds of 1000 Km/h, there must be something wrong because no place on Earth has winds with speeds of 1000 Km/h. It can be some error in the sensor, some unexpected interference, some unit error, etc. But our intuition tells that something is wrong with the excessively high wind speed.
