As you know, I’m a master pattern recognizer who excels at spotting patterns that may form in sports. Recently, I noticed a possible forming pattern in the NBA where teams that play back-to-back games in certain scenarios tend to go Under the total at the end of the season when they are tired.
A few days ago, I shared with you my findings on the above hypothesis based on the last 3 years of the NBA. But that wasn’t enough. I needed more data. I’ve been digging deep into the stat sheets to discover whether there is further merit to this strategy. And today, I’m going to share my new findings with you in this 2nd part of my writeup.
Here’s the NBA angle I researched:
- The game must be played on February 1st or after. Reasoning: February is considered a month toward the end of the season where teams tend to start showing fatigue. This affects how many points are scored in the game.
- The team must be playing back-to-back games. This means they must play 2 consecutive games without a rest day. Reasoning: At a time near the end of the season when teams are already tired, the fatigue effect is magnified further when a team is forced to play two consecutive games in a row without any day of rest. This can affect how many points are scored in the 2nd game.
Research is now fully conducted and tested for the last 6 years (in part 1, we only tested for the last 3 years)
The hypothesis is that when teams are tired, they tend to slow the pace of the game down and score less points. Therefore, the smart bet to take is assumed to be on the Under the Total. Let’s see if this hypothesis holds true. Here is the Over/Under the Total record for the last 6 years of NBA (since the 2012 NBA season) on the 2nd game of a back-to-back series starting in February or later:
424 Overs – 465 Unders
While games have gone Under 52.3% of the time, the gap here is not statistically significant enough to conclude a real betting advantage. The key win rate number to hit is 52.4% in order to break even when betting on sports, assuming that the odds on your wagers are all -110.
Therefore, our hypothesis needed further polishing. This is typically done by adding filters that can help refine a smarter betting strategy. First, I wanted to see what happens if the back-to-back series was played in the order of Home-Home, Home-Road, Road-Home, and Road-Road. What I wanted to see is whether fatigue issues can be further affected from traveling factors.
Below are the results of my findings. The records below are written in Over-Under format. For example, Home-Home: 35-45 means that when a team plays two back-to-back home games, the 2nd game goes Over 35 times and Under 45 times:
The home-home and home-road combinations here both yield a winning percentage of over 56%. That’s well over the target profitability mark. This is something to keep a note of, as it seems to suggest that when the first game of a back-to-back series is played at home, teams might be more likely to go Under in the 2nd game. This would need further research into previous years to confirm how well the strategy holds up.
I continued to dig deeper. What happens if the team lost the previous game, or won the previous game? Would their victory or loss in the 1st game of a back-to-back series have any statistically significant effect on their motivation level to play faster or slower-paced in the 2nd game? Here are my findings, again written in the Over-Under format:
If the team lost the previous game: 238-237
If the team won the previous game: 186-228
The results indicate that teams tend to slow down their pace more often after they’ve won the previous game than if they had lost. In these cases, teams would go Under more than 55% of the time on the 2nd game of the back-to-back.
I continued to research further. What if the team went Over in the 1st game? What if they went Under? How did that affect their scoring in the 2nd game? Here are the results, again in the Over/Under format:
If the team went Over in the 1st game of the back-to-back: 195-227
If the team went Under in the 1st game of the back-to-back: 226-235
Here, it looks like when teams go Over in the 1st game of a back-to-back series, they tend to slow down their pace and go Under in the 2nd game. The Under on this angle here enjoyed a 53.8% win rate in the last 6 years. Fatigue issues may be the most likely factor to cause this effect.
In part 1, I reasoned that the 2nd game of a back-to-back series after February tend to go Under after they have gone Over in the 1st game because of the following 3 factors:
NBA Teams are tired starting February when the season is nearing its end.
An NBA team becomes further fatigued when they are forced to play back-to-back games this late in the season at a time when they are already tired.
If an NBA team played fast paced resulting in an Over the Total in the 1st game of a back-to-back series, then they may become even more fatigued in the 2nd game, thus resulting in an abnormally high amount of Unders in the 2nd game.
But I still wanted more. What happened if teams had over-performed or under-performed in the 1st game? Here are the definitions I use for over-performing and under-performing:
Over-perform: The team not only won the 1st game, but also won against the spread.
Under-perform: The team not only lost the 1st game, but also lost against the spread.
Here are my findings on the Over-Under results in back-to-back series after February if teams would over-perform or under-perform in the 1st game:
If team under-performed the 1st game (lost the game PLUS lost ATS): 198-184
If team over-performed the 1st game (won the game PLUS won ATS): 149-183
The record in the last 6 years shows that if teams over-performed the 1st game (won the game PLUS won ATS), they’d end up going Under 55.12% of the time in the 2nd game! Fatigue issues is the most likely cause here that contribute to this effect.
I still wanted more. What happened if teams would over-perform AND also go Over in the 1st game? And what happened if teams would under-perform AND go Under in the 1st game? How did that affect their scoring on the 2nd game of a back-to-back series after February? Here are my findings:
- If team team under-performed AND also went Under the total in the 1st game (lost the game + lost ATS + went Under the total): 112-91 (55.17% win rate)
- If team over-performed AND also went Over the total in the 1st game (won the game + won ATS + went Over the total): 68-88 (56.41% win rate)
These seem to be the most promising data yet. It looks like when teams under-perform and also went under in the 1st game, then they’re more likely to bounce back and go over in the 2nd game. Likewise, when teams would over-perform and also went over in the 1st game, they’re more likely to bounce back and go Under in the 2nd game. Fatigue issue may be the most likely cause here. Both of these betting strategies produced well above the 52.4% key win rate target for profitability.
I believe this is promising, but I’m still far from making any conclusions. It is worth looking into, and I will continue to dig deeper by back-testing this angle far beyond just the last 6 years to see how it continues to hold up. In my upcoming part 3 of this research, I will continue testing these hypotheses further into the last 10 years. I’ll share with you my findings as soon as I have them.
For now, the hypothesis based on the last 6 years of NBA research is that: When an NBA team over-performed and also went over the total in the 1st game of a back-to-back series starting in February, then the smart bet to take is on the Under the total in the 2nd game. The most likely reason to explain the merit of this strategy is that teams get tired.
Click here to see part of my research: Part 1: Do NBA Teams Tend To Go Over Or Under At End Of Season?
Click here to see part of my research: Part 2: Do NBA Teams Tend To Go Over Or Under At End Of Season?
Click here to see part of my research: Part 4: Do NBA Teams Tend To Go Over Or Under At End Of Season?
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The Sports Betting Whale