Best Games of the Decade

Check out the Win Probability graphs and play-by-play of your favorite team's biggest comebacks and most exciting games since 2000. An explanation can be found here. Just select a year, a team, or 'any', and start clicking:

Or search for all the games for your favorite team:

May 2, 2009

Epic Bulls-Celtics Series

If you haven’t been paying attention to this series you’re missing one of the most exciting 7-game series ever, even if it’s just the first round.

Going into Thursday night’s game, there were already 3 OT games and 1 last second buzzer-beater game. Then this happened: A 3OT potential elimination game that featured multiple furious comebacks for both teams and ultimately tied the series 3-3 with a 1-point win by Chicago. These two teams are as evenly matched as it gets. They square off for Game 7 tonight at 8.



Here are all 6 games of the series so far.

Compared to basketball or football, the hockey graphs aren't as compelling at first glance, at least during the game. But a quick look at a graph after the game tells a dramatic story you just won’t get with a box score. Below is Thursday night’s Game 1 between Chicago and Vancouver.

5-3? Well, that doesn’t sound terribly exciting. But check out what happened: 3-0 lead held until the third period. With 10 minutes left in the game, another goal, and with 5 min left another to tie it 3-3. Then Vancouver gets the game-winning goal with less than 2 min to go. Then in the final seconds, a garbage goal with the goalie pulled makes it 5-3.


You can check out the beta version of the hockey graphs for today's Caps-Penguins and Blackhawks-Canucks games. Power plays have not been factored in yet, but that's in progress, and it should be ready early next week.

6 comments:

Mark M said...

Out of interest, have you reactively tested the data produced by the graphs to the real-life result to confirm accuracy (i.e. for all games when home team WP is 0.5 at half time, have the home teams won half of those games)?

Brian Burke said...

I don't have enough games to make that meaningful or worthwhile yet.

Mark M said...

Cheers. I guess as the model is built from previous data that it will probably be correct. It's always worth checking though (I'm sure nearly every mathematician has attempted to build a model to use for gambling purposes that's works when using past data but proves useless for future games).

Brian Burke said...

Here is a link to a post on the methodology. The model was originally applied to NCAA games, but this NBA model is based all new data from every game of the last 2 full NBA seasons.

It's an empirical logit regression model based on home court advantage, score difference, and time remaining. Foul bonuses, the possession arrow, and time outs are not factored in.

Ty Willihnganz said...

Terrific work, as always, Brian. Do you set the home court advantage as a constant, or do you adjust it according to each team's home court efficiency differentials? In other words, if one team tends to play better at home, do you take that into account?

Keep up the great work.

Ty Willihnganz

Brian Burke said...

Ty-Thanks. The HCA is a league-wide average.

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