## Thursday, June 21, 2012

### Homecourt and rest time advantage

In a previous post, I looked at the true impact of homecourt advantage in the NBA, for the league in general and for each individual team. The model was simple, only considering whether the game was at home or away.

The main take-away was that playing at home bumped your probability of winning by almost 20 percentage points, from 40% to 60%. Quite a significant jump, although not every team observed the same jump.

I did however feel that the model was a little over-simplistic in ignoring another phenomenon which could impact a team's performance: rest time between games. Especially over the 2011-2012 condensed season with certain teams playing back-to-back-to-back games, one can definitely wonder how rest days come into play. If a team is playing on the road, can the fact that they have had three days of rest as opposed to their opponents back-to-back games mitigate the opponent's home court advantage?

The data and methodology are almost identical to the post I mentioned earlier: I looked at all 2009-201 and 2010-2011 games, and for each match-up looked at which team played at home and how many days of rest each team had.

Since we are now looking at multiple variables instead of just the homecourt impact, I will only provide the breakdown of results for the league in general, providing them for each team would just take up too much space.

Impact of rest days

The following table provides the victory probability based on where the game is played and the number of rest days for both teams.

Team A at home Rest days (Team A) Rest days (Team B) Win probability
Yes 1 1 59.1%
No 1 1 40.9%
Yes 2 1 65.2%
No 2 1 47.4%
Yes 3+ 1 62.6%
No 3+ 1 44.6%
Yes 1 2 52.6%
No 1 2 34.8%
Yes 2 2 59.1%
No 2 2 40.9%
Yes 3+ 2 56.4%
No 3+ 2 38.3%
Yes 1 3+ 55.4%
No 1 3+ 37.4%
Yes 2 3+ 61.7%
No 2 3+ 43.6%
Yes 3+ 3+ 59.1%
No 3+ 3+ 40.9%

Some interesting highlights are that:
• independently of the number of rest days each team has had the difference homecourt advantage is always around 17-18%
• the homecourt effect is much more predominant than the number of rest days: even in the best case scenario, the win probability on the road is 47.4%, so essentially a +7% percentage uplift due to rest days, as opposed to the +20% we saw in the previous post for the homecourt advantage impact.
• it turns out that resting 2 days improves probability of victory compared to one day only, and three or more days is also more beneficial than one day only, two days is actually preferable to 3 or more days. This is also a debate that comes around often especially during playoff time, where one team comes out of a game 7 to meet a team that finished a sweep over a week before. Is too much rest a bad thing? From this data it does appear that 2 days provides the optimal balance between hitting your stride while you're hot and resting your sore legs.

Team's optimal rest days

What is true for the league isn't necessarily true for individual teams. I wanted to check if all teams preferred to rest 2 days instead of 1 or 3+ days. Were younger teams eager to have back-to-back games? Were older teams dreadful of tight schedules?

Team Significant Optimal rest days
NBA Yes 2
ATL Yes 2
BOS No 3
CHA Yes 2
CHI Yes 2
CLE No 2
DAL No 3
DEN Yes 3
DET Yes 3
GSW Yes 1
HOU No 2
IND Yes 2
LAC Yes 2
LAL Yes 1
MEM Yes 2
MIA No 2
MIL Yes 1
MIN Yes 1
NJN Yes 2
NOH Yes 3
NYK No 3
OKC No 3
ORL No 2
PHI No 2
PHO Yes 3
POR Yes 1
SAC No 1
SAS No 2
TOR Yes 3
UTA No 3
WAS Yes 3

Upon close inspection there does not seem to be any strong correlation between the team's age and the preferred number of rest days. Sure Boston is an old team preferring over three days and Golden State is one of the youngest team performing best on back-to-back games, but the Lakers are an old team also preferring back-to-back teams and the Wizards are a young team with best odds after 3+ days of rest.

To conclude, while rest days do influence performance in different ways for different teams, homecourt advantage remains the most impactful variable for outcome prediction of a game.

## Monday, June 11, 2012

### Thunder VS Heat: Stormy match-up

Now that the final two final contenders, it's time for the final predictions of the 2012 NBA season!

On Sekou Smith's Hang Time Blog the experts favor Oklahoma City 5 votes to 1, but what do the stats say?

The same model that was used to correctly predict the Thunder in 5 against the Lakers, and had slightly favored the Spurs in 7 over the Thunder in 6, gives a small advantage to OKC given its track record and homecourt advantage, but the margin is extremely close:

Winner Num games Probability
OKC 4 6.4%
MIA 4 6.0%
OKC 5 13.8%
MIA 5 11.3%
OKC 6 15.0%
MIA 6 16.3%
OKC 7 17.0%
MIA 7 14.4%

So if I had to put my money down, it would be for the Thunder in 7 as 3 NBA.com experts claimed.
But be careful, Miami in 6 is a very close possibility!

## Saturday, June 9, 2012

### Is Dexter getting better?

My latest entries have mostly been basketball-focused but the highly anticipated playoff matchups are to be blamed for that!

So after my post on the Johnny Depp - Tim Burton collaboration, I would like to take a stab at tracking the evolution of TV series. I think there are a broad type of questions that can be considered, such as:

How does the rating of individual episodes evolve throughout the course of TV series lifetime? Are there really "good" and "bad" seasons? Do TV series get cancel when the ratings go down by too much? Is there a common threshold? Do all seasons have high-rated cliffhangers at the end of the season?

Data

Similarly to the Johnny Depp analysis, I will be extracting my data from IMDB. To start off, I will focus on one particular TV series (and personal favorites): Dexter.

Plot

Let us plot the evolution of the individual episode ratings by "time":
Two main insights stand out:
• there appears to be a "seasonal" pattern within each season:
- the ratings either stay flat or go down in the first few episodes
- the ratings then shoot upwards during the second half of the season
• after 5 seasons of overall similar quality, it appears that the last season has not performed as well. For the first time in over 5 years ratings dropped before 8.0, and even the strong season finale was the lowest-rated finales.
If we compare the distribution of season 6's ratings with those of all prior seasons, the difference jumps out:
The best season 6 episode has a rating barely greater than the median rating of all past seasons!

I will start looking at other TV series and see if an overall low-rated season is the beginning of the end (hopefully not!). Do networks quickly panic and cancel shows as soon as they start dropping in overall quality?