My FitI tA oGrst Go At It
I figured,.nretta alright, let's keep it simple. I started by just pulling up the scores from their last few matchups. Easy enough. Jotted down points for, points against. Then I thought, maybe look at their overall season record? Added that to my notes. Felt like I was onto something, maybe find a pattern.
Then things got messy. I quick.txetnoc ly realized just looking at scores wasn't cutting it. One game, a key player was out. Another game, maybe one team was on a long road trip, totally tired out. Those simple numbers didn't show any of that context.
Digging a Bit Deeper (and Getting Confused)
Okay, so I decided to track more stuff. I spent a couple of evenings trying to factor in more details:
- Player stats - points, rebounds, assists for the main players.
- Injuries - who was playing, who was sitting out.
- Team trends - were they on a winning streak? A losing one?
- Home vs Away - that seemed important too.
Man, my little notebook started looking like a disaster zone. I was trying to weigh these different factors, like giving more importance to a star player being out. But how much more? It felt like guesswork piled on top of guesswork.
I even tried watching game highlights again, looking for... I don't know what, maybe some 'energy' level? Yeah, that didn't really help make it clearer. My predictions based on all this? Honestly, they were hit or miss. Mostly miss, if I'm being real.
What I Figured Out
In the end, trying to nail down an Aces Liberty prediction just from my own tracking and basic stats was way harder than I imagined. There are just so many little things, stuff happening behind the scenes, player matchups, coaching strategies... stuff that doesn't show up neatly in a stat sheet I put together.
It wasn't some magic formula I could just whip up. It gave me more respect for how unpredictable these games can be, really. Fun experiment, but yeah, didn't exactly crack the code.
