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JiriHrdina · 12-05-2014, 01:03 PM

I listened to this entire segment today and it underscored, for me, why the analytics community has struggled to get wider buy-in across the fan bases.

The guy came across as smug, dismissive and as a guy who thinks that he’s the smartest guy in the room – and has no patience for anyone with a differing opinion. He reinforced the stereotype of a hockey nerd who doesn’t watch the game.

Now I get it – I understand why these guys are defensive. They get called “geek” and told to step away from the spreadsheet all the time – that must be irritating. He had interesting things to say, but his presentation of that information is poor. Again – it comes off arrogant and dismissive.

Pinder didn’t help by calling those that were objecting to the opinions being raised as being “scared” by the stats.

I thought the timing of the segment was also poor. I got into my car looking forward to listening to the details of a pretty incredible win last night. Instead my entire commute was spent listening to a guy tell me all the reasons why the team I follow sucks. None of the information was new – same stuff – unsustainable, poor possession stats, high shooting percentages.

BLAH BLAH BLAH.

This is a conversation you save for an off-day – not the morning after a great win. You need to have some sense of the emotional pulse of your audience – and when to have the right conversations.

Contrast that with the regular segment Kerr has in the afternoon with a different analytics guy – I can’t recall his name. It is ALWAYS interesting. They don’t focus entirely on the Flames, but touch on them and spend time looking at trends around the league. The analytics guy presents the data he has, and his opinions of what it means – but never comes across as a know it all.

Part of what the analytics community needs to realize is that the data in part should help you figure out the next question to ask – not draw hard and fast absolute conclusions.
So for instance with the Flames they should be saying

“Hmmmm…the underlying numbers don’t match with the success the Flames are having – let’s drill down to try and figure out why”.

Instead the answer is “it’s all luck – this team isn’t very good”.
That’s just not good enough.

12-05-2014, 01:03 PM	#182
JiriHrdina I believe in the Pony Power Join Date: Jul 2003 Exp:	I listened to this entire segment today and it underscored, for me, why the analytics community has struggled to get wider buy-in across the fan bases. The guy came across as smug, dismissive and as a guy who thinks that he’s the smartest guy in the room – and has no patience for anyone with a differing opinion. He reinforced the stereotype of a hockey nerd who doesn’t watch the game. Now I get it – I understand why these guys are defensive. They get called “geek” and told to step away from the spreadsheet all the time – that must be irritating. He had interesting things to say, but his presentation of that information is poor. Again – it comes off arrogant and dismissive. Pinder didn’t help by calling those that were objecting to the opinions being raised as being “scared” by the stats. I thought the timing of the segment was also poor. I got into my car looking forward to listening to the details of a pretty incredible win last night. Instead my entire commute was spent listening to a guy tell me all the reasons why the team I follow sucks. None of the information was new – same stuff – unsustainable, poor possession stats, high shooting percentages. BLAH BLAH BLAH. This is a conversation you save for an off-day – not the morning after a great win. You need to have some sense of the emotional pulse of your audience – and when to have the right conversations. Contrast that with the regular segment Kerr has in the afternoon with a different analytics guy – I can’t recall his name. It is ALWAYS interesting. They don’t focus entirely on the Flames, but touch on them and spend time looking at trends around the league. The analytics guy presents the data he has, and his opinions of what it means – but never comes across as a know it all. Part of what the analytics community needs to realize is that the data in part should help you figure out the next question to ask – not draw hard and fast absolute conclusions. So for instance with the Flames they should be saying “Hmmmm…the underlying numbers don’t match with the success the Flames are having – let’s drill down to try and figure out why”. Instead the answer is “it’s all luck – this team isn’t very good”. That’s just not good enough.