Arbusers

Did anyone watch that event?
Days ago, odds computed by myself in Syracuse's favor were much bigger, than offered in the market (circa 1,20 to 1,26 across the agencies). Didn't touch that match at all, due to several reasons - no video signal, lack of the desired odds, the big margin here. The risk of that event (knowing the dispersion at that league) was big at the published odds level. Eventually, very hard win for the host after Extra Time played.
Later, in the post-analysis, based upon published available stats and the match data, some of my initial probabilities were confirmed at first sight, but if anyone watched that event, may comment.
At the first sight, the data implied an equal level game for both the teams, no big supremacy for the so-called Favorite? Or some tactics games and instructions were given from the Coaches? Or good/bad implemented things by the players? Or some other things?
Thanks.

I am noticing that you are analysing a rather big number of markets and I am wondering if that is healthy for your business. Usually I would advise people to stay within their circle of competence, but seems your is much bigger. I mean, from Aris, Volos, to Syracuse, there is a big distance. Don't you think?

Hello, Arbusers,

Thank you for your opinion and for your kind advice.
Let me explain.

NCAA basketball is very tough, but sometimes there are good opportunities there. In that game, I didn't participate, simply ask if someone watched and analyzed. Can't believe here are not writing US citizens, loving that basketball game.
When the position is based upon information and own perception, the probability to build some base is bigger than simply thinking upon the match like 1, X or 2 without argument. And when the player is lovin' some games, plus long time observations, in my opinion, the perspective is to be qualified and informed much more than people watchin' 1 or 2 events in a month.

@ Arbusers, especially for that event, in pre-analysis, previous strikes for both the teams, and most recent series and matches, let's say 5, 10, 15 or all the data. The EMA-like analysis gives, let's say much more weight on the recent data than older. For some reason, I have triggered odds for the Orange team such as circa 1.5 (100, divided by the probabilities, formed by my perception) or something, if these current conditions and these past recent results are similar conditions for the given event. But I personally prefer to watch video signal when possible, due to the possibility of blindly typed statistics data (RAW data) to trap the player in a big pitfall. Blindly applied technical analysis in leagues like NCAA is dreadful. Don't know if the Coach of the better team orders the slow pace, or injury arise, or the underdog team is risking in va-banque style in a given quarter, or other hundreds of things happened. Never accepted only data, without rationale behind them. For instance, yesterday the Olympiacos team was awakened at the end of the match vs Olimpia Milan, but what was the Risk/Reward ratio, provided that almost similar case happened at home recently, vs Crvena Zvezda Belgrade, and that case was wasted due to poor time management by coach Bartzokas?

Brick by brick, year after year, hope one day to build a solid system for the stats and fundamental model, generating better triggers for entry/exit points. That's not easy for me at all.
I personally experiment, forming new data ratios and graphics, alongside traditional data, given in the NBA and other sports. Most of these new columns rows and curves are simply unacceptable data, short series of matches rejected that. Other kinds of data stay much longer, before bein' rejected, and other ratios and data aren't rejected yet. Hopefully, among these data in the long haul, to be accepted most value of them, givin' some value. At the moment, a few kinds of data are not rejected as valuable, but these aren't long time tested, yet. Therefore their use is not proven and may be dangerous (or on the contrary, they're hidden jewels and long-time observations are needed to be accepted.) And another problem, if they are valuable, is how to make the right assessment of that data, provided that they are long time working. And the third problem, when in the future (year, 10 years, or never) these approved and right assessed data will go broke, if they will go broke at all, and must be rejected in the model due to some reason, i.e. the agencies accommodate similars data row model pretty well and therefore these are not valuable for us?
That was mostly for the quantity data. But the fundamental analysis data? Tactics/Coaches philosophies/Pace changes/Implementation by the players/substitutions/owners/distance from the cities/hidden factors and much, much more. And the right weight of every one factor? And much tens of the data, quality and quantity ones, and their ratios and weights, and many more? Many years so far, sometimes seems to me I start again and again. But new things are spotted every time. Always willin' to learn new things:) But after many years, I'm sure, I may return more experience here in that forum. I'm on my way, gainin' some experience.

By the way, if here in the forum are some people, interesting in sport metrics analysis (mostly living in the US and working among the Major Leagues/College leagues there, or simply Statisticians or Sportal Journalists there), they may write some opinions in the forum and why not some papers in the Portal. The users of the forum will be very much grateful, and the forum will evolve for sure.

Again, thanks for your advice.