The Brewster

So I’ve been using the BBA/GBC as a very effective writing avoidance crutch for the past day or so, and along the way got tied up in looking at various pitching data. I think I may have even learned a thing or two along the way. Such are the wonders of life and learning.

Anyway, one of the things I may have learned is another way the OOTP engine seems almost kind of pretty good. That is how it’s allocating various kinds of strikes. Specifically, swinging strikes vs. called strikes. I’m not sure. But the data was fun. I used the GBC because with fewer teams the demarcation of data is sometimes a little easier to see, and besides, why not give the GBC something to waste their days on every now and again? In this case, I went to my game log script and pulled data it gathers on every pitch thrown.

Here is the data.

Team	Pitches	Contact	Bunt	Strikes	StrC	StrSw	Foul	Balls	SwStr	Str%	Ball%
Athens	4748	882	11	2890	736	440	821	1858	0.093	0.609	0.391
Buenos Aires	4399	909		2719	733	338	739	1680	0.077	0.618	0.382
Cairo	4474	883	6	2777	696	401	791	1697	0.09	0.621	0.379
Jerusalem	4989	885	1	2986	778	482	840	2003	0.097	0.599	0.401
Johannesburg	4754	914	2	2971	798	477	780	1783	0.1	0.625	0.375
London	4759	930	4	3016	760	479	843	1743	0.101	0.634	0.366
Moscow	4764	926	10	2982	754	420	872	1782	0.088	0.626	0.374
Sao Paulo	4868	969	3	3028	788	441	827	1840	0.091	0.622	0.378
Sydney	4581	891	4	2805	744	415	751	1776	0.091	0.612	0.388
Tokyo	4365	809	3	2768	700	454	802	1597	0.104	0.634	0.366
***
League	46701	8998	44	28942	7487	4347	8066	17759	0.093	0.62	0.38

As always with this kind of information, there’s probably a lot to look at, but in particular I want to focus on the Swinging Strike column.

The first thing to note is that the numbers are a little down relative to MLB, anyway. MLB swinging strike rate is roughly 11%. The first thing I thought was that maybe GBC would be lower due to lesser pitchers/hitters, but that’s not the case. GBC’s swinging strike rate is 9.3%, whereas BBA’s is 9.1%. FWIW, I reported that to our benevolent Devs. We’ll see if anything changes or not. But for now I think it’s a learning that the swinging strike rate of a league, across that whole league, is not specifically driven by the players. But what is driven by the players is probably the allocation of those swinging strikes.

Here's what I mean.

Take a look at Buenos Aires. Their pitchers swinging strike rate is 7.7%, lowest in the league. Moscow is second lowest at 8.8%. I haven’t done a rigorous, big-data statistical breakdown, but now go to those two teams’ pitcher screen in game and scan their Stuff ratings. Then scan other teams’ stuff ratings. It seems to me that the eyeball test says that teams with staffs that carry greater stuff have a strong tendency to register higher on the swinging strike metric. A scan of Tokyo’s roster (10.4% leads the league), supports the motion.

I’m not sure what to do with this from a base gameplay perspective. And, in fact I think it would be a bad idea to suggest that there’s specific gameplay value in that tidbit of academic learning. At least there would be a lot more digging needed to formulate what this information meant when it comes to player evaluation. So, be careful.

But I do think that’s kind of cool.

And it helped me avoid doing anything productive, so it’s got that going for it, too.

I would also expect control to lead to a greater proportion of called strikes. They’re in the zone more and walking less batters.