Game Over

I'm sorry to say that I won't be at hoops for a while.

I'll probably pick the blog back up when I return.

Happy hooping in my absence.

Gym Wind Chill -14

Holy crap was it cold in the gym today. Can't tell you how many turnovers there were because all of our hands were so damn cold we couldn't hold onto the ball. There were several new guys/kids - clearly the result of school being out for the cold or Xmas break.

Still managed two courts and fourteen games. Here are the stats...

As you can see, I was 8-0 in no small part to some very good teammates. The 8 wins in a row is my personal record. Here are everyone's stats including each person's longest winning and losing streak.

Here's the Game Winning Shot data. If you haven't seen it before, look up the original GWS post for an explanation. No doubt Steve's thinking about this chart every time his team has 18,19 or 20 points. This chart is only the guys who have played in at least 10 games where I recorded the GWS.

Next time I'm gonna break down W/L by month - there's giant disparity for some of us from one month to the next.

56 - 51

Today in the final game, the score wound up being 56-51. We were going to play to 31, but with the score tied at 25-25 we were invaded by DevilChildren throwing rubber balls on our court. So, we promptly switched courts and decided to start over at 0-0. My team lost in the end, 31-26. So, with the 25-25 score before we switched courts, it was really 56-51. Pretty sweet.

Lots of games and players. Recorded 19 diff games today - missed about 2 or 3. Three new players brings the total since I started keeping track at the end of September to 104 diff players.

Here is how often they have come. First, everyone who has come more than once...



Then, all that have come exactly once...



Anyway, here are today's stats. Wins/Losses/% and your average teammates lifetime win %. You can see that I've highlighted in orange everyone who today had teammates that AVERAGE a 55% or better winning %. That's gigantic. It shows that any day you can play with really strong or really weak players all day. Again, somehow Pride was the benefit of ridiculously good teammates. He's either really lucky or really sly... As you could guess, the people with good teammates all day won a lot of games and are mostly at the top of the day's chart...

Lastly, here are the cumulative stats for everyone with at least 20 games played...

A couple of arbitrary things... There was a team today that the sum of their historic win % totaled 268%. That's the highest one ever. The team was James, Alvin, Steve and Pride. That means the average player on that team wins 67% of the time (268%/4). Zoiks. Of course, they won.

Also, TK now holds the record - set over Dec 3, 5 and 10, by winning 14 straight games during that stretch.

Blogbuster

Today was weird in a bunch of ways. First, I was there at 11:45 and yet I wasn't in the first game. If your read my previous post, you know that almost never happens to me. Then, I wound up on the far court and no one on the first or second court was prepared to record the results of the games. The wind up is that I missed the results for many games today. Some guys that were there for a while, I have for just 1, 2 or 3 games. Bogus. I'll have to figure out a better system on busy days when I'm on the far court to get some help on the other courts. Lastly, the Governor of Illinois called me and told me my bid for the senate seat wasn't high enough and he was selling it to somebody else.

Anyway, here are the new cumulative wins and losses - split into two to make it easier to see when you click on one part...




Here are the updated Adj win % and Power Ratings for guys with 20 games played or more. I simplified the chart a little. The important columns are schd strg (how difficult your opponents and how weak your teammates were), Adj Win % (your win % tweaked to reflect the strength of your opponents and teammates), PR (your Power Rating which is the % of games you have won compared to what you should have won based on your schd strg) and the last column is the overall ranking based on the combo of Adj Win % and PR. If you want to know more about how it's derived, let me know.

When do you show up?

Shad mentioned that he was surprised he was in the first game when he showed up today. That got me thinking that while I don't keep track of when people show up, I do know who is in the first game (team 1 & team 2) and who isn't. So, here's a chart showing how often you have played (days), how often you have been on Team 1, Team 2 & not in the 1st game at all. Also, the last two columns are % of days that you play that you are in the first game and % of days you show that you aren't in the first game.

As you can see, Marvena has come 19 of the 30 days I've tracked and never been in the 1st game. I've been in the first game 27 of the 30 times, but only 10 of the 27 was I on team 1.

James, Don, BK and young Dane don't play a lot, but are always here early when they do.

The Waiting is the Hardest Part

My apologies to Tom Petty for the title.

Had 16 dudes for a few fleeting moments today and then poor Paul (#2) hurt is back. I say poor Paul not because of his hurt back, but because all the crap he caught for bailing when we had 16. It's always hilarious when we try to beg people to stay to get eight. I've seen guys who had to leave near the end slip quickly out the door when there were still 10 or 9 dudes before it got down to 8 so as not to be the bad guy who kills the day.

Anyway, here are today's stats, not lots of games, but surely lots of waiting.. The last columnn is the average historical winning % of the players on your team today (not including yourself, of course). Jack had lots of help.








Had the opportunity (because of only one game going) to keep team shooting stats in a game...



It was Nate, Shad, Luke and Keith against Tony, Gary, Sean #2 and Jason.



Nate's team won a squeaker 21-18.



Nate's team shot 10/21 overall (47.6%). 9/18 from two point range and 1/3 on three pointers.



Tony's team shot 8/20 overall (40.0%). 6/13 inside the arc and 2/7 from downtown.



It was interesting watching Nate's team not even attempt a three 'til late in the game - contrary to the normal noon hoops mantra of "Heave it up".



Here are the cum stats for guys with at least 20 games...

Inhospitable Hosts

There were two new guys today, Jeremy and David (#2) (not the tall David). As hosts and elders of noon hoops, we did not welcome them very nicely. I know this for sure, because I was their teammate all day. The beatings and slaughters were handed out to our team one after the other. David (#2) went 0-4, Jeremy 0-9, I managed to win one early and went 1-9. Quite a turnaround from my 7-1 earlier in the week. To quote Die Hard, "Welcome to the party, pal."

Oh! Before I forget, make sure to check out video from Friday night's Celtics/Blazers game if you haven't yet. Big Baby Davis lived up to his name. He was weeping like a baby on the sideline. It was ludicrous. Apparently he got admonished in the huddle by Garnett and Doc Rivers and then he sat on the bench and start wailing like a kid who lost his blankie. Then he's sitting on the bench a few minutes later and tears were streaming down his face. Zoiks.

Anyway, back to the show... Here are today's results. TK and Nate played together some today and did well...

Here are the cumulative stats for guys with at least 20 games (welcome Sean to the club). They are sorted by games played. I could tell you that's because lots of guys ask how many they've played, but it's really sorted this way so that I could be first.

Here are some random observations...

Today we had a team that had the highest sum of their winning %s we've seen in over a month. It was Alvin (64%), Keith (51%), Luke (67%) and TK (66%) for a total of 248%. They won, of course.

It's been almost 80 games since a team with a summed win % under 180 has won a game. That game was Dane 35, Erik 42, Marvena 49 and myself 43. No need to embarrass the people we beat as big underdogs...

Don has hit the GWS in 55% of the games that his team has won. Next highest for someone who plays a lot is Luke with the GWS in 43% of the games that his team has won.

Noon Hoops BCS Power Rankings

So the data set is still small (statiscally speaking), but it's cool to look at different comparisons. For the first PR (a few posts ago) I took your win % and divided it by what your win % should have been based on your teammates and opponents. If your actual win % were equal to your predicted win %, your PR would be 100%. More means you have been better than average, less means not as good as average.

Now, I tried two other methods. Basically, without boring you with the math, I took your opponent's and teammate's win % and used the data to adjust your winning % up or down so that now you have an adjusted win %. So, 50% would mean you have been exactly average. I used this method for the two new versions called "adjusted win % 1" and 'adjusted win % 2". The only diff between 1 and 2 is that for adj win % 2, the opponents and teammates have more emphasis in the adjustment.

So, in the end, of course all the rankings are somewhat similar. However, like the BCS in College Football, there are some differences. So, on the chart I show your rank in each of the 3 ratings systems (Adj win % 1, Adj win % 2 and Power Ratings) and then the last column is the overall composite of the three to determine the final rankings.

Knock yourselves out... (only dudes with 20+ games)...

The first 3 columns are games played, Actual win % and strength of schedule (negative being more difficult, positive being easier)...

Medical Breakthrough

Saw a pamphlet today on sprained ankles. They had suggestions on how to avoid sprained ankles. One of the suggestions was to "Be careul when walking or running on rough ground to avoid tripping." Brilliant.

Ryan and Mike (#3) Trample

Ryan showed up today for the first time since I've been blogging. Missed all those moves and especially those rainbow 3s. He and his buddy Mike - that's Mike #3 on the stats - stepped on everyone's neck as they played together all day and went 7-0.

Here are today's stats...



Here are everyone's cumulative stats, including your longest personal winning and losing streaks...




Finally, here's the Game Winning Shot (GWS) data. If you don't know how to read it, look at the GWS post from last month or just ask me at hoops.

Power Ratings I

Time for power ratings. The theory of the win/loss %s is that after a long period of time, everyone will play with a random group of players and all the teammates and opponents will be evenly distributed. Thus, your personal win % would be representative of how you compare to the other players. The problem is that it will take a long time before there is true parity in the teammates and opponents everyone plays with. Any given week or month you could have a very good or very bad run of players in your games (as well as good or bad runs of your own performance). The new answer is Power Ratings.

With PR (Power Ratings) I actually analyze all the games you have played and look at who your teammates and opponents were to see how they compared to the average. If you play with guys who usually win, you should win more often than not. On the other hand, if you face tough teams more often than average, that would negatively impact your chances of winning.

So, here is my first PR rankings.

The columns are:

1. Whom

2. Games

3. Win % (Actual)

4. Average Team (the average of the sum of the win % of the 3 teammates you played with... 150% is overall average)

5. Average Opponent (the average of the sum of the win % of the 4 opponents you played against ... 200% is the overall average)

6. Schd Strg - Strength of Schedule - subtracting the opponents from your team (with 50% for you) - 0% means you have played with and against completely average teams overall. Negative means tougher schd, positive means easier.

7. Pred win% - This is what your win % would be with those players if you were an exactly average player

8. Power Rating - your win % divided by your predicted win % - 100% means you've performed exactly average.

This chart has all kinds of crunched numbers in it. I'm gonna show the chart sorted a couple of ways to highlight a couple of points. This first version (above) is sorted by difficulty of schedule. I have taken the sum of your 3 teammates win % in all your games and taken the sum of your 4 opponent's win % in all the games also. If everyone was average, your 3 teammates would add up to 150% (50% each) and your 4 opponents would add up to 200%. So, if your opponents average more than 200%, you have faced teams harder than average. Also, if your teammates add up to less than 150%, you teammates have been worse than average. So, I have calculated the % of games you should have won (if you were exactly average) based on these numbers.

So, if you look at the chart, Tony's average team in all his games was only 146%, so if he were average, his team total would have been 196%. On the other hand, his opponents average team is a whopping 209% (that is huge, statistically speaking). So in the average game Tony has played, he has been 13% underdogs. As 13% underdogs, you would only expect them (if Tony were average) to win 39% of the time - based on the historical data. So, while Tony only has a 37% win percentage, that's not nearly as bad when you consider that with his teammates and against his opponents, he should have only won 39% anyway.

Other guys at the top of this chart who have been cursed by tough games are Ray, Sam, Shad & Gary. On the other side of the spectrum, are the guys who have had the biggest advantage in the games they've played. Good teammates and weak opponents. The runaway benefactor of being on good teams is Pride. Pride's 27 teams have averaged 172% (57.3% for each of 3 teammates). That's ridiculous (that's like having Steve, Nate and BK as your teammates - ON AVERAGE). He's only played a few days and played many games with James, BK, etc. His 4 opponents have averaged 199%. So, 172% + 50% for him if he were average, results in his teams being a 23% favorite (on average) in all his games. A 23% favorite wins 69% of the time at noon hoops. So, actually, Pride's 63% winning % isn't unexpected. Other guys with easy games on average have been James, Steve, Jack & Luke.

So, now that I know everyone's teammates and opponents, and I know how to translate team favorite percentages into predicted winnning percentages, I came up with the PR. It is simply your winning % divided by what your winning % should be based on your teammates and opponents. So, if you have won 54% and you should have won 54%, you are 54/54 or 100%. 100% theortically means you have performed exactly on average. Better than 100% means you've won more than you should have and less than 100% means you've won less.

That's a lot of words, if you have any questions, ask or email me.

So, here is the same chart sorted by Power Rating...

Of course, functionally what happened is that players with tough strength of schd are higher in the PR than they were when just looking at their win %. Conversely, guys who have played with better teams moved down the ladder in relation to their win %. I would predict that in the future, adding the power ratings together for a team will be a far greater predictor of the winners than just adding their winning percentages.

The bottom line is that 130% PR means that James and Anthony are personally winning 30% more of their games than the average player would with their teammates and opponents. Myself, at 88%, means that I win 12% less than an average noon hoops player would with my teammates and opponents so far. Crap.

I'll have today's stats later (these charts don't include today's stats).

I Rule

Short on time today, but wanted to get some results posted.

Yesterday we got in 11 games. For a while we had the dreaded 15 players and there was a lot of sitting out. Anywho, I wound up on top of the heap with a 7-1 record. Which brings me to another point... I'm guessing that there is a correlation between how many wins someone had on a certain day and how interested they are in checking the blog. It's just a little less fun to see the numbers in black and white when your winning % is below the Mason-Dixon line.

Here are today's stats...





Here are everyone's stats with at least 20 games played...





Obviously, 20 isn't a lot of games for statistical significance. So I have started looking at power rankings. My friend Carl (from 40+ hoops on Tues and Thurs - he calls it "Legends", I call it "Geezers") suggested a rating system that takes into account the winning %s of your teammates and appropriately compares and adjusts your rating overall. If you were lucky enough to play with Luke, Alvin and Steve like I was today, you should be more likely to win than not. So, to that end, I'm analyzing a few different formulas to have adjusted winning percentages that would be normalized by the rest of who was on your team. You'll be surprised how good (on average) a few guy's teams have been, and conversely, a few poor souls in their games so far have been burdened with very weak teams and so they aren't as bad as their winning % might imply.

But that's next time.

See you tomorrow.